Education ✍️

Sept. 2023 - May. 2025
Master of Science in Computer Science, New York University, Tandon School of Engineering
GPA 3.9/4.0
Core Course: Computational Neuroscience, Algorithmic Machine Learning and Data Science, Neuroinformatics
Sept. 2019 - Jun. 2023
Bachelor of Engineering in Computer Engineering, The Chinese University of Hong Kong, Shenzhen
First Class Honors
Core Course: Graduate Course Advanced Machine Learning, Computer Vision, Neural system, Machine Learning, Signal Processing, Data Structure, Linear Algebra, Operating System, Optimization
Dean’s List (2019-2020, 2020-2021, top 25%) Undergraduate Research Award (2020)
Jan. 2022 - Aug. 2022
Visiting Student, University of California, Berkeley
Core Course: Computational Model of Cognition, Algorithm, Artificial Intelligence
July 1 – July 22 2023
The 11th Computational and Cognitive Neuroscience Summer School by Cold Spring Harbor Asia
Core Course: Dynamical System, Neural Coding, Computational Model, Low-Rank RNN
Aug.2-20 2021
Neuromatch Academy-Deep Learning Summer School 2021 Certificate of Completion
Jun. - Aug. 2022
Reinforcement Learning Course Completion | University of Ulberta

Publication 📑

Yu, Junjie, Chenyi Li, Kexin Lou, Chen Wei, and Quanying Liu. “Embedding decomposition for artifacts removal in EEG signals.” Journal of Neural Engineering 19, no. 2 (2022): 026052

Paper: Embedding Decomposition for Artifacts Removal in EEG Signals

Code: DeepSeparator

Chenyi Li, Sreejan Kumar, Marcelo Mattar (2024). Learning to Reinforcement Learn with Transformer. [Manuscript in preparation]

Chenyi Li, Guande Wu, Gromit Yeuk-Yin Chan, Xiaoan Liu, Sonia Castelo Quispe, Shaoyu Chen, Leslie Welch, Claudio Silva, Jing Qian (2024). 悟り: Towards Proactive AR Assistant with Belief-Desire-Intent User Modeling. [Manuscript in preparation]

Tianxiao He, Anna Maslarova, Mihály Vöröslakos, Chenyi Li, Yurong Liu, György Buzsáki, Erdem Varol (2024). Blind in vivo localization of microelectrode arrays via functional correlation patterns in the mouse hippocampus. [Manuscript in preparation]

Research Experience 📚

Sep. 2023 – present
Research Assistant | Mattar Lab
Advisor: Marcelo Mattar, Assistant Professor of Psychology and Neural Science at New York University
• Implemented Decision-Transformer in a maze navigation game to do meta-reinforcement learning
• Conducted meta-learning experiments for pretrained Decision-Transformer
Jan. 2024 – present
Research Assistant | Visualization Imaging and Data Analysis Center at NYU
Advisor: Claudio Silva, Professor of Computer Science, Engineering and Data Science at New York University
• Developed AI technologies to help users perform complex tasks in the Perceptually-enabled Task Guidance (PTG) project
• Innovated a Belief-Desire-Intent (BDI) framework for user modeling and novel design space of user intent
• Integrated Intent-Tracking modules into Augmented Reality (AR) on HoloLens to provide proactive task guidance
• Executed advanced GPT prompt engineering techniques to refine task-oriented guidance, tailored to the user model
Jan. 2024 – present
Research Assistant | Neuroinformatics Lab at NYU
Advisor: Erdem Varol, Assistant Professor at the Department of Computer Science & Engineering at Tandon School of Engineering, New York University
• Analyzed spike features (statistics, Interspike-Interval, etc.) of electrophysiological data (Neuronexus, Neuropixel)
• Applied transformer-based model LOLCAT on Neuronexus data to classify hippocampal subregions
• Conducted extensive experiments on cross-subject generalizability of the classifier
Feb. 2023 - May. 2023
Research Assistant | Liu Lab
Advisor: Yunzhe Liu, Professor at Chinese Institute for Brain Research
• Implemented RNN Meta-Reinforcement Learning with Replay
• Combined meta-RL with Tolman Eichenbaum Machine Model • Proposed to combine meta-RL with Tolman Eichenbaum Machine Model
Jun. 2022 - Jan. 2023
Research Assistant | Cognitive Developmental and Learning Lab
Advisor: Alison Gopnik, Professor at Department of Psychology, University of California, Berkeley
• Conducted literature research on intrinsic reward reinforcement learning and applied the unsupervised meta-learning
• Developed 2D grid world games using Python to simulate environments of 3 kinds of animals
• Conducted exploratory data analysis on the model-based reinforcement learning agents’ behaviors on 20 games using R
• Led a behavioral coding for a pilot behavioral experiment about “play”, “exploit”, and “explore” with 72 subjects
Jun. 2021 - Dec. 2021
Visiting Student | Neural Control and Computing Lab
Advisor: Quanying Liu, Assistant Professor at School of Engineering, Southern University of Science and Technology
• Trained and tested deep neural network (inception network, CNN, RNN, LSTM) on 50000 single-channel noisy EEG
• Implemented traditional denoise method (EEMD-ICA, HHT, Adaptive Filter) on 10000 EEG data for comparison
• Participated in writing the literature review, proposed methods and experiment results parts of the paper
This work resulted in a publication in Journal of Neural Engineering.
Oct. 2020 - May. 2021
Research Assistant | Human-Cloud Systems Laboratory Advisor: Wei Cai, Assistant Professor at School of Science and Engineering, Chinese University of Hong Kong, Shenzhen
• Learned reinforcement learning via courses by David Silver, and “Reinforcement Learning: An Introduction”
• Conducted literature review on reinforcement learning applications in city traffic light control

Project Experience 🛠️

Dec.1-5 2021
IDEA: Decentralized Academic Peer Review Application
• Built up an on-chain decentralized anonymous peer-review system with reputation hub
• Enabled reproducibility check in the review process
• Developed open access publication based on a token system
Sept. 2022 - Dec. 2022
Final Year Project | Face Attribute Editing by StyleGAN
• Explored the disentanglement features of the hidden space in StyleGAN
• Developed a novel pipeline for multi-face attribute editing using disentanglement
Sept.9-12 2021
CUMCM: Raw Materials Ordering and Transportation Strategies with Mathematical Modeling
• Applied K-means and time series analysis on the supply-demand data of 402 raw material suppliers
• Utilized 0-1 programming to develop a 24-week ordering strategy based on the supply capacity model of 50 suppliers
• Solved the vector-bin packing problem to optimize the transportation strategy; Awarded 3rd Prize in Competition
Dec. 2019 - July. 2023
Leader | uBuddies: CUHKSZ Peer Counseling Group
• Created an innovative program, Final Week Program, to relieve students’ negative emotions when preparing for final exams
• Provided peer counseling about emotion, self-development, friendship and intimate relationship over 10 hours
July 2021-Sept. 2022
Leader | Field Study on Female Family-Work Balance in Eastern China
• Developed a comprehensive online survey for 518 subjects and conducted semi-structured interviews with 15 subjects
• Conducted analysis using R on relationship between the industry and the challenge and support female get in maternity leave

Skills 🪄

Programming Language
Python(NumPy, Pytorch, OpenCV), Matlab, C++, R, MNE-Python (ERP analysis, Source Localization), SQL
Game Creation
Blender, Unity, VR/AR development

Contact 📞

email
chenyili@nyu.edu
phone
+1 9172037986 +86 15858140435