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HST.526[J] | Future Medicine: Drug Delivery, Therapeutics, and Diagnostics | Aims to describe the direction and future of medical technology. Introduces pharmaceutics, pharmacology, and conventional medical devices, then transitions to drug delivery systems, mechanical/electric-based and biological/cell-based therapies, and sensors. Covers nano- and micro drug delivery systems, including polymer-drug conjugates, protein therapeutics, liposomes and polymer nanoparticles, viral and non-viral genetic therapy, and tissue engineering. Previous coursework in cell biology and organic chemistry recommended. Students taking graduate version complete additional assignments. Limited to 40. | true | Spring | Graduate | 3-0-6 | 5.12 or permission of instructor | 10.643[J] | false | false | false | False | False | False |
HST.531 | Medical Physics of Proton Radiation Therapy | Acceleration of protons for radiation therapy; introduction into advanced techniques such as laser acceleration and dielectric wall acceleration. Topics include the interactions of protons with the patient, Monte Carlo simulation, and dose calculation methods; biological aspects of proton therapy, relative biological effectiveness (RBE), and the role of contaminating neutrons; treatment planning and treatment optimization methods, and intensity-modulated proton therapy (IMPT); the effect of organ motion and its compensation by use of image-guided treatment techniques; general dosimetry and advanced in-vivo dosimetry methods, including PET/CT and prompt gamma measurements. Outlook into therapy with heavier ions. Includes practical demonstrations at the Proton Therapy Center of the Massachusetts General Hospital. | true | Spring | Graduate | 2-0-4 | null | null | false | false | false | False | False | False |
HST.533 | Medical Imaging in Radiation Therapy | Introduces imaging concepts and applications used throughout radiation therapy workflows, including magnetic resonance imaging (MRI), positron emission tomography (PET), and computed tomography (CT). Advanced topics include proton imaging modalities, such as prompt gamma imaging and proton radiography/CT. Includes lectures regarding image reconstruction and image registration. Introduces students to open-source medical image computing software (3D Slicer, RTK, and Plastimatch). Includes imaging demonstrations at Massachusetts General Hospital. | false | Spring | Graduate | 2-0-4 | 18.06 | null | false | false | false | False | False | False |
HST.535[J] | Tissue Engineering and Organ Regeneration | Principles and practice of tissue engineering (TE) and organ regeneration (OR). Topics include factors that prevent the spontaneous regeneration of tissues/organs in the adult (following traumatic injury, surgical excision, disease, and aging), and molecular and cell-biological mechanisms that can be harnessed for induced regeneration. Presents the basic science of organ regeneration. Principles underlying engineering strategies for employing select biomaterial scaffolds, exogenous cells, soluble regulators, and physical stimuli, for the formation of tissue in vitro (TE) and regeneration of tissues/organs in vivo (OR). Describes the technologies for producing biomaterial scaffolds and for incorporating cells and regulatory molecules into workable devices. Examples of clinical successes and failures of regenerative devices are analyzed as case studies. | true | Fall | Graduate | 3-0-9 | (Biology (GIR), Chemistry (GIR), and Physics I (GIR)) or permission of instructor | 2.787[J] | false | false | false | False | False | False |
HST.537[J] | Fluids and Diseases | Designed for students in engineering and the quantitative sciences who want to explore applications of mathematics, physics and fluid dynamics to infectious diseases and health; and for students in epidemiology, environmental health, ecology, medicine, and systems modeling seeking to understand physical and spatial modeling, and the role of fluid dynamics and physical constraints on infectious diseases and pathologies. The first part of the class reviews modeling in epidemiology and data collection, and highlights concepts of spatial modeling and heterogeneity. The remainder highlights multi-scale dynamics, the role of fluids and fluid dynamics in physiology, and pathology in a range of infectious diseases. The laboratory portion entails activities aimed at integrating applied learning with theoretical concepts discussed in lectures and covered in problem sets. Students taking graduate version complete additional assignments. | false | Spring | Graduate | 3-3-6 | null | 1.631[J], 2.250[J] | false | false | false | False | False | False |
HST.538[J] | Genomics and Evolution of Infectious Disease | Provides a thorough introduction to the forces driving infectious disease evolution, practical experience with bioinformatics and computational tools, and discussions of current topics relevant to public health. Topics include mechanisms of genome variation in bacteria and viruses, population genetics, outbreak detection and tracking, strategies to impede the evolution of drug resistance, emergence of new disease, and microbiomes and metagenomics. Discusses primary literature and computational assignments. Students taking graduate version complete additional assignments. | true | Spring | Graduate | 3-0-9 | Biology (GIR) and (1.000 or 6.100B) | 1.881[J] | false | false | false | False | False | False |
HST.539[J] | Advances in Interdisciplinary Science in Human Health and Disease | Introduces major principles, concepts, and clinical applications of biophysics, biophysical chemistry, and systems biology. Emphasizes biological macromolecular interactions, biochemical reaction dynamics, and genomics. Discusses current technological frontiers and areas of active research at the interface of basic and clinical science. Provides integrated, interdisciplinary training and core experimental and computational methods in molecular biochemistry and genomics. | true | Spring | Graduate | 3-0-9 | 5.13, 5.601, 5.602, and (5.07 or 7.05) | 5.64[J] | false | false | false | False | False | False |
HST.540[J] | Human Physiology | Comprehensive exploration of human physiology, emphasizing the molecular basis and applied aspects of organ function and regulation in health and disease. Includes a review of cell structure and function, as well as the mechanisms by which the endocrine and nervous systems integrate cellular metabolism. Special emphasis on examining the cardiovascular, pulmonary, gastrointestinal, and renal systems, as well as liver function, drug metabolism, and pharmacogenetics. | true | Fall | Undergraduate | 5-0-7 | 7.05 | 7.20[J] | false | false | false | False | False | False |
HST.541[J] | Cellular Neurophysiology and Computing | Integrated overview of the biophysics of cells from prokaryotes to neurons, with a focus on mass transport and electrical signal generation across cell membrane. First third of course focuses on mass transport through membranes: diffusion, osmosis, chemically mediated, and active transport. Second third focuses on electrical properties of cells: ion transport to action potential generation and propagation in electrically excitable cells. Synaptic transmission. Electrical properties interpreted via kinetic and molecular properties of single voltage-gated ion channels. Final third focuses on biophysics of synaptic transmission and introduction to neural computing. Laboratory and computer exercises illustrate the concepts. Students taking graduate version complete different assignments. | true | Spring | Graduate | 5-2-5 | (Physics II (GIR), 18.03, and (2.005, 6.2000, 6.3000, 10.301, or 20.110)) or permission of instructor | 2.794[J], 6.4812[J], 9.021[J], 20.470[J] | false | false | false | False | False | False |
HST.542[J] | Quantitative and Clinical Physiology | Application of the principles of energy and mass flow to major human organ systems. Anatomical, physiological and clinical features of the cardiovascular, respiratory and renal systems. Mechanisms of regulation and homeostasis. Systems, features and devices that are most illuminated by the methods of physical sciences and engineering models. Required laboratory work includes animal studies. Students taking graduate version complete additional assignments. | true | Fall | Undergraduate | 4-2-6 | Physics II (GIR), 18.03, or permission of instructor | 2.792[J], 6.4820[J] | false | false | false | False | False | False |
HST.552[J] | Medical Device Design | Provides an intense project-based learning experience around the design of medical devices with foci ranging from mechanical to electro mechanical to electronics. Projects motivated by real-world clinical challenges provided by sponsors and clinicians who also help mentor teams. Covers the design process, project management, and fundamentals of mechanical and electrical circuit and sensor design. Students work in small teams to execute a substantial term project, with emphasis placed upon developing creative designs — via a deterministic design process — that are developed and optimized using analytical techniques. Includes mandatory lab. Instruction and practice in written and oral communication provided. Students taking graduate version complete additional assignments. Enrollment limited. | true | Spring | Graduate | 3-3-6 | 2.008, 6.2040, 6.2050, 6.2060, 22.071, or permission of instructor | 2.75[J], 6.4861[J] | false | false | false | False | False | False |
