Niharmahesh commited on
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a03802a
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1 Parent(s): 7bc447d

Update app.py

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  1. app.py +47 -1
app.py CHANGED
@@ -34,7 +34,53 @@ def display_header():
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  def display_summary():
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  #st.markdown('## Summary', unsafe_allow_html=True)
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- st.markdown("""Hello! This is Nihar Palem. I'm originally from Hyderabad and currently residing in the Silicon Valley Bay Area, San Jose. I'm a Graduate with Master's degree in Data Analytics (Applied Data Science) from San Jose State University. In this portfolio, you can explore my academic background, work experience, and projects in the data science field. You'll also find links to my skills, other hobbies, and certifications.""")
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  def display_education():
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  st.markdown('## Education')
 
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  def display_summary():
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  #st.markdown('## Summary', unsafe_allow_html=True)
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+ st.markdown("""
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+ # Welcome to My Portfolio
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+ Hello! I'm **Sai Nihar Reddy Palem**, an Applied AI Engineer, Data Scientist, and AI Researcher currently based in San Jose, California. Originally from Hyderabad, India, I've made the Silicon Valley Bay Area my home as I pursue groundbreaking advancements in artificial intelligence research and translate them into real-world applications.
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+ ## About Me
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+ I'm a passionate AI researcher and practitioner with a **Master's degree in Applied Data Science** from San Jose State University, backed by 2+ years of intensive experience in designing, building, and deploying state-of-the-art multimodal AI systems. My work sits at the intersection of cutting-edge research and production engineering, where I continuously explore the latest advancements in AI research space while building scalable, impactful solutions.
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+ As an AI researcher, I'm deeply committed to pushing the boundaries of what's possible with multimodal AI, Large Language Models, and multi-agent architectures. I systematically adapt cutting-edge research papers into practical applications, focusing on reproducible results, performance benchmarking, and production deployment considerations.
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+ ## Research & Innovation Focus
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+ My research interests and contributions span across:
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+ - **Multimodal AI Research**: Leading comprehensive evaluation initiatives for enterprise multimodal AI systems, specializing in vision-language understanding, cross-modal bias detection, and adversarial testing
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+ - **Advanced LLM Methodologies**: Pioneering fine-tuning strategies including PEFT, LoRA, and 2-stage training, achieving 12% performance improvements across multiple domains
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+ - **Multi-Agent System Architecture**: Developing sophisticated multi-agent workflows that combine strategic reasoning, visual generation, and quality assessment
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+ - **AI Evaluation & Benchmarking**: Engineering comprehensive evaluation frameworks for state-of-the-art models like Gemini 3.0, with custom datasets across mathematics, finance, chemistry, and biology
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+ - **Production AI Research**: Bridging the gap between theoretical advancements and scalable production systems
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+
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+ ## What You'll Discover Here
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+ In this portfolio, you can explore my multifaceted journey through:
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+ - **Research Contributions**: My work in multimodal AI evaluation benchmarking, advanced prompt engineering methodologies, and robust AI testing frameworks that contribute to the broader ML research community
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+ - **Professional Experience**: From my current role as a Data Scientist & Applied AI Engineer at Turing, where I develop auto-hinter systems and comprehensive model evaluation benchmarks, to my foundational analytics work
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+ - **Award-Winning Projects**: Breakthrough applications like AdHubby (Tenstorrent Multi-Agent Hackathon Winner built in 8 hours), ResumeMaster AI with 5,000+ user interactions, and InfraSight AI for satellite imagery analysis
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+ - **Academic Excellence**: My educational evolution from Electrical Engineering to Applied Data Science, with specialized coursework in Computer Vision, Multimodal Deep Learning, and Advanced Machine Learning
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+ - **Technical Publications**: Thought leadership in ML engineering best practices, open-source contributions with 10,000+ community interactions, and insights into enterprise AI implementation
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+ - **Research Implementation**: How I systematically transform cutting-edge NLP and multimodal research into practical, production-ready applications
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+ ## My Vision & Passion
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+ I'm driven by an insatiable curiosity to explore the frontiers of AI research while maintaining a steadfast commitment to creating tangible impact. Whether I'm fine-tuning Vision Transformers on 40GB satellite datasets, developing auto-rater systems for PhD-level question evaluation, or engineering multi-agent systems that democratize professional marketing, my work embodies the perfect synthesis of research excellence and practical innovation.
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+ My passion lies in not just understanding the latest research breakthroughs in multimodal AI, transformer architectures, and distributed training, but in pioneering new methodologies that advance the field while solving real-world challenges. I believe the future of AI lies in the seamless integration of research-driven insights with production-grade engineering excellence.
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+ ## Research Impact & Community
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+ Through my research and development work, I've contributed to advancing the AI research space through comprehensive evaluation methodologies, open-source applications, and systematic approaches to translating theoretical advances into practical solutions. My work spans from developing robust testing frameworks for AI workflows to creating evaluation benchmarks that help the community better understand and improve state-of-the-art models.
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+ ---
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+ *Ready to explore the intersection of AI research and practical innovation? Connect with me on [LinkedIn](your-linkedin-url), dive into my research code on [GitHub](your-github-url), or read my latest research insights on [Medium](your-medium-url).*
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+ """)
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  def display_education():
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  st.markdown('## Education')