People who I have shared grants with

    Adrian Barbu (FSU), Elias Bareinboim (Purdue), Terry Boult (UCCS), Joyce Chai (UMichigan), Jason Cong (UCLA), Stuart Geman (Brown), Tao Gao (UCLA), Pablo Garcia (SRI), Tim Groeling (UCLA), Abhinav Gupta (CMU), Martial Hebert (CMU), Derek Hoiem (UIUC), Nancy Kanwisher (MIT), Daphane Koller (Stanford), Feifei Li (Stanford), Jitendra Malik (UC Berkeley), Mike Miller (JHU), Judea Pearl (UCLA), Pietro Perona (Caltech), Deva Ramanan (UC Irvine), Brian Scholl (Yale), Kevin Skadron (UV), Francis Steen (UCLA), Josh Tenenbaum (MIT), Sinisa Todorovic (Oregon State), Antonio Torralba (MIT), Ying Wu (Norhtwestern), Yingnian Wu (UCLA), Alan Yuille (UCLA), Cheng Zhai (UIUC).

Ph.D. Students supervised at UCLA
  • Zhuowen Tu, [CS] Ph.D. 2002, Image Parsing by Data-Driven Markov Chain Monte Carlo.
  • Cheng-En Guo, [CS] Ph.D. 2004, A Mathematical Theory for Texton and Primal Sketch.
  • Adrian Barbu, [CS] Ph.D. 2005, Cluster Sampling and Its Applications in Segmentation, Stereo and Motion
  • Yizhou Wang, [CS] Ph.D. 2005, Modeling Complex Motion: Photometric, Geometric, Topological, and Dynamic Aspects
  • Feng Han, [CS] Ph.D. 2005, Computing 3D Scene From A Single Image by Bottom-up/Top-Down Bayesian Inference
  • Romeo Maciuca, [Stat] Ph.D 2006, MCMC Analysis: First Hitting Times, Visiting Scheme, and Auxiliary Variables
  • Zijian Xu, [Stat] Ph.D 2007, A Hierarchical Compositional Model for Representation and Sketching of High-resolution Human Images
  • Kent Shi, [Stat] Ph.D 2009, Mapping Natural Image Patches by Explicit and Implicit Manifolds
  • Jacob Porway, [Stat] Ph.D 2010 A Hierarchical and Contextual Model for Learning and Recognizing Highly Variant Visual Categories
  • Zhangzhang Si [Stat] Ph.D 2011 Learning And-Or Templates for Object Recognition by Information Projection
  • Mingtian Zhao [Stat] Ph.D 2011 A Statistical and Computational theory for the Art of Painting
  • Tianfu Wu [Stat] Ph.D 2011 Integration and Goal-guided Scheduling of Bottom-up and Top-Down Computing Processes in Hierarchical Models
  • Benjamin Yao [Stat] Ph.D 2011 Learning Spatial-Temporal Models for Understanding Actions and Events in Video
  • Wenze Hu [Stat] Ph.D 2012 Integrating 3D and 2D Representations for View-invariant Object Recognition
  • Brandon Rothrock [CS] Ph.D 2013 Stochastic Image Grammars for Human Pose Estimation
  • Maria Pavlovskaia [Stat] Ph.D 2014 Mapping Highly Non-convex Energy Landscapes in Clustering, Grammar and Curriculum Learning
  • Jungseock Joo [CS] Ph.D 2015 Visual Persuasion in Mass Media: A Computational Framework for Understanding Visual Communication
  • Yibiao Zhao [Stat] Ph.D 2015 A Quest for Visual Commonsense: Scene Understanding by Functional and Physics Reasoning
  • Seyoung Park [CS] Ph.D 2016 Attribute Grammar for Joint Parsing of Human Attribute, Part and Pose
  • Amy Morrow [Stat] Ph.D 2016 Learning and Inferring Perceptual Causality from Videos
  • Dan Xie [Stat] Ph.D 2016 Inferring the Intentions and Attentions of Agents from Videos.