HST.560[J] | Radiation Biophysics | Provides a background in sources of radiation with an emphasis on terrestrial and space environments and on industrial production. Discusses experimental approaches to evaluating biological effects resulting from irradiation regimes differing in radiation type, dose and dose-rate. Effects at the molecular, cellular, organism, and population level are examined. Literature is reviewed identifying gaps in our understanding of the health effects of radiation, and responses of regulatory bodies to these gaps is discussed. Students taking graduate version complete additional assignments. | true | Fall | Graduate | 3-0-9 | Permission of instructor | 22.55[J] | false | false | false | False | False | False |
HST.562[J] | Pioneering Technologies for Interrogating Complex Biological Systems | Introduces pioneering technologies in biology and medicine and discusses their underlying biological/molecular/engineering principles. Topics include emerging sample processing technologies, advanced optical imaging modalities, and next-gen molecular phenotyping techniques. Provides practical experience with optical microscopy and 3D phenotyping techniques. Limited to 15. | true | Spring | Graduate | 3-0-9 | null | 9.271[J], 10.562[J] | false | false | false | False | False | False |
HST.563 | Imaging Biophysics and Clinical Applications | Introduction to the connections and distinctions among various imaging modalities (x-ray, optical, ultrasound, MRI, PET, SPECT, EEG), common goals of biomedical imaging, broadly defined target of biomedical imaging, and the current practical and economic landscape of biomedical imaging research. Emphasis on applications of imaging research. Final project consists of student groups writing mock grant applications for biomedical imaging research project, modeled after an exploratory National Institutes of Health (NIH) grant application. | true | Spring | Graduate | 2-1-9 | (8.03 and 18.03) or permission of instructor | null | false | false | false | False | False | False |
HST.565 | Medical Imaging Sciences and Applications | Covers biophysical, biomedical, mathematical and instrumentation basics of positron emission tomography (PET), x-ray and computed tomography (CT), magnetic resonance imaging (MRI), single photon emission tomography (SPECT), optical Imaging and ultrasound. Topics include particles and photon interactions, nuclear counting statistics, gamma cameras, and computed tomography as it pertains to SPECT and PET (PET-CT, PET-MR, time-of-flight PET), MR physics and various sequences, optical and ultrasound physics foundations for imaging. Discusses clinical applications of PET and MR in molecular imaging of the brain, the heart, cancer and the role of AI in medical imaging. Includes medical demonstration lectures of SPECT, PET-CT and PET-MR imaging at Massachusetts General Hospital. Considers the ways imaging techniques are rooted in physics, engineering, and mathematics, and their respective role in anatomic and physiologic/molecular imaging. | true | Fall | Graduate | 3-0-9 | null | null | false | false | false | False | False | False |
HST.576[J] | Topics in Neural Signal Processing | Presents signal processing and statistical methods used to study neural systems and analyze neurophysiological data. Topics include state-space modeling formulated using the Bayesian Chapman-Kolmogorov system, theory of point processes, EM algorithm, Bayesian and sequential Monte Carlo methods. Applications include dynamic analyses of neural encoding, neural spike train decoding, studies of neural receptive field plasticity, algorithms for neural prosthetic control, EEG and MEG source localization. Students should know introductory probability theory and statistics. | false | Spring | Graduate | 3-0-9 | Permission of instructor | 9.272[J] | false | false | false | False | False | False |
HST.580[J] | Data Acquisition and Image Reconstruction in MRI | Applies analysis of signals and noise in linear systems, sampling, and Fourier properties to magnetic resonance (MR) imaging acquisition and reconstruction. Provides adequate foundation for MR physics to enable study of RF excitation design, efficient Fourier sampling, parallel encoding, reconstruction of non-uniformly sampled data, and the impact of hardware imperfections on reconstruction performance. Surveys active areas of MR research. Assignments include Matlab-based work with real data. Includes visit to a scan site for human MR studies. | true | Fall | Graduate | 3-0-9 | 6.3010 | 6.8810[J] | false | false | false | False | False | False |
HST.582[J] | Biomedical Signal and Image Processing | Fundamentals of digital signal processing with emphasis on problems in biomedical research and clinical medicine. Basic principles and algorithms for processing both deterministic and random signals. Topics include data acquisition, imaging, filtering, coding, feature extraction, and modeling. Lab projects, performed in MATLAB, provide practical experience in processing physiological data, with examples from cardiology, speech processing, and medical imaging. Lectures cover signal processing topics relevant to the lab exercises, as well as background on the biological signals processed in the labs. Students taking graduate version complete additional assignments. | true | Spring | Graduate | 3-1-8 | (6.3700 and (2.004, 6.3000, 16.002, or 18.085)) or permission of instructor | 6.8800[J], 16.456[J] | false | false | false | False | False | False |
HST.583[J] | Functional Magnetic Resonance Imaging: Data Acquisition and Analysis | Provides background necessary for designing, conducting, and interpreting fMRI studies in the human brain. Covers in depth the physics of image encoding, mechanisms of anatomical and functional contrasts, the physiological basis of fMRI signals, cerebral hemodynamics, and neurovascular coupling. Also covers design methods for stimulus-, task-driven and resting-state experiments, as well as workflows for model-based and data-driven analysis methods for data. Instruction in brain structure analysis and surface- and region-based analyses. Laboratory sessions include data acquisition sessions at the 3 Tesla MRI scanner at MIT and the Connectom and 7 Tesla scanners at the MGH/HST Martinos Center, as well as hands-on data analysis workshops. Introductory or college-level neurobiology, physics, and signal processing are helpful. | false | Fall | Graduate | 2-3-7 | 18.05 and (18.06 or permission of instructor) | 9.583[J] | false | false | false | False | False | False |
HST.584[J] | Magnetic Resonance Analytic, Biochemical, and Imaging Techniques | Introduction to basic NMR theory. Examples of biochemical data obtained using NMR summarized along with other related experiments. Detailed study of NMR imaging techniques includes discussions of basic cross-sectional image reconstruction, image contrast, flow and real-time imaging, and hardware design considerations. Exposure to laboratory NMR spectroscopic and imaging equipment included. | false | Spring | Graduate | 3-0-12 | Permission of instructor | 22.561[J] | false | false | false | False | False | False |
HST.590 | Biomedical Engineering Seminar Series | Seminars focused on the development of professional skills for biomedical engineers and scientists. Each term focuses on a different topic, resulting in a repeating cycle that covers biomedical and research ethics, business and entrepreneurship, global health and biomedical innovation, and health systems and policy. Includes guest lectures, case studies, interactive small group discussions, and role-playing simulations. | true | Fall, Spring | Graduate | 1-0-0 [P/D/F] | null | null | false | false | false | False | False | False |
HST.599 | Research in Health Sciences and Technology | For students conducting pre-thesis research or lab rotations in HST, in cases where the assigned research is approved for academic credit by the department. Hours arranged with research advisor. Restricted to HST students. | true | Fall, IAP, Spring, Summer | Graduate | rranged [P/D/F] | Permission of instructor | null | false | false | false | False | False | False |
HST.714[J] | Introduction to Sound, Speech, and Hearing | Introduces students to the acoustics, anatomy, physiology, and mechanics related to speech and hearing. Focuses on how humans generate and perceive speech. Topics related to speech, explored through applications and challenges involving acoustics, speech recognition, and speech disorders, include acoustic theory of speech production, basic digital speech processing, control mechanisms of speech production and basic elements of speech and voice perception. Topics related to hearing include acoustics and mechanics of the outer ear, middle ear, and cochlea, how pathologies affect their function, and methods for clinical diagnosis. Surgical treatments and medical devices such as hearing aids, bone conduction devices, and implants are also covered. | true | Fall | Graduate | 4-0-8 | (6.3000 and 8.03) or permission of instructor | 9.016[J] | false | false | false | False | False | False |
