About
Highly accomplished AI Research Scientist with a Ph.D. from Stanford University and extensive expertise in generative models, diffusion models, and reinforcement learning. Proven track record of driving cutting-edge research, evidenced by numerous top-tier publications and prestigious awards, including the ICLR 2022 Outstanding Paper Award. Adept at developing innovative machine learning algorithms and contributing to state-of-the-art AI advancements at leading organizations like NVIDIA, Facebook AI Research, and OpenAI.
Work
Santa Clara, CA, US
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Summary
Drives advanced research and development in generative AI, focusing on diffusion models and their applications in image and language synthesis for NVIDIA's cutting-edge platforms.
Highlights
Led research and co-authored 'eDiff-I: Text-to-Image Diffusion Models with Ensemble of Expert Denoisers' (arXiv:2211.01324), contributing to state-of-the-art text-to-image generation and influencing NVIDIA's generative AI roadmap.
Developed and optimized novel diffusion implicit models, enhancing the efficiency and quality of generative processes for real-world applications.
Collaborated cross-functionally to translate complex research breakthroughs into practical solutions, impacting future product development cycles.
Contributed to the strategic direction of AI research, identifying key areas for innovation in large-scale model development and deployment.
Stanford, CA, US
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Summary
Conducted independent, high-impact research in advanced machine learning, focusing on generative models, reinforcement learning, and Bayesian optimization.
Highlights
Pioneered research on 'A General Recipe for Likelihood-free Bayesian Optimization,' which received a long oral presentation (Top 2.2%) at ICML 2022, demonstrating significant advancements in optimization techniques.
Published multiple influential papers in top-tier conferences, including NeurIPS 2022 and AAAI 2023, advancing the theoretical and practical aspects of diffusion models and imitation learning.
Mentored and guided junior researchers and graduate students, contributing to their academic growth and successful project completion.
Stanford, CA, US
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Summary
Conducted rigorous doctoral research in Computer Science, specializing in generative models, reinforcement learning, and AI interpretability under Professor Stefano Ermon.
Highlights
Authored 'Comparing Distributions by Measuring Differences that Affect Decision Making,' which earned the ICLR 2022 Outstanding Paper Award, a top recognition in the field.
Developed Denoising Diffusion Implicit Models (DDIMs), a seminal contribution to diffusion models that significantly improved sampling speed and quality.
Secured the prestigious Qualcomm Innovation Fellowship for developing 'Safe Multi-Agent Imitation Learning for Self-Driving,' showcasing innovative application of AI.
Published over 20 peer-reviewed papers in leading AI/ML conferences (NeurIPS, ICML, ICLR, AAAI, ECCV), establishing expertise in core AI methodologies.
Menlo Park, CA, US
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Summary
Contributed to high-impact AI research projects at Facebook AI Research, focusing on large-scale computer vision applications.
Highlights
Developed and implemented novel algorithms for 'Large-scale Object Counting from Satellite Images,' enhancing the accuracy and efficiency of geospatial analysis.
Collaborated effectively within a world-class research team to push the boundaries of generative models and computer vision.
Presented research findings to senior scientists, contributing to the team's intellectual property and strategic initiatives.
San Francisco, CA, US
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Summary
Engaged in pioneering research on deep learning and AI models, contributing to cutting-edge projects at OpenAI.
Highlights
Contributed to the development of 'Learning Interpretable Skill Abstractions from Language (LISA),' enhancing the interpretability and understanding of complex AI behaviors.
Assisted in designing and executing large-scale experiments for advanced AI models, optimizing performance and scalability.
Collaborated on research initiatives that significantly advanced the state-of-the-art in reinforcement learning and generative modeling.
Beijing, Beijing, China
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Summary
Participated in research and development of core computer vision technologies at Megvii, a leading AI company.
Highlights
Contributed to the development of robust image classification models, improving recognition accuracy for various real-world scenarios.
Implemented and evaluated diverse deep learning architectures, gaining practical experience in model selection and optimization.
Applied theoretical AI concepts to real-world challenges in facial recognition and image analysis, enhancing product capabilities.
Durham, NC, US
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Summary
Conducted foundational research in machine learning and data science, exploring applications of advanced statistical modeling.
Highlights
Explored and applied statistical modeling and machine learning techniques to analyze complex datasets, laying groundwork for future research.
Collaborated on a research project focused on Factored Temporal Sigmoid Belief Networks for sequence learning, contributing to early insights.
Developed a strong understanding of research methodologies, experimental design, and scientific writing.
Awards
ICLR 2022 Outstanding Paper Award
Awarded By
International Conference on Learning Representations (ICLR)
Awarded for the paper 'Comparing Distributions by Measuring Differences that Affect Decision Making,' recognizing its significant impact on the field.
Qualcomm Innovation Fellowship
Awarded By
Qualcomm
One of 8 recipients for the project on 'Safe Multi-Agent Imitation Learning for Self-Driving,' acknowledging innovative research potential.
Qualcomm Scholarship
Awarded By
Qualcomm
Awarded to Top 1% of Tsinghua undergraduates for exceptional research experiences.
Google Excellence Scholarship
Awarded By
Awarded to 58 undergraduate and graduate students in China for academic and research excellence.
Outstanding Winner, Interdisciplinary Contest in Modeling
Awarded By
Interdisciplinary Contest in Modeling
Highest award (Top 0.3%) for the paper 'Organizational Churn: A Roll of the Dice?', recognizing superior analytical and modeling skills.
Outstanding Undergraduate, China Computer Federation
Awarded By
China Computer Federation
Awarded to 2 undergraduate students in Tsinghua University for outstanding academic performance.
Zhong Shimo Scholarship
Awarded By
Tsinghua University CS Department
Highest scholarship (Top 0.75%) in the Computer Science Department at Tsinghua University.
Bronze Prize, National Olympiad in Informatics
Awarded By
National Olympiad in Informatics
Awarded for exceptional performance in the national computer science competition.
Publications
Published by
International Conference on Learning Representations (ICLR)
Summary
Authored the ICLR 2022 Outstanding Paper, introducing a novel method for comparing distributions that significantly impacts decision-making processes in AI.
Skills
Machine Learning
Deep Learning, Generative Models, Diffusion Models, Reinforcement Learning, Bayesian Optimization, Imitation Learning, Computer Vision, Natural Language Processing, Neural Networks, Probabilistic Graphical Models, Model Interpretability, Few-shot Learning, Multi-agent Systems.
Programming & Tools
Python, PyTorch, TensorFlow, NumPy, SciPy, Scikit-learn, Git, LaTeX.
Research & Development
Algorithm Design, Data Analysis, Scientific Computing, Model Optimization, Experimental Design, Peer Review, Technical Writing, Mentorship.