Zeyu Zheng
Associate Professor
Studies stochastic simulation, generative models and reinforcement learning for decision-making.
Zeyu Zheng's lab at UC Berkeley works on reinforcement learning, generative & foundation models and physics-based simulation & animation. 33 papers since 2023, 17 at top venues, mostly Management Science and Operations Research. Applications close .
At a glance
- papers, 2023–2026
- 9/ year
- at T1 venues
- 52%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 11 papers2025 · T1 8
- 12 papers2024 · T1 4
- 10 papers2023 · T1 5
T1 venuesOtherVenues: Management Science, Operations Research, NeurIPS, AISTATS, ICML
Research focuspaper titles that use each topic's words
- Physics-based simulation & animation9 papers
- Reinforcement learning6 papers
- Generative & foundation models1 paper
- industrial engineering0 papers
- operations0 papers
Paper list
From the lab homepage.
202511 papers
- Operations Research (T1)A Doubly Stochastic Simulator with Applications in Arrivals Modeling and Simulation (opens in a new tab)
- Management Science (T1)A Simple and Optimal Policy Design with Safety against Heavy-tailed Risk for Stochastic Bandits (opens in a new tab)
- KDD (T1)A/B Test and Online Experiment Under Diminishing Marginal Effects: Regret Minimization and Statistical Inference (opens in a new tab)
- INFORMS Journal on ComputingClustering then Estimation of Spatio-Temporal Self-Exciting Processes (opens in a new tab)
- Information Systems Research, AcceptedCollaborative Intelligence in Sequential Experiments: A Human-in-the-Loop Framework for Drug Discovery (opens in a new tab)
- ICML (T1)Efficient Fine-Grained Guidance for Diffusion Model Based Symbolic Music Generation (opens in a new tab)
- Operations Research (T1)Joint Optimization and Statistical Inference for Zero-th Order Simulation Optimization (opens in a new tab)
- INFORMS Journal on Computing, AcceptedMachine Learning-Assisted Stochastic Kriging Metamodel for Offline Simulation Online Application
- Management Science (T1)Non-stationary A/B Tests: Optimal Variance Reduction, Bias Correction, and Valid Inference (opens in a new tab)
- Management Science (T1)Offline Planning and Online Learning under Recovering Rewards (opens in a new tab)
- Operations Research (T1)Stochastic Localization Methods for Convex Discrete Optimization via Simulation (opens in a new tab)
202412 papers
- WSCA Preliminary Study on Accelerating Simulation Optimization with GPU Implementation (opens in a new tab)
- Conference on Health, Inference, and LearningDaily Physical Activity Monitoring–Adaptive Learning from Multi-source Motion Sensor Data (opens in a new tab)
- Management Science (T1)Dynamic Pricing with External Information and Inventory Constraints (opens in a new tab)
- WSCEnhancing Language Model with Both Human and Artificial Intelligence Feedback Data (opens in a new tab)
- Journal of EconometricsInference on the Best Policies with Many Covariates (opens in a new tab)
- WSCLarge Language Model Assisted Experiment Design with Generative Human-Behavior Agents (opens in a new tab)
- Production and Operations ManagementLearning Newsvendor Problems With Intertemporal Dependence and Moderate Non-stationarities (opens in a new tab)
- WSCLLM Enhanced Machine Learning Estimators for Classification (opens in a new tab)
- Management Science (T1)On Greedy-like Policies in Online Matching with Reusable Network Resources and Decaying Rewards (opens in a new tab)
- Operations Research (T1)Performance Evaluation and Stochastic Optimization with Gradually Changing Non-Stationary Data (opens in a new tab)
- AISTATS (T1)Stochastic Multi-Armed Bandits with Strongly Reward-Dependent Delays (opens in a new tab)
- WSCUsing COSIMLA Within Policy Iteration for MDPs with Large State Spaces (opens in a new tab)
202310 papers
- WSCA Preliminary Study of Regularization Framework for Constructing Task-Specific Simulators (opens in a new tab)
- WSCBest Arm Identification with Fairness Constraints on Subpopulations (opens in a new tab)
- WSCCombining Numerical Linear Algebra with Simulation (COSIMLA) with General Regeneration Set to Compute Markov Chain Stationary Expectations (opens in a new tab)
- NeurIPS (T1)Contextual Gaussian Process Bandits with Neural Networks (opens in a new tab)
- Operations Research (T1)Gradient-based Methods for Convex Discrete Optimization via Simulation (opens in a new tab)
- INFORMS Journal on ComputingGradient-based Simulation Optimization Algorithms via Multi-Resolution System Approximations (opens in a new tab)
- Management Science (T1)Immediacy Provision and Matchmaking (opens in a new tab)
- TOMACSLearning to Simulate Sequentially Generated Data via Neural Networks and Wasserstein Training (opens in a new tab)
- NeurIPS (T1)Non-stationary Experimental Design under Linear Trends (opens in a new tab)
- NeurIPS (T1)Stochastic Multi-armed Bandits: Optimal Trade-off among Optimality, Consistency, and Tail Risk (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to UC BerkeleyFall 2027
UC Berkeley EECS Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- not required
- English
- TOEFL/IELTS (non-English-country degrees)
- Fee
- See program page
Confirmed on the program page.
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