HST.716[J] | Signal Processing by the Auditory System: Perception | Studies information processing performance of the human auditory system in relation to current physiological knowledge. Examines mathematical models for the quantification of auditory-based behavior and the relation between behavior and peripheral physiology, reflecting the tono-topic organization and stochastic responses of the auditory system. Mathematical models of psychophysical relations, incorporating quantitative knowledge of physiological transformations by the peripheral auditory system. | true | Fall | Graduate | 3-0-9 | (6.3000 and (6.3700 or 6.3702)) or permission of instructor | 6.8830[J] | false | false | false | False | False | False |
HST.723[J] | Audition: Neural Mechanisms, Perception and Cognition | Neural structures and mechanisms mediating the detection, localization and recognition of sounds. General principles are conveyed by theme discussions of auditory masking, sound localization, musical pitch, cochlear implants, cortical plasticity and auditory scene analysis. Follows Harvard FAS calendar. | true | Spring | Graduate | 6-0-6 | Permission of instructor | 9.285[J] | false | false | false | False | False | False |
HST.728[J] | Spoken Language Processing | Introduces the rapidly developing field of spoken language processing including automatic speech recognition. Topics include acoustic theory of speech production, acoustic-phonetics, signal representation, acoustic and language modeling, search, hidden Markov modeling, neural networks models, end-to-end deep learning models, and other machine learning techniques applied to speech and language processing topics. Lecture material intersperses theory with practice. Includes problem sets, laboratory exercises, and open-ended term project. | true | Spring | Graduate | 3-1-8 | 6.3000 and 6.3900 | 6.8620[J] | false | false | false | False | False | False |
HST.916[J] | Case Studies and Strategies in Drug Discovery and Development | Aims to develop appreciation for the stages of drug discovery and development, from target identification, to the submission of preclinical and clinical data to regulatory authorities for marketing approval. Following introductory lectures on the process of drug development, students working in small teams analyze how one of four new drugs or drug candidates traversed the discovery/development landscape. For each case, an outside expert from the sponsoring drug company or pivotal clinical trial principal investigator provides guidance and critiques the teams' presentations to the class. | true | Spring | Graduate | 2-0-4 | null | 7.549[J], 15.137[J], 20.486[J] | false | false | false | False | False | False |
HST.918[J] | Economics of Health Care Industries | Uses economics as a framework to consider healthcare issues, including differences between health care and other industries, the role of health insurance, regulatory issues and incentives for innovation, data analytics to measure value, personalized/stratified medicines, strategic issues in pricing and marketing, use of e-commerce and information technology, and formation and management of various alliances. Provides a better understanding of the US healthcare landscape, and considers incentives for global health investments. Visiting speakers from industry and academia provide multiple expert viewpoints on these topics. Expectations and evaluation criteria differ for students taking the graduate version; consult syllabus or instructor for specific details. | true | Spring | Graduate | 3-0-3 | null | 15.141[J] | false | false | false | False | False | False |
HST.920[J] | Principles and Practice of Drug Development | Description and critical assessment of the major issues and stages of developing a pharmaceutical or biopharmaceutical. Drug discovery, preclinical development, clinical investigation, manufacturing and regulatory issues considered for small and large molecules. Economic and financial considerations of the drug development process. Multidisciplinary perspective from faculty in clinical; life; and management sciences; as well as industry guests. | true | Fall | Graduate | 3-0-6 | Permission of instructor | 10.547[J], 15.136[J], IDS.620[J] | false | false | false | False | False | False |
HST.936 | Global Health Informatics to Improve Quality of Care | Addresses issues related to how health information systems can improve the quality of care in resource poor settings. Discusses key challenges and real problems; design paradigms and approaches; and system evaluation and the challenges of measuring impact. Weekly lectures led by internationally recognized experts in the field. Students taking HST.936, HST.937 and HST.938 attend common lectures; assignments and laboratory time differ. HST.936 has no laboratory. | true | Spring | Graduate | 2-0-1 | null | null | false | false | false | False | False | False |
HST.937 | Global Health Informatics to Improve Quality of Care | Addresses issues related to how health information systems can improve the quality of care in resource poor settings. Discusses key challenges and real problems; design paradigms and approaches; and system evaluation and the challenges of measuring impact. Weekly lectures led by internationally recognized experts in the field. Students taking HST.936, HST.937 and HST.938 attend common lectures; assignments and laboratory time differ. HST.936 has no laboratory. | true | Spring | Graduate | 2-2-2 | null | null | false | false | false | False | False | False |
HST.938 | Global Health Informatics to Improve Quality of Care | Addresses issues related to how health information systems can improve the quality of care in resource poor settings. Discusses key challenges and real problems; design paradigms and approaches; and system evaluation and the challenges of measuring impact. Weekly lectures led by internationally recognized experts in the field. Students taking HST.936, HST.937 and HST.938 attend common lectures; assignments and laboratory time differ. HST.936 has no laboratory. | true | Spring | Graduate | 2-2-8 | null | null | false | false | false | False | False | False |
HST.940[J] | Bioinformatics: Principles, Methods and Applications | Introduction to bioinformatics, the collection of principles and computational methods used to upgrade the information content of biological data generated by genome sequencing, proteomics, and cell-wide physiological measurements of gene expression and metabolic fluxes. Fundamentals from systems theory presented to define modeling philosophies and simulation methodologies for the integration of genomic and physiological data in the analysis of complex biological processes. Various computational methods address a broad spectrum of problems in functional genomics and cell physiology. Application of bioinformatics to metabolic engineering, drug design, and biotechnology also discussed. | true | Spring | Graduate | 3-0-9 | Permission of instructor | 10.555[J] | false | false | false | False | False | False |
HST.953[J] | Clinical Data Learning, Visualization, and Deployments | Examines the practical considerations for operationalizing machine learning in healthcare settings, with a focus on robust, private, and fair modeling using real retrospective healthcare data. Explores the pre-modeling creation of dataset pipeline to the post-modeling "implementation science," which addresses how models are incorporated at the point of care. Students complete three homework assignments (one each in machine learning, visualization, and implementation), followed by a project proposal and presentation. Students gain experience in dataset creation and curation, machine learning training, visualization, and deployment considerations that target utility and clinical value. Students partner with computer scientists, engineers, social scientists, and clinicians to better appreciate the multidisciplinary nature of data science. | true | Fall | Graduate | 3-0-9 | (6.7900 and 6.7930) or permission of instructor | 6.8850[J] | false | false | false | False | False | False |
HST.956[J] | Machine Learning for Healthcare | Introduces students to machine learning in healthcare, including the nature of clinical data and the use of machine learning for risk stratification, disease progression modeling, precision medicine, diagnosis, subtype discovery, and improving clinical workflows. Topics include causality, interpretability, algorithmic fairness, time-series analysis, graphical models, deep learning and transfer learning. Guest lectures by clinicians from the Boston area, and projects with real clinical data, emphasize subtleties of working with clinical data and translating machine learning into clinical practice. | true | Spring | Graduate | 4-0-8 | 6.3900, 6.4100, 6.7810, 6.7900, 6.8611, or 9.520 | 6.7930[J] | false | false | false | False | False | False |
