Yingtian Tang

I am currently a PhD student at EPFL, working on NeuroAI with Prof. Martin Schrimpf.

I had my Master's degree at University of Pennsylvania, majoring in Computer and Information Science (CIS). I was also a research assistant at the GRASP Lab, supervised by Prof. Pratik Chaudhari.

I had my undergraduate at University of Electronic Science and Technology of China, majored in Computer Science. During my undergraduate, I also worked as research assistants in Nanyang Technological University (Rapid-Rich Object Search Lab), and later Tencent (Robotics X).

Contact

Twitter, Bluesky

Google Scholar

yingtian.tang [at] epfl dot ch

Curriculum Vitae

Research Interests

I am interested in the intersection of artificial intelligence and neuroscience, especially how current machine learning methods could approach brain modeling with large-scale data. I am also interested in how these brain models could guide the synthesis of stronger stimuli for neuroscience experiments and potential medical applications. I used to study and was impressed by the research by people like James J. Gibson and Peter Dayan, and believe that NeuroAI will take them further, by modeling the brain's dynamic processes from multiple modalities (audio, visual, tactile) to diverse neural/behavioral outcomes (recognition, decision-making, motor).

Currently, I am working on building models for dynamic perceptual representation, based on state-of-the-art representation learning methods, such as JEPA and MAE, and brain recordings of video watching.

Publications

NEvo: Neural-Guided Evolutionary Video Synthesis for Dynamic Visual Selectivity
Yingtian Tang, Sogand Salehi, Ming Zhou, Amir Zamir, Leyla Isik, Martin Schrimpf
arxiv
Link, Tweets, Page, HuggingFace

Diverse Perceptual Representations Across Visual Pathways Emerge from A Single Objective
Yingtian Tang, Abdulkadir Gokce, Khaled Jedoui Al-Karkari, Daniel Yamins, Martin Schrimpf
bioRxiv
Link, Tweets, Page

From Language to Cognition: How LLMs Outgrow the Human Language Network
Badr AlKhamissi, Greta Tuckute, Yingtian Tang, Taha Binhuraib, Antoine Bosselut*,Martin Schrimpf*
CCN 2025
Link, Tweets

Dreaming Out Loud: A Self-Synthesis Approach For Training Vision-Language Models With Developmentally Plausible Data
Yingtian Tang*, Badr AlKhamissi*, Abdulkadir Gokce*, Johannes Mehrer, Martin Schrimpf
BabyLM Challenge, at CoNLL 2024
Link

Online Motion Style Transfer for Interactive Character Control
Yingtian Tang, Jiangtao Liu, Cheng Zhou, and Tingguang Li
Arxiv Preprint (2021)
Link

Learning-Aided Heuristics Design for Storage System
Yingtian Tang, Han Lu, Xijun Li, Lei Chen, Mingxuan Yuan, and Jia Zeng
The 2021 ACM SIGMOD/PODS International Conference on Management of Data
Link

Accurate probabilistic miss ratio curve approximation for adaptive cache allocation in block storage systems
Rongshang Li, Yingtian Tang, Qiquan Shi, Hui Mao, Lei Chen, Jikun Jin, Peng Lu, and Zhuo Cheng
2022 Design, Automation & Test in Europe Conference & Exhibition (DATE)
Link