Teaching
[Spring 2024] TA, "Advanced Topics on Deep Learning" (COMP_SCI 496), Northwestern University CS.
[Spring 2024] TA, "Mathematical Foundations of Machine Learning" (COMP_SCI 496 & STAT 435), Northwestern University CS & Stats & Data Science.
[Winter 2022] TA, "Data Science Pipeline" (COMP_SCI 326), Northwestern University CS.
[Fall 2020] Instructor, "Vibrations, Waves, & Electromagnetism." Notes & recordings upon request, University of Maryland College Park Physics.
[2018-2021] TA for multiple courses (PHYS121, PHYS122, PHYS131, PHYS132, PHYS260, PHYS261, PHYS603...), University of Maryland College Park Physics.
[Spring 2018] TA, "Gravity, S-Matrix & String Theory," NTU Physics.
[Fall 2017] TA, "Quantum Field Theory I," NTU Physics.
Collaboration and Mentoring
(in reverse chronological order)
(in reverse chronological order)
Maojiang Su, University of Science and Technology of China (School of the Gifted Young) BS'24 -> Prospective Ph.D. Applicants for Fall 2024 (CS/Stats/DS/OR)
Computational Limits of Low-Rank Adaptation (LoRA) for Transformer-Based Models (ArXiv)
Thomas Yuan-Lung Lin, High School Outreach Student @ WLSH'23 -> NTU Physics (Class of 2027)
On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis (ICML'24)
Wei-Bo Wang, NTU Physics BS'24 -> Prospective Ph.D. Applicants for Fall 2024 (CS/Phys)
Outlier-Efficient Hopfield Layers for Large Transformer-Based Models (ICML'24)
Morris Huang, NTU Physics MS'24 -> Prospective Ph.D. Applicants for Fall 2024 (CS/Phys)
BiSHop: Bi-Directional Cellular Learning for Tabular Data with Generalized Sparse Hopfield Model (ICML'24)
Hong-Yu Chen, NTU Physics MS'24 -> CS PhD study at NU (Fall'24)
Outlier-Efficient Hopfield Layers for Large Transformer-Based Models (ICML'24)
Bo-Yu Chen, High School Outreach Student @ HSNU'23 -> NTU Physics (Class of 2027) with NTU Fu Bell Scholarship (Highest Distinction across University)
STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction (ICLR'24)
On Sparse Modern Hopfield Model (NeurIPS'23)
Chenwei Xu, MSCS'24 at NU -> Stats & DS PhD study at NU (Fall'24)
BiSHop: Bi-Directional Cellular Learning for Tabular Data with Generalized Sparse Hopfield Model (ICML'24)
On Sparse Modern Hopfield Model (NeurIPS'23)
Beyond PID Controllers: PPO with Neuralized PID Policy for Proton Beam Intensity Control in Mu2e (NeurIPS'23, ML4Phys Workshop) [READS Collaboration, Fermilab]
Feature Programming for Multivariate Time Series Prediction (ICML'23)
Dennis Wu, MSCS'24 at NU -> CS PhD study at NU (Fall'24)
Uniform Memory Retrieval with Larger Capacity for Modern Hopfield Models (ICML'24)
STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction (ICLR'24)
On Sparse Modern Hopfield Model (NeurIPS'23)
Zhenyu Pan, MSECE'24 at U. of Rochester -> CS PhD study at NU (Fall'24)
Zhenji Wang, UMD'21 Math -> MS'23 at Columbia U. -> ML PhD study at U. of Tsukuba
Differential Geometry and Heat Kernel Expansion, 2021 Spring
“To boldly go where no man has gone before.”
By far, Star Trek has one of the most famous opening narrations in the history of the filming industry. Resonating a feeling of the 1960’s futuristic optimism, the iconic phrase was first spoken by William Shatner who starred as Captain James T. Kirk in the original series.
“Space: the final frontier. These are the voyages of the starship Enterprise. Its five-year mission: to explore a strange new world, to seek out new life and new civilizations, to boldly go where no man has gone before.”