HST.962 | Medical Product Development and Translational Biomedical Research | Explores the translation of basic biomedical science into therapies. Topics span pharmaceutical, medical device, and diagnostics development. Exposes students to strategic assessment of clinical areas, product comparison, regulatory risk assessment by indication, and rational safety program design. Develops quantitative understanding of statistics and trial design. | true | Spring | Graduate | 1-0-3 | Permission of instructor | null | false | false | false | False | False | False |
HST.971[J] | Strategic Decision Making in Life Science Ventures | Surveys key strategic decisions faced by managers, investors and scientists at each stage in the value chain of the life science industry. Aims to develop students' ability to understand and effectively assess these strategic challenges. Focuses on the biotech sector, with additional examples from the digital health and precision medicine industries. Includes case studies, analytical models, and detailed quantitative analysis. Intended for students interested in building a life science company or working in the sector as a manager, consultant, analyst, or investor. Provides analytical background to the industry for biological and biomedical scientists, engineers and physicians with an interest in understanding the commercial dynamics of the life sciences or the commercial potential of their research. | true | Spring | Graduate | 3-0-6 | null | 15.363[J] | false | false | false | False | False | False |
HST.974 | Innovating for Mission Impact in Medicine and Healthcare | Through a mentored experience, and in conjunction with the MIT Catalyst program, participants develop and validate a small portfolio of research opportunities/proposals. Provides experience with critical professional skills (interfacing with diverse experts, research strategy, critically evaluating the landscape and potential to add value, proposal development, communication, etc.) that heightens the potential to have meaningful impact through their work and career. Restricted to MIT Catalyst Fellows. | true | Fall, Spring | Graduate | 3-0-9 | Permission of instructor | null | false | false | false | False | False | False |
HST.978[J] | Healthcare Ventures | Addresses healthcare entrepreneurship with an emphasis on startups bridging care re-design, digital health, medical devices, and new healthcare business models. Includes prominent speakers and experts from key domains across venture capital, medicine, pharma, med devices, regulatory, insurance, software, design thinking, entrepreneurship, including many alumni from the class sharing their journeys. Provides practical experiences in venture validation/creation through team-based work around themes. Illustrates best practices in identifying and validating health venture opportunities amid challenges of navigating healthcare complexity, team dynamics, and venture capital raising process. Intended for students from engineering, medicine, public health, and MBA programs. Video conference facilities provided to facilitate remote participation by Executive MBA and traveling students. | true | Spring | Graduate | 3-0-9 | null | 15.367[J] | false | false | false | False | False | False |
HST.980 | Emerging Problems in Infectious Diseases | Introduces contemporary challenges in preventing, detecting, diagnosing and treating emerging and newly emerging pathogens. Provides students with team-based opportunities to brainstorm, propose and present innovative solutions to such challenges. Expert lecturers discuss emerging problems in infectious diseases. Includes brainstorming sessions in which student teams identify problems in infectious diseases and propose innovative solutions. The teams then prepare and deliver short presentations, outlining identified problems and solutions. | true | IAP | Graduate | 1-0-2 [P/D/F] | null | null | false | false | false | False | False | False |
HST.999 | Practical Experience in Health Sciences and Technology | Required for HST PhD students to gain professional perspective in research experiences, academic experiences, or internships related to health sciences and technology. Professional perspective options include: internships (with industry, government, medicine or academia), industrial or medical colloquia or seminars, research collaboration with industry or government, and professional development for entry into academia or entrepreneurial engagement. For an internship experience, an offer of employment from a company or organization is required prior to enrollment. Upon completion of the activity, student must submit a letter from the employer describing the work accomplished, along with a substantive final report written by the student. Consult HST's Academic Office for details on procedures and restrictions. | true | Fall, IAP, Spring, Summer | Graduate | rranged [P/D/F] | null | null | false | false | false | False | False | False |
HST.THG | Graduate Thesis | Program of research leading to the writing of a PhD or ScD thesis or an HST SM thesis; to be arranged by the student and an appropriate faculty advisor. | true | Fall, IAP, Spring, Summer | Graduate | rranged | Permission of instructor | null | false | false | false | False | False | False |
HST.UR | Undergraduate Research in Health Sciences and Technology | Extended participation in the work of a faculty member or research group. Research is arranged by mutual agreement between the student and a member of the faculty of the Harvard-MIT Program Health Sciences and Technology, and may continue over several terms. Registration requires submission of a written proposal to the MIT UROP, signed by the faculty advisor and approved by the department. A summary report must be submitted at the end of each term. | true | Fall, IAP, Spring, Summer | Undergraduate | rranged [P/D/F] | null | null | false | false | false | False | False | False |
HST.URG | Undergraduate Research in Health Sciences and Technology | Extended participation in the work of a faculty member or research group. Research is arranged by mutual agreement between the student and a member of the faculty of the Harvard-MIT Program in Health Sciences and Technology, and may continue over several terms. Registration requires submission of a written proposal to the MIT UROP Office; signed by the faculty advisor and approved by the department. A summary report must be submitted at the end of each term. | true | Fall, IAP, Spring, Summer | Undergraduate | rranged | null | null | false | false | false | False | False | False |
HST.S16 | Special Graduate Subject: Health Sciences and Technology | Opportunity for group study of advanced subjects related to Health Sciences and Technology not otherwise included in the curriculum. Offerings are initiated by IMES/HST faculty on an ad hoc basis subject to program approval. Prerequisites may vary by topic; consult faculty at time of offering. | true | Fall, IAP, Spring, Summer | Graduate | rranged [P/D/F] | null | null | false | false | false | False | False | False |
HST.S17 | Special Graduate Subject: Health Sciences and Technology | Opportunity for group study of advanced subjects related to Health Sciences and Technology not otherwise included in the curriculum. Offerings are initiated by IMES/HST faculty on an ad hoc basis subject to program approval. Prerequisites may vary by topic; consult faculty at time of offering. | true | Fall, IAP, Spring, Summer | Graduate | rranged [P/D/F] | Permission of instructor | null | false | false | false | False | False | False |
HST.S18 | Special Graduate Subject: Health Sciences and Technology | Opportunity for group study of advanced subjects related to Health Sciences and Technology not otherwise included in the curriculum. Offerings are initiated by IMES/HST faculty on an ad hoc basis subject to program approval. Prerequisites may vary by topic; consult faculty at time of offering. | true | Fall, IAP, Spring, Summer | Graduate | rranged | Permission of instructor | null | false | false | false | False | False | False |
HST.S19 | Special Graduate Subject: Health Sciences and Technology | Opportunity for group study of advanced subjects related to Health Sciences and Technology not otherwise included in the curriculum. Offerings are initiated by IMES/HST faculty on an ad hoc basis subject to program approval. Prerequisites may vary by topic; consult faculty at time of offering. | true | Fall, IAP, Spring, Summer | Graduate | rranged | Permission of instructor | null | false | false | false | False | False | False |
HST.S46 | Special Undergraduate Subject: Health Sciences and Technology | Group study of subjects related to health sciences and technology not otherwise included in the curriculum. Prerequisites may vary by topic; consult faculty at time of offering. | true | Fall, IAP, Spring, Summer | Undergraduate | rranged [P/D/F] | Permission of instructor | null | false | false | false | False | False | False |
HST.S47 | Special Undergraduate Subject: Health Sciences and Technology | Group study of subjects related to health sciences and technology not otherwise included in the curriculum. Prerequisites may vary by topic; consult faculty at time of offering. | true | Fall, IAP, Spring, Summer | Undergraduate | rranged [P/D/F] | Permission of instructor | null | false | false | false | False | False | False |