  • Weixin Li [CS] Ph.D 2017 Joint Image-Text Topic Detection and Tracking for Analyzing Social and Political News Events
  • Bruce Nie [Stat] Ph.D 2017 Spatial-Temporal Hierarchical Model for Joint Learning and Inference of Human Action and Pose
  • Yang Lu [Stat] Ph.D 2017 Coupling and Learning Hierarchical Generative and Descriptive Models for Image Synthesis and Analysis
  • Chengcheng Yu [Stat] Ph.D 2017 Single View 3D Scene Reconstruction Using Visual Commonsense
  • Hang Qi [CS] Ph.D 2018 Joint Spatial, Temporal, and Causal Inference and Restricted Turng Test via Storyline Queries
  • Yixin Zhu [Stat] Ph.D 2018 Visual Commonsense Reasoning: Functionality, Physics, Causality, and Utility
  • Yuanlu Xu [CS] Ph.D. 2019 3D Scene and Event Understanding by Joint Spatial and Temporal Inference and Reasoning
  • Siyuan Qi [CS] Ph.D. 2019 Task-oriented Visual Understanding of Scenes and Events
  • Nishant Shukla [CS] Ph.D. 2019 Utility Learning, Non-Markovian Planning, and Task-Oriented Programming Language
  • Tianmin Shu [Stat] Ph.D. 2019 Social Scene Understanding:  Group Activity Parsing, Human-Robot Interactions, and Perception of Animacy
  • Yang Liu [Stat] Ph.D. 2019 Learning Fluents for Task Representation
  • Tao Yuan [Stat] Ph.D. 2019 A Cognition Platform for Joint Inference of 3D Geometry, Object States, and Human Belief
  • Mitchell Hill [Stat] Ph.D. 2020 Learning and Mapping Energy Functions of High-Dimensional Image Data
  • Hangxin Liu [CS] Ph.D.2021 Robot Imitation by Action Understanding, Mirroring, and Interactions
  • Siyuan Huang [Stat] Ph.D. 2021 Human-like Hollistic 3D Scene Understanding
  • Xu Xie [Stat] Ph.D. 2021  Robot Learning from Interactions with Physics-realistic Environment: Constructing Big Task Platform for Training AI Agents
  • Zilong Zheng [CS] Ph.D. 2021 Multimodal Conversation Modeling via Neural Perception, Structure Learning, and Communication
  • Feng Shi [CS] Ph.D. 2021 Adaptive AI algorithms & Unified Hardware Acceleration
  • Lifeng Fan [Stat] Ph.D. 2021 A Hierarchical Computational Framework for Social Interaction Understanding
  • Tengyu Liu [CS] Ph.D. 2021 Hierarchical Modeling of Human-Object Interactions: from Concurrent Action Parsing to Physics-Based Grasping
  • Ruiqi Gao [Stat] Ph.D. 2021 Effective Learning of Descriptive and Generator Models and Learning Representations for Grid Cells and V1 Cells
  • Erik Nijkamp [Stat] Ph.D. 2021 Learning Descriptive and Generative Models with Short-Run MCMC
  • Mark Edmonds [CS] Ph.D. 2021 Learning How and Why: Causal Learning and Explanation from Physical, Interactive, and Communicative Environments
  • Arjun Akula [Stat] Ph.D. 2021 Gaining Justified Human Trust by Improving Explainability in Vision and Language Reasoning Models
  • Liang Qiu [EE] Ph.D. 2022 Conversational Modeling with Human Values, Social Relations, Mental States, and Structure Learning
  • Luyao Yuan [CS] Ph.D. 2022 Communicative Learning: A Unified Learning Formalism
  • Yixin Chen [Stat] Ph.D. 2022 Holistic Scene Understanding and Goal-directed Multi-agent Event Parsing
  • Qing Li [Stat] Ph.D. 2022 Closing the Recognition and Reasoning Loop from A Statistical Learning Perspective
  • Xiaofeng Gao [Stat] Ph.D. 2022 Bidirectional Mental State Alignment for Human-Machine Collaboration
  • Chi Zhang [CS] A Unified Framework for Concept Learning from Few Examples: IQ-Test and Number Sense
  • Jonathan Mitchell [CS] Stochastic Security: Adversarial Defense using Energy-Based Models
