Guozheng Huang
Ph.D Student
Are you smarter than you thought? As a former contestant in the Chinese Mathematical Olympiad, I am very interested in the brain's activities during logical decision-making and abstract computation processes. By comparing the performance of humans and marmosets in completing higher-order cognitive tasks, I aim to quantitatively define "intelligence" and understand its evolutionary process. I'm also committed to using mathematical tools such as category theory and Lie algebra to account for the mechanisms of how intelligent agents establish and develop the world model. Feel free to join my research on www.huangguozheng.com and contact with me.
Research fields
Quantitative Analysis and Comparison of Higher-Order Cognitive Behaviors between Humans and Marmosets (Logical Decision-Making, Path Exploration, Music Preference); reinforcement learning and meta-learning models.
Education
September 2020 – Present, PhD candidate, School of Biomedical Engineering, Tsinghua Laboratory of Brain and Intelligence, Tsinghua University
Major Coursework: Brain and Cognitive Science, Neural and Cognitive Computation, Machine Learning
Awards: Future Researchers Scholar of Tsinghua University
September 2016 – June 2020, Bachelor of Science, Department of Mathematics, Tsinghua University
Research
September 2020 – Present, PhD Dissertation Research
Marmoset Dynamic Maze: Developed a dynamic maze with multiple paths to measure the cognitive behaviors of marmosets, utilizing visual and audio stimuli.
Marmoset Behavior Capture System: Captured real-time actions of marmosets and analyzed their behaviors using video and audio data from specifically designed cameras.
Human VR and Online Reinforcement Learning Maze: Establishing Unity Project in PC and VR device(Varjo XR-3) to quantitatively measure human’s ability of adaptive learning in dynamicly-changing logic maze, analysed in methods of reinforcement learning, rule learning and other state-of-art AI algorithms. Set experiment platform in Elastic Compute Service to gather human behavior data online.
September 2019 – August 2020, Undergraduate Research under Professor Carlo Vittorio Cannistraci
Generative Networks in Hyperbolic Space and Inverse Problems: Constructed generative network models in hyperbolic space and addressed inverse problems related to network model establishment. Optimized and visualized the nPSO model, and evaluated the minimum curvilinear embedding method. The primary results were documented in the graduation thesis.
Project
July 11-25 2023, Student, Neural Data Science Summer School, Cold Spring Harbor, New York (online)
August 14-21 2022, Teaching Assistant, CNeuro: Computational and Theoretical Neuroscience Summer School, Tsinghua Laboratory of Brain and Intelligence, Beijing
August 9-22 2021, Student, AI and Brain Computation Summer School, Cold Spring Harbor Asia, Suzhou
August 12-24 2018, Teaching assistant, The 2018 Yau math camp, Yau Mathematical Sciences Center, Beijing
Publication List
Chaoqun Cheng, Zijian Huang, Ruiming Zhang, Guozheng Huang, Han Wang, Likai Tang, Xiaoqin Wang, MarmoPose: A Real-time Multi-Marmoset 3D Pose Tracking System. bioRxiv 2024.02.27.582429; doi: https://doi.org/10.1101/2024.02.27.582429
Contacts
E-mail: hgz20@mails.tsinghua.edu.cn
Website: www.huangguozheng.com