HST.S48 | Special Undergraduate Subject: Health Sciences and Technology | Group study of subjects related to health sciences and technology not otherwise included in the curriculum. Prerequisites may vary by topic; consult faculty at time of offering. | true | Fall, IAP, Spring, Summer | Undergraduate | rranged | Permission of instructor | null | false | false | false | False | False | False |
HST.S49 | Special Undergraduate Subject: Health Sciences and Technology | Group study of subjects related to health sciences and technology not otherwise included in the curriculum. Prerequisites may vary by topic; consult faculty at time of offering. | true | Fall, IAP, Spring, Summer | Undergraduate | rranged | Permission of instructor | null | false | false | false | False | False | False |
HST.S56 | Special Graduate Subject: Medical Engineering and Medical Physics | Opportunity for group study of advanced subjects related to the Medical Engineering and Medical Physics Program not otherwise included in the curriculum. Offerings are initiated by IMES/HST faculty on an ad hoc basis subject to program approval. Prerequisites may vary by topic; consult faculty at time of offering. | true | Fall | Graduate | rranged [P/D/F] | Permission of instructor | null | false | false | false | False | False | False |
HST.S57 | Special Graduate Subject: Medical Engineering and Medical Physics | Opportunity for group study of advanced subjects related to the Medical Engineering and Medical Physics Program not otherwise included in the curriculum. Offerings are initiated by IMES/HST faculty on an ad hoc basis subject to program approval. Prerequisites may vary by topic; consult faculty at time of offering. | true | Fall, IAP, Spring, Summer | Graduate | rranged [P/D/F] | Permission of instructor | null | false | false | false | False | False | False |
HST.S58 | Special Subject: Medical Engineering and Medical Physics | Opportunity for group study of advanced subjects related to the Medical Engineering and Medical Physics Program not otherwise included in the curriculum. Offerings are initiated by HST faculty on an ad hoc basis subject to program approval. Prerequisites may vary by topic; consult faculty at time of offering. | true | Fall, IAP, Spring, Summer | Graduate | rranged | Permission of instructor | null | false | false | false | False | False | False |
HST.S59 | Special Graduate Subject: Medical Engineering and Medical Physics | Opportunity for group study of advanced subjects related to the Medical Engineering and Medical Physics Program not otherwise included in the curriculum. Offerings are initiated by IMES/HST faculty on an ad hoc basis subject to program approval. Prerequisites may vary by topic; consult faculty at time of offering. | true | Fall, IAP, Spring, Summer | Graduate | rranged | Permission of instructor | null | false | false | false | False | False | False |
HST.S78 | Special Subject: Speech and Hearing Sciences | Opportunity for group study of advanced subjects related to the Speech and Hearing Sciences not otherwise included in the curriculum. Offerings initiated by members of the SHS faculty on an ad hoc basis subject to program approval. Prerequisites may vary by topic; consult faculty at time of offering. | true | Fall, IAP, Spring | Graduate | rranged | Permission of instructor | null | false | false | false | False | False | False |
HST.S96 | Special Graduate Subject: Biomedical Entrepreneurship | Opportunity for group study of advanced subjects relating to biomedical entrepreneurship not otherwise included in the curriculum. Offerings are initiated by HST/IMES faculty on an ad hoc basis subject to program approval. Prerequisites may vary by topic. Consult faculty at time of offering. | true | Fall, IAP, Spring, Summer | Graduate | rranged [P/D/F] | Permission of instructor | null | false | false | false | False | False | False |
HST.S97 | Special Graduate Subject: Biomedical Entrepreneurship | Opportunity for group study of advanced subjects relating to biomedical entrepreneurship not otherwise included in the curriculum. Offerings are initiated by HST faculty on an ad hoc basis subject to program approval. Prerequisites may vary by topic. Consult faculty at time of offering. | true | Fall, IAP, Spring, Summer | Graduate | rranged [P/D/F] | Permission of instructor | null | false | false | false | False | False | False |
HST.S98 | Special Graduate Subject: Biomedical Entrepreneurship | Opportunity for group study of advanced subjects relating to biomedical entrepreneurship not otherwise included in the curriculum. Offerings are initiated by HST faculty on an ad hoc basis subject to program approval. Prerequisites may vary by topic. Consult faculty at time of offering. | true | Fall, Spring | Graduate | rranged | Permission of instructor | null | false | false | false | False | False | False |
HST.S99 | Special Graduate Subject: Biomedical Entrepreneurship | Opportunity for group study of advanced subjects relating to biomedical entrepreneurship not otherwise included in the curriculum. Offerings are initiated by HST faculty on an ad hoc basis subject to program approval. Prerequisites may vary by topic. Consult faculty at time of offering.
HST/IMES Faculty | true | Fall, IAP, Spring, Summer | Graduate | rranged | Permission of instructor | null | false | false | false | False | False | False |
IDS.012[J] | Statistics, Computation and Applications | Hands-on analysis of data demonstrates the interplay between statistics and computation. Includes four modules, each centered on a specific data set, and introduced by a domain expert. Provides instruction in specific, relevant analysis methods and corresponding algorithmic aspects. Potential modules may include medical data, gene regulation, social networks, finance data (time series), traffic, transportation, weather forecasting, policy, or industrial web applications. Projects address a large-scale data analysis question. Students taking graduate version complete additional assignments. Enrollment limited; priority to Statistics and Data Science minors, and to juniors and seniors. | true | Spring | Undergraduate | 3-1-8 | (6.100B, (18.03, 18.06, or 18.C06), and (6.3700, 6.3800, 14.30, 16.09, or 18.05)) or permission of instructor | 6.3730[J] | false | false | false | False | False | False |
IDS.013[J] | Statistical Thinking and Data Analysis | Introduces a rigorous treatment of statistical data analysis while helping students develop a strong intuition for the strengths and limitations of various methods. Topics include statistical sampling and uncertainty, estimation, hypothesis testing, linear regression, classification, analysis of variation, and elements of data mining. Involves empirical use of hypothesis testing and other statistical methodologies in several domains, including the assessment of A-B experiments on the web and the identification of genes correlated with diseases. | true | Spring | Undergraduate | 3-1-8 | 6.3700 or 15.069 | 15.075[J] | true | false | false | False | False | False |
IDS.014[J] | Fundamentals of Statistics | A rapid introduction to the theoretical foundations of statistical methods that are useful in many applications. Covers a broad range of topics in a short amount of time with the goal of providing a rigorous and cohesive understanding of the modern statistical landscape. Mathematical language is used for intuition and basic derivations but not proofs. Main topics include: parametric estimation, confidence intervals, hypothesis testing, Bayesian inference, and linear and logistic regression. Additional topics may include: causal inference, nonparametric estimation, and classification. | true | Fall, Spring | Undergraduate | 4-0-8 | 6.3700 or 18.600 | 18.650[J] | false | false | false | False | False | False |
IDS.045[J] | System Safety | Introduces the concepts of system safety and how to analyze and design safer systems. Topics include the causes of accidents in general, and recent major accidents in particular; hazard analysis, safety-driven design techniques; design of human-automation interaction; integrating safety into the system engineering process; and managing and operating safety-critical systems. | true | Fall | Undergraduate | 3-0-9 | null | 16.63[J] | false | false | true | False | False | False |
IDS.050[J] | Cybersecurity | Focuses on the complexity of cybersecurity in a changing world. Examines national and international aspects of overall cyber ecology. Explores sources and consequences of cyber threats and different types of damages. Considers impacts for and of various aspects of cybersecurity in diverse geostrategic, political, business and economic contexts. Addresses national and international policy responses as well as formal and informal strategies and mechanisms for responding to cyber insecurity and enhancing conditions of cybersecurity. Students taking graduate version expected to pursue subject in greater depth through reading and individual research. | true | Spring | Undergraduate | 3-0-9 | null | 17.447[J], MAS.460[J] | false | false | false | False | Social Sciences | False |