  • Shu Wang [Stat] Fluent Calculus and Task Space in Real World Scenes
  • Sirui Xie [CS] The Interactions and Convergence of U and V
  • Pan Lu [CS] Scenario-Based Problem Solving with Joint Image-Text parsing and Commonsense Reasoning
  • Ziyuan Jiao [ME] Robot Manipulation, Causal Action Planning and Motion Planning
  • Baoxiong Jia [CS] Joint Scene and Event Parsing and Prodiction
  • Zeyu Zhang [CS] Tool Manipulation
  • Yizhou Zhao [Stat] Learning and Communication in Multi-agent System
  • Steven Gong [CS] Scenario-Based Problem Solving
  • Muzhi Han [ME] Robot Action Planning based on Scene Understanding and Cognitive Reasoning
  • Yining Hong [CS] Neural Symbolic Reasoning, Automated Math Problem Solving and Commonsense Reasoning
  • Xiaojian Ma [CS] Robotics and Multi-agent Systems
  • Dequan Kong [Stat] Statistical Modeling and Learning
  • Xu Chao [Stat] Scene Understanding
  • Qian Long [CS] Multi-Agent Systems
Postdocs supervised at UCLA
  • Xiuwen Liu, Postdoc 1999-2000, Texture modeling and Julesz ensemble
  • Hong Chen, Postdoc 2003-2006, Human face, hair, and cloth modeling and sketching
  • Haifeng Gong, Postdoc 2007-2009, Intrackability: An information Theoretical Criterion for pursuing Hybrid Video Representations
  • Liang Lin, Postdoc 2007-2009, Layered Graph Matching
  • Mingtao Pei Research Associate 2009-2011, Event understanding and Intent Prediction in Video
  • Tianfu Wu Postdoc 2011-2014, Decision policy and learning and-or graph for object detection and tracking.
  • Bo Zheng Research Associate 2012-2013, 3D scene parsing by reasoning physical stability and risk
  • Kewei Tu Postdoc 2012-2014, Joint video and text parsing, query answering, and grammar learning
  • Xiaobai Liu Postdoc 2013-2015, Attributed grammar for scene understanding, camera calibration and 3D reconstruction
  • Caiming Xiong Postdoc 2014-2015, Robot Learning from demonstrations.
  • Wei Liang Research Associate, 2013-2015, Container recognition and causality inferrence
  • Quanshi Zhang Postdoc 2014-2018, Webscale lifelong Communicative Learning.
  • Ping Wei Postdoc 2015-2017, Inferring the Mind of Agents in Video: Belief, Intent, and Attention
  • Jianwen Xie Postdoc 2016-2017, Generative and Decriptive Models (Deep Networks) for Learning
  • Changsong Liu Postdoc 2016-2018, Communicative Learning and Situated Dialogues
  • Yixin Zhu Postdoc 2018-2020, Cognitive Robots
  • Keze Wang Postdoc 2018-2020, Explainable AI and Learning with small labelled examples
Visiting Ph.D students supervised at UCLA
  • Zhi Han Visiting Ph.D Student 2009-2011, Video Primal Sketch: A Middle Level Generic Representation of Video
  • Shuo Wang Visiting Ph.D Student 2011-2013, Scene Modeling and Recognition with Tangram Model
  • Ping Wei Visiting Ph.D Student 2011-2012, Modeling 4DHOI and Concurrent Action and Affordance
  • Jifeng Dai Visiting Ph.D Student 2012-2013, Unsupervised learning for co-segmentation and image parsing
  • Li Bo Visiting Ph.D Student 2014-2016, Modeling Occlusion for vehicle detection, parsing, and fluent reasoning.
  • Wenguan Wang Visiting Ph.D Student 2016-2018, Joint parsing of human poses, attributes and actions by QA learning
  • Zhenliang Zhang Visiting Ph.D Student 2017-2019, Mixed reality for robot learning.
  • Zhixiong Nan Visiting Ph.D Student 2017-2019, Visual attention and intention inference
Many students were co-supervised at Microsoft Research Asia and Lotus Hill Institute during 1998-2010.
© S.-C. Zhu