Shuo Feng
Assistant Professor
Works on testing and validation of intelligent systems and autonomous vehicles, dense reinforcement learning, and world models for embodied AI.
Shuo Feng's lab at Tsinghua works on autonomous vehicles & drones, embodied & active vision and reinforcement learning. 18 papers since 2023, 1 at top venues, mostly ICRA. Applications close .
At a glance
- papers, 2023–2026
- 5/ year
- at T1 venues
- 6%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 4 papers2026 · T1 1 · collecting
- 5 papers2025 · T1 0
- 6 papers2024 · T1 0
- 3 papers2023 · T1 0
T1 venuesOtherVenues: ICRA
Research focuspaper titles that use each topic's words
- Autonomous vehicles & drones9 papers
- Reinforcement learning5 papers
- dense2 papers
- intelligent systems1 paper
- Embodied & active vision0 papers
Paper list
From DBLP.
20264 papers
- IEEE Trans. Intell. Transp. Syst.Controllable Risk Scenario Generation From Human Crash Data for Autonomous Vehicle Testing (opens in a new tab)
- IEEE Trans. Intell. Transp. Syst.Intelligent Safety Testing of Autonomous Vehicles With Implicit Traffic Distributions by Dense Reinforcement Learning (opens in a new tab)
- IEEE Trans. Intell. Transp. Syst.Pride and Prejudice: Toward an Information-Theoretic Framework for Mutually Communicative Driver Behavior Modeling (opens in a new tab)
- ICRA (T1)Semantic-Level Conflict Traffic Scenario Generation via Spatiotemporal Polygon Anchors (opens in a new tab)
20255 papers
- IEEE Trans. Intell. Transp. Syst.Adaptive Testing Environment Generation for Connected and Automated Vehicles With Dense Reinforcement Learning (opens in a new tab)
- IEEE Trans. Intell. Transp. Syst.Distributionally Consistent Simulation of Naturalistic Driving Environment for Autonomous Vehicle Testing (opens in a new tab)
- IEEE Trans. Intell. Transp. Syst.Few-Shot Testing of Autonomous Vehicles With Scenario Similarity Learning (opens in a new tab)
- ITSCIntersectioNDE: Learning Complex Urban Traffic Dynamics Based on Interaction Decoupling Strategy (opens in a new tab)
- IEEE Trans. Intell. Transp. Syst.Responsibility-Based Socially Compatible Driving Behavior Modeling Verified by Hierarchical Multi-Agent Inverse Reinforcement Learning (opens in a new tab)
20246 papers
- CASEAccurately Predicting Probabilities of Safety-Critical Rare Events for Intelligent Systems (opens in a new tab)
- IEEE Trans. Intell. Transp. Syst.Adaptive Safety Evaluation for Connected and Automated Vehicles With Sparse Control Variates (opens in a new tab)
- IEEE Trans. Intell. Transp. Syst.Evaluation of Automated Driving System Safety Metrics With Logged Vehicle Trajectory Data (opens in a new tab)
- IVFew-Shot Scenario Testing for Autonomous Vehicles Based on Neighborhood Coverage and Similarity (opens in a new tab)
- IEEE Intell. Transp. Syst. Mag.How to Guarantee Driving Safety for Autonomous Vehicles in a Real-World Environment: A Perspective on Self-Evolution Mechanisms (opens in a new tab)
- WSCSimulation and AI for Critical Infrastructure (opens in a new tab)
20233 papers
- IEEE Trans. Intell. Transp. Syst.An Adaptive Multi-Fidelity Sampling Framework for Safety Analysis of Connected and Automated Vehicles (opens in a new tab)
- IEEE Trans. Intell. Veh.Fault-Tolerant Cooperative Driving at Signal-Free Intersections (opens in a new tab)
- IEEE Trans. Intell. Veh.Mechanical System Inspired Microscopic Traffic Model: Modeling, Analysis, and Validation (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to TsinghuaFall 2027
Computer Science PhD (international applicants)
- Round
- Main
- Opens
- GRE
- See program page
- English
- Per school catalog
- Fee
- RMB 800
Not yet confirmed for this intake.
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Data
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- The alumni list could not be found on the lab site.
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