IDS.055[J] | Science, Technology, and Public Policy | Analysis of issues at the intersection of science, technology, public policy, and business. Cases drawn from antitrust and intellectual property rights; health and environmental policy; defense procurement and strategy; strategic trade and industrial policy; and R&D funding. Structured around theories of political economy, modified to take into account integration of uncertain technical information into public and private decision-making. Meets with 17.310 when offered concurrently. | true | Fall | Undergraduate | 4-0-8 | null | 17.309[J], STS.082[J] | false | false | false | False | Social Sciences | CI-H |
IDS.057[J] | Data and Society | Introduces students to the social, political, and ethical aspects of data science work. Designed to create reflective practitioners who are able to think critically about how collecting, aggregating, and analyzing data are social processes and processes that affect people. | true | Spring | Undergraduate | 3-0-9 | null | 11.155[J], STS.005[J] | false | false | false | False | Humanities | False |
IDS.060[J] | Environmental Law, Policy, and Economics: Pollution Prevention and Control | Analyzes federal and state regulation of air and water pollution, hazardous waste, greenhouse gas emissions, and production/use of toxic chemicals. Analyzes pollution/climate change as economic problems and failure of markets. Explores the role of science and economics in legal decisions. Emphasizes use of legal mechanisms and alternative approaches (i.e., economic incentives, voluntary approaches) to control pollution and encourage chemical accident and pollution prevention. Focuses on major federal legislation, underlying administrative system, and common law in analyzing environmental policy, economic consequences, and role of the courts. Discusses classical pollutants and toxic industrial chemicals, greenhouse gas emissions, community right-to-know, and environmental justice. Develops basic legal skills: how to read/understand cases, regulations, and statutes. Students taking graduate version explore the subject in greater depth. | true | Spring | Undergraduate | 3-0-9 | null | 1.801[J], 11.021[J], 17.393[J] | false | false | false | False | Social Sciences | False |
IDS.061[J] | Regulation of Chemicals, Radiation, and Biotechnology | Focuses on policy design and evaluation in the regulation of hazardous substances and processes. Includes risk assessment, industrial chemicals, pesticides, food contaminants, pharmaceuticals, radiation and radioactive wastes, product safety, workplace hazards, indoor air pollution, biotechnology, victims' compensation, and administrative law. Health and economic consequences of regulation, as well as its potential to spur technological change, are discussed for each regulatory regime. Students taking the graduate version are expected to explore the subject in greater depth. | true | Spring | Undergraduate | 3-0-9 | IDS.060 or permission of instructor | 1.802[J], 11.022[J] | false | false | false | False | False | False |
IDS.062[J] | Global Environmental Negotiations | Practical introduction to global environmental negotiations designed for science and engineering students. Covers basic issues in international negotiations, such as North-South conflict, implementation and compliance, trade, and historical perspective on global environmental treaties. Offers hands-on practice in developing and interpreting international agreements through role-play simulations and observation of ongoing climate change negotiating processes. Students taking graduate version complete additional assignments. | true | Fall | Undergraduate | 2-0-4 | Permission of instructor | 12.346[J] | false | false | false | False | False | False |
IDS.063[J] | People and the Planet: Environmental Governance and Science | Introduces governance and science aspects of complex environmental problems and approaches to solutions. Introduces quantitative analyses and methodological tools to analyze environmental issues that have human and natural components. Demonstrates concepts through a series of in-depth case studies of environmental governance and science problems. Students develop writing, quantitative modeling, and analytical skills in assessing environmental systems problems and developing solutions. Through experiential activities, such as modeling and policy exercises, students engage with the challenges and possibilities of governance in complex, interacting systems, including biogeophysical processes and societal and stakeholder interactions. | true | Fall | Undergraduate | 3-0-6 | null | 12.387[J], 15.874[J] | false | false | false | False | False | False |
IDS.065[J] | Energy Systems for Climate Change Mitigation | Reviews the contributions of energy systems to global greenhouse gas emissions, and the levers for reducing those emissions. Lectures and projects focus on evaluating energy systems against climate policy goals, using performance metrics such as cost, carbon intensity, and others. Student projects explore pathways for realizing emissions reduction scenarios. Projects address the climate change mitigation potential of energy technologies (hardware and software), technological and behavioral change trajectories, and technology and policy portfolios. Background in energy systems strongly recommended. Students taking the graduate version complete additional assignments and explore the subject in greater depth. Preference to students in the Energy Studies or Environment and Sustainability minors. | true | Fall | Undergraduate | 3-0-9 | (Calculus I (GIR), Chemistry (GIR), and Physics I (GIR)) or permission of instructor | 1.067[J], 10.421[J] | false | false | false | False | False | False |
IDS.066[J] | Law, Technology, and Public Policy | Examines how law, economics, and technological change shape public policy, and how law can sway technological change; how the legal system responds to environmental, safety, energy, social, and ethical problems; how law and markets interact to influence technological development; and how law can affect wealth distribution, employment, and social justice. Covers energy/climate change; genetic engineering; telecommunications and role of misinformation; industrial automation; effect of regulation on technological innovation; impacts of antitrust law on innovation and equity; pharmaceuticals; nanotechnology; cost/benefit analysis as a decision tool; public participation in governmental decisions affecting science and technology; corporate influence on technology and welfare; and law and economics as competing paradigms to encourage sustainability. Students taking graduate version explore subject in greater depth. | true | Fall | Undergraduate | 3-0-9 | null | 11.122[J] | false | false | false | False | Social Sciences | False |
IDS.075[J] | Transportation: Foundations and Methods | Covers core analytical and numerical methods for modeling, planning, operations, and control of transportation systems. Traffic flow theory, vehicle dynamics and behavior, numerical integration and simulation, graphical analysis. Properties of delays, queueing theory. Resource allocation, optimization models, linear and integer programming. Autonomy in transport, Markov Decision Processes, reinforcement learning, deep learning. Applications drawn broadly from land, air, and sea transport; private and public sector; transport of passengers and goods; futuristic, modern, and historical. Hands-on computational labs. Linear algebra background is encouraged but not required. Students taking graduate version complete additional assignments. | true | Spring | Undergraduate | 3-1-8 | (1.010A and (1.00 or 1.000)) or permission of instructor | 1.041[J] | false | false | false | False | False | False |
IDS.131[J] | Statistics, Computation and Applications | Hands-on analysis of data demonstrates the interplay between statistics and computation. Includes four modules, each centered on a specific data set, and introduced by a domain expert. Provides instruction in specific, relevant analysis methods and corresponding algorithmic aspects. Potential modules may include medical data, gene regulation, social networks, finance data (time series), traffic, transportation, weather forecasting, policy, or industrial web applications. Projects address a large-scale data analysis question. Students taking graduate version complete additional assignments. Limited enrollment; priority to Statistics and Data Science minors and to juniors and seniors. | true | Spring | Graduate | 3-1-8 | (6.100B, (18.03, 18.06, or 18.C06), and (6.3700, 6.3800, 14.30, 16.09, or 18.05)) or permission of instructor | 6.3732[J] | false | false | false | False | False | False |
IDS.136[J] | Graphical Models: A Geometric, Algebraic, and Combinatorial Perspective | Provides instruction in the geometric, algebraic and combinatorial perspective on graphical models. Presents methods for learning the underlying graph and inferring its parameters. Topics include exponential families, duality theory, conic duality, polyhedral geometry, undirected graphical models, Bayesian networks, Markov properties, total positivity of distributions, hidden variables, and tensor decompositions. | true | Fall | Graduate | 3-0-9 | 6.3702 and 18.06 | 6.7820[J] | false | false | false | False | False | False |
