Highly accomplished AI professional with a PhD in Artificial Intelligence from Zhejiang University, specializing in computational neuroscience and agentic intelligence. Leverages deep expertise in credit assignment, associative memory models, and representation learning to develop innovative algorithmic solutions. Currently driving advanced AI system capabilities as a Senior Algorithmic Engineer at ByteDance, with a strong record of impactful publications and patented inventions.
Hangzhou, Zhejiang, China
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Summary
Leads the development and optimization of advanced algorithms, focusing on long-term reward and credit assignment for agentic intelligence applications.
Highlights
Developing innovative algorithmic solutions for long-term reward and credit assignment problems, significantly enhancing AI system learning capabilities and performance.
Applying advanced computational neuroscience principles to design and implement robust agentic intelligence models, improving system autonomy and decision-making.
Collaborating with cross-functional teams to integrate cutting-edge AI research into product development cycles, contributing to next-generation features.
Driving the evolution of AI systems through continuous research and deployment of state-of-the-art machine learning techniques, maintaining competitive advantage.
Hangzhou, Zhejiang, China
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Summary
Conducted advanced research in representation learning and associative memory, contributing to foundational AI models and scientific publications.
Highlights
Investigated novel representation learning techniques for complex data structures, improving model efficiency and interpretability in AI systems.
Developed and evaluated associative memory models, enhancing AI systems' ability to recall and synthesize information with increased accuracy.
Published significant research findings in top-tier conferences, including NeurIPS 2023, advancing the field of computational neuroscience and AI.
Contributed to the development of a 'Model of Basic World Understanding,' integrating multi-modal world models and credit assignment in binary networks.
Hangzhou, Zhejiang, China
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Summary
Conducted doctoral research in Artificial Intelligence, specializing in spiking generative models for spatiotemporal memory construction and computational neuroscience.
Highlights
Completed a PhD dissertation on 'A Spiking Generative Model of Spatiotemporal Memory Construction and Computation,' establishing a novel framework for world understanding models.
Pioneered research in multi-modal world models, associative memory, and credit assignment within binary neural networks, advancing theoretical AI foundations.
Authored and co-authored multiple peer-reviewed publications in prestigious AI/ML conferences and journals (NeurIPS, Cell Press Patterns, Neural Networks, AAAI).
Developed and validated brain-inspired algorithms for representation learning and lifelong learning, contributing to the field's theoretical and practical advancements.
Hangzhou, Zhejiang, China
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Summary
Explored credit assignment mechanisms and neuromorphic algorithms, contributing to brain-inspired AI architectures and related publications.
Highlights
Researched and implemented sophisticated credit assignment algorithms, optimizing learning processes in complex neural networks for improved performance.
Designed and tested neuromorphic algorithms for energy-efficient and biologically plausible AI systems, contributing to sustainable computing.
Contributed to scientific publications focusing on the intersection of neuroscience and artificial intelligence, including work on noise exploitation in SNNs.
Collaborated on projects that advanced understanding of gradient estimators and their application in spiking neural networks.
Awarded By
Zhejiang University
Received a prestigious award of honor recognizing outstanding academic and research achievements as a graduate.
Awarded By
Zhejiang University
Designated as a Graduate of Merit, also known as a 'Triple A graduate,' for exceptional performance across academic, research, and extracurricular domains.
Awarded By
TENCENT
Recognized as an inaugural talent in Tencent's 'Project Up' initiative for promising researchers and engineers.
Awarded By
CHINA MOBILE
Selected for China Mobile's 'Project Golden Seed' talent initiative, indicating high potential in technological innovation.
Awarded By
CCNT, Zhejiang University
Acknowledged as an outstanding graduate student by the Center for Computational Neuroscience and Technology (CCNT).
Published by
Zhejiang University
Summary
Doctoral dissertation exploring a novel spiking generative model for spatiotemporal memory and a basic world understanding model, incorporating multi-modal world models, associative memory, and credit assignment in binary networks.
Published by
NeurIPS (Thirty-seventh Conference on Neural Information Processing Systems)
Summary
Published work on memory-conditioning computation and credit assignment within spiking latent variable models, presented at a top-tier AI conference.
Published by
AAAI (Thirty-Eighth AAAI Conference on Artificial Intelligence)
Summary
Presented a brain-inspired spatiotemporal aware representation method for successive Point of Interest (POI) recommendation, focusing on representation learning and spatiotemporal modeling.
Machine Learning, Deep Learning, Agentic Intelligence, Computational Neuroscience, Neuromorphic Computing, Reinforcement Learning.
Credit Assignment, Representation Learning, Associative Memory Models, Spiking Neural Networks (SNNs), Gradient Estimators, Neuromorphic Algorithms, Algorithm Optimization.
Scientific Writing, Peer Review, Conference Presentations, Journal Publications, Dissertation Writing, Literature Review.
Spatiotemporal Modeling, Multi-modal Data, World Models, Binary Networks, Data Interpretation, Model Evaluation.
Intellectual Property, Patent Application, Innovation, Technical Documentation.