IDS.140[J] | Reinforcement Learning: Foundations and Methods | Examines reinforcement learning (RL) as a methodology for approximately solving sequential decision-making under uncertainty, with foundations in optimal control and machine learning. Provides a mathematical introduction to RL, including dynamic programming, statistical, and empirical perspectives, and special topics. Core topics include: dynamic programming, special structures, finite and infinite horizon Markov Decision Processes, value and policy iteration, Monte Carlo methods, temporal differences, Q-learning, stochastic approximation, and bandits. Also covers approximate dynamic programming, including value-based methods and policy space methods. Applications and examples drawn from diverse domains. Focus is mathematical, but is supplemented with computational exercises. An analysis prerequisite is suggested but not required; mathematical maturity is necessary. | true | Fall | Graduate | 4-0-8 | 6.3700 or permission of instructor | 1.127[J], 6.7920[J] | false | false | false | False | False | False |
IDS.145[J] | Data Mining: Finding the Models and Predictions that Create Value | Introduction to data mining, data science, and machine learning for recognizing patterns, developing models and predictive analytics, and making intelligent use of massive amounts of data collected via the internet, e-commerce, electronic banking, medical databases, etc. Topics include logistic regression, association rules, tree-structured classification and regression, cluster analysis, discriminant analysis, and neural network methods. Presents examples of successful applications in credit ratings, fraud detection, marketing, customer relationship management, investments, and synthetic clinical trials. Introduces data-mining software (R and Python). Grading based on homework, cases, and a term project. Expectations and evaluation criteria differ for students taking the undergraduate version; consult syllabus or instructor for specific details. | true | Spring | Graduate | 2-0-4 | 15.060, 15.075, or permission of instructor | 15.062[J] | false | false | false | False | False | False |
IDS.147[J] | Statistical Machine Learning and Data Science | Advanced introduction to theory and application of statistics, data-mining and machine learning using techniques from management science, marketing, finance, consulting, and bioinformatics. Covers bootstrap theory of estimation, testing, nonparametric statistics, analysis of variance, experimental design, categorical data analysis, regression analysis, MCMC, and Bayesian methods. Focuses on data mining, supervised learning, and multivariate analysis. Topics chosen from logistic regression, principal components and dimension reduction; discrimination and classification analysis, trees (CART), partial least squares, nearest neighbors, regularized methods, support vector machines, boosting and bagging, clustering, independent component analysis, and nonparametric regression. Uses statistics software R, Python, and MATLAB. Grading based on homework, cases, and a term project. | true | Spring | Graduate | 4-0-8 | Permission of instructor | 15.077[J] | false | false | false | False | False | False |
IDS.160[J] | Mathematical Statistics: a Non-Asymptotic Approach | Introduces students to modern non-asymptotic statistical analysis. Topics include high-dimensional models, nonparametric regression, covariance estimation, principal component analysis, oracle inequalities, prediction and margin analysis for classification. Develops a rigorous probabilistic toolkit, including tail bounds and a basic theory of empirical processes | true | Spring | Graduate | 3-0-9 | (6.7700, 18.06, and 18.6501) or permission of instructor | 9.521[J], 18.656[J] | false | false | false | False | False | False |
IDS.190 | Doctoral Seminar in Statistics and Data Science | Interdisciplinary seminar explores diverse topics in statistics and data science. Restricted to students in the Interdisciplinary Doctoral Program in Statistics. | true | Fall | Graduate | 1-0-2 [P/D/F] | null | null | false | false | false | False | False | False |
IDS.250[J] | The Theory of Operations Management | Provides mathematical foundations underlying the theory of operations management. Covers both classic and state-of-the-art results in various application domains, including inventory management, supply chain management and logistics, behavioral operations, healthcare management, service industries, pricing and revenue management, and auctions. Studies a wide range of mathematical and analytical techniques, such as dynamic programming, stochastic orders, principal-agent models and contract design, behavioral and experimental economics, algorithms and approximations, data-driven and learning models, and mechanism design. Also provides practical experience in how to apply the theoretical models to solve OM problems in business settings. Specific topics vary from year to year. | true | Spring | Graduate | 3-0-9 | (6.7210 and 6.7700) or permission of instructor | 1.271[J], 15.764[J] | false | false | false | False | False | False |
IDS.305[J] | Business and Operations Analytics | Provides instruction on identifying, evaluating, and capturing business analytics opportunities that create value. Also provides basic instruction in analytics methods and case study analysis of organizations that successfully deployed these techniques. | true | Spring | Graduate | 2-0-4 | Permission of instructor | 1.275[J] | false | false | false | False | False | False |
IDS.332 | System Design and Management for a Changing World: Combined | Practical-oriented subject that builds upon theory and methods and culminates in extended application. Covers methods to identify, value, and implement flexibility in design (real options). Topics include definition of uncertainties, simulation of performance for scenarios, screening models to identify desirable flexibility, decision analysis, and multidimensional economic evaluation. Students demonstrate proficiency through an extended application to a system design of their choice. Complements research or thesis projects. Class is "flipped" to maximize student engagement and learning. Meets with IDS.333 in the first half of term. Enrollment limited. | true | Fall | Graduate | 3-0-9 | Permission of instructor | null | false | false | false | False | False | False |
IDS.333[J] | System Design and Management for a Changing World: Tools | Focuses on design choices and decisions under uncertainty. Topics include identification and description of uncertainties using probability distributions; the calculation of commensurate measures of value, such as expected net present values; Monte Carlo simulation and risk analysis; and the use of decision analysis to explore alternative strategies and identify optimal initial choices. Presents applied analysis of practical examples from a variety of engineering systems using spreadsheet and decision analysis software. Class is "flipped" to maximize student engagement and learning. Meets with IDS.332 first half of term. | true | Fall | Graduate | 3-0-3 | null | EM.423[J] | false | false | false | False | False | False |
IDS.334[J] | System Design and Management for a Changing World: Projects (IDS.330) | Focuses on implementation of flexibility (real options) in the design of products, start-ups, ongoing management of operations, or policy plans. Applies the methods presented in IDS.333: recognition of uncertainty, identification of best opportunities for flexibility, and valuation of these options and their effective implementation. Students work on their own project concept, for which they develop a dynamic business plan for design, deployment, and most beneficial implementation of their system over time. Useful complement to thesis or research projects. Class is "flipped" to maximize student engagement and learning. Subject meets in second half of term in the fall and first half of term in the spring. | true | Fall, Spring | Graduate | 3-0-3 | IDS.333 or permission of instructor | EM.424[J] | false | false | false | False | False | False |
IDS.336[J] | Systems Architecting Applied to Enterprises | Focuses on understanding, designing and transforming sociotechnical enterprises using systems principles and practices. Includes discussions and reading on enterprise theory, systems architecting, transformation challenges and case studies of evolving enterprises. Covers frameworks and methods for ecosystem analysis, stakeholder analysis, design thinking, systems architecture and evaluation, and human-centered enterprise design strategies. Students engage in interactive breakout sessions during class and participate in a selected small team project to design a future architecture for a real-world enterprise. Selected projects are based on student interests in enterprises such as small, medium, or large companies, government agencies, academic units, start-ups, and nonprofit organizations. | true | Spring | Graduate | 3-0-9 | Permission of instructor | 16.855[J], EM.429[J] | false | false | false | False | False | False |
IDS.337[J] | Aerospace Biomedical and Life Support Engineering | Fundamentals of human performance, physiology, and life support impacting engineering design and aerospace systems. Topics include effects of gravity on the muscle, skeletal, cardiovascular, and neurovestibular systems; human/pilot modeling and human/machine design; flight experiment design; and life support engineering for extravehicular activity (EVA). Case studies of current research are presented. Assignments include a design project, quantitative homework sets, and quizzes emphasizing engineering and systems aspects. | true | Spring | Graduate | 3-0-9 | 16.06, 16.400, or permission of instructor | 16.423[J], HST.515[J] | false | false | false | False | False | False |
IDS.338[J] | Multidisciplinary Design Optimization | Systems modeling for design and optimization. Selection of design variables, objective functions and constraints. Overview of principles, methods and tools in multidisciplinary design optimization (MDO). Subsystem identification, development and interface design. Design of experiments (DOE). Review of linear (LP) and non-linear (NLP) constrained optimization formulations. Scalar versus vector optimization problems. Karush-Kuhn-Tucker (KKT) conditions of optimality, Lagrange multipliers, adjoints, gradient search methods, sensitivity analysis, geometric programming, simulated annealing, genetic algorithms and particle swarm optimization. Constraint satisfaction problems and isoperformance. Non-dominance and Pareto frontiers. Surrogate models and multifidelity optimization strategies. System design for value. Students execute a term project in small teams related to their area of interest. | true | Fall | Graduate | 3-1-8 | 18.085 or permission of instructor | 16.888[J], EM.428[J] | false | false | false | False | False | False |
IDS.339[J] | Space Systems Engineering | Focus on developing space system architectures. Applies subsystem knowledge gained in 16.851 to examine interactions between subsystems in the context of a space system design. Principles and processes of systems engineering including developing space architectures, developing and writing requirements, and concepts of risk are explored and applied to the project. Subject develops, documents, and presents a conceptual design of a space system including a preliminary spacecraft design. | true | Spring | Graduate | 4-2-6 | 16.842, 16.851, or permission of instructor | 16.89[J] | false | false | false | False | False | False |
IDS.340[J] | System Safety Concepts | Covers important concepts and techniques in designing and operating safety-critical systems. Topics include the nature of risk, formal accident and human error models, causes of accidents, fundamental concepts of system safety engineering, system and software hazard analysis, designing for safety, fault tolerance, safety issues in the design of human-machine interaction, verification of safety, creating a safety culture, and management of safety-critical projects. Includes a class project involving the high-level system design and analysis of a safety-critical system. Enrollment may be limited. | true | Fall | Graduate | 3-0-9 | Permission of instructor | 16.863[J] | false | false | false | False | False | False |
IDS.341[J] | Concepts in the Engineering of Software | Reading and discussion on issues in the engineering of software systems and software development project design. Includes the present state of software engineering, what has been tried in the past, what worked, what did not, and why. Topics may differ in each offering, but are chosen from the software process and life cycle; requirements and specifications; design principles; testing, formal analysis, and reviews; quality management and assessment; product and process metrics; COTS and reuse; evolution and maintenance; team organization and people management; and software engineering aspects of programming languages. Enrollment may be limited. | true | Spring | Graduate | 3-0-9 | Permission of instructor | 16.355[J] | false | false | false | False | False | False |
IDS.350[J] | Cybersecurity | Focuses on the complexity of cybersecurity in a changing world. Examines national and international aspects of overall cyber ecology. Explores sources and consequences of cyber threats and different types of damages. Considers impacts for and of various aspects of cybersecurity in diverse geostrategic, political, business and economic contexts. Addresses national and international policy responses as well as formal and informal strategies and mechanisms for responding to cyber insecurity and enhancing conditions of cybersecurity. Students taking graduate version expected to pursue subject in greater depth through reading and individual research. | true | Spring | Graduate | 3-0-9 | Permission of instructor | 17.448[J], MAS.660[J] | false | false | false | False | False | False |
IDS.405 | Critical Internet Studies (CMS.867) | Focuses on the power dynamics in internet-related technologies (including social networking platforms, surveillance technology, entertainment technologies, and emerging media forms). Theories and readings focus on the cultural, social, economic, and political aspects of internet use and design, with a special attention to gender and race. Topics include: online communication and communities, algorithms and search engines, activism and online resistance, surveillance and privacy, content moderation and platform governance, and the spread of dis- and misinformation. Instruction and practice in written and oral communication provided. Students taking the graduate version complete additional readings and assignments. | true | Spring | Graduate | 3-0-9 | null | null | false | false | false | False | False | False |
IDS.410 | Modeling and Assessment for Policy | Explores how scientific information and quantitative models can be used to inform policy decision-making. Develops an understanding of quantitative modeling techniques and their role in the policy process through case studies and interactive activities. Addresses issues such as analysis of scientific assessment processes, uses of integrated assessment models, public perception of quantitative information, methods for dealing with uncertainties, and design choices in building policy-relevant models. | true | Spring | Graduate | 3-0-6 | null | null | false | false | false | False | False | False |
IDS.411 | Concepts and Research in Technology and Policy | Core integrative subject, with substantive participation from a series of guest faculty lecturers, examines key technology-policy concepts. Explores alternative framings of roles of technology in policy, emphasizing the implications of these alternatives upon problem-solving in the area. Exercises prepare students to apply these concepts in the framing of their thesis research. Preference to first-year students in the Technology and Policy Program. | true | Spring | Graduate | 3-0-6 | Permission of instructor | null | false | false | false | False | False | False |
IDS.412[J] | Science, Technology, and Public Policy | Analysis of issues at the intersection of science, technology, public policy, and business. Cases drawn from antitrust and intellectual property rights; health and environmental policy; defense procurement and strategy; strategic trade and industrial policy; and R&D funding. Structured around theories of political economy, modified to take account of integration of uncertain technical information into public and private decision-making. Meets with 17.309 when offered concurrently. | true | Fall | Graduate | 4-0-8 | Permission of instructor | 17.310[J], STS.482[J] | false | false | false | False | False | False |
IDS.435[J] | Law, Technology, and Public Policy | Examines how law, economics, and technological change shape public policy, and how law can sway technological change; how the legal system responds to environmental, safety, energy, social, and ethical problems; how law and markets interact to influence technological development; and how law can affect wealth distribution, employment, and social justice. Covers energy/climate change; genetic engineering; telecommunications and the role of misinformation; industrial automation; effect of regulation on technological innovation; impacts of antitrust law on innovation and equity; pharmaceuticals; nanotechnology; cost/benefit analysis as a decision tool; public participation in governmental decisions affecting science and technology; corporate influence on technology and welfare; and law and economics as competing paradigms to encourage sustainability. Students taking graduate version explore subject in greater depth. | true | Fall | Graduate | 3-0-9 | null | 11.422[J], 15.655[J] | false | false | false | False | False | False |
IDS.436[J] | Technology, Law, and the Working Environment | Addresses relationship between technology-related problems and the law applicable to work environment. National Labor Relations Act, Occupational Safety and Health Act. Toxic Substances Control Act, state worker's compensation, and suits by workers in the courts discussed. Problems related to occupational health and safety, collective bargaining as a mechanism for altering technology in the workplace, job alienation, productivity, and the organization of work addressed. Prior courses or experience in the environmental, public health, or law-related areas. | true | Spring | Graduate | 3-0-6 | Permission of instructor | 10.805[J] | false | false | false | False | False | False |
Subsets and Splits