Mohan M. Trivedi
Distinguished Professor
Studies machine perception for intelligent vehicles and human-centered autonomous driving, including driver behavior analysis.
Mohan M. Trivedi's lab at UCSD works on embodied & active vision, autonomous vehicles & drones and robot perception & SLAM. 25 papers since 2023, 1 at top venues, mostly ECCV. 65 alumni. Applications close .
At a glance
- papers, 2023–2026
- 7/ year
- at T1 venues
- 4%
- PhD students
- —
- MS students
- —
- alumni listed
- 65
Papers by yearfrom the lab homepage, 2023–2026
- 5 papers2026 · T1 0 · collecting
- 5 papers2025 · T1 0
- 8 papers2024 · T1 1
- 7 papers2023 · T1 0
T1 venuesOtherVenues: ECCV
Research focuspaper titles that use each topic's words
- Embodied & active vision8 papers
- Autonomous vehicles & drones6 papers
- Robot perception & SLAM1 paper
- machine perception0 papers
- intelligent vehicles0 papers
Paper list
From the lab homepage.
20265 papers
- International Technical Conference on the Enhanced Safety of VehiclesLooking and Listening Inside and Outside: Multimodal Artificial Intelligence Systems for Driver Safety Assessment and Intelligent Vehicle Decision-making
- —Robust Detection, Assocation, and Localization of Vehicle Lights: A Context-Based Cascaded CNN Approach and Evaluations
- International Technical Conference on the Enhanced Safety of VehiclesVision and Language: Novel Representations and Artificial Intelligence Systems for Driving Scene Safety Assessment and Autonomous Vehicle Planning
- IEEE International Conference on Intelligent Transportation SystemsVision-Language Work Zone Intelligence for Safety-Critical Speed Regulation of Mixed-Autonomy Vehicles in Dynamic Environments
- IEEE International Conference on Intelligent Transportation SystemsWhen Stopping Fails: Rethinking Minimal Risk Conditions through Human-Interactive Autonomous Driving for Safe Transportation Systems
20255 papers
- IEEE Open Journal of Intelligent Transportation SystemsA New Perspective On AI Safety Through Control Theory Methodologies
- WACV WorkshopLanguage-Driven Active Learning for Diverse Open-Set 3D Object Detection
- —Lights as Points: Learning to Look at Vehicle Substructures with Anchor-Free Object Detection
- IEEE ITSCPerception Without Vision for Trajectory Prediction: Ego Vehicle Dynamics as Scene Representation for Efficient Active Learning in Autonomous Driving
- —PointCompress3D: A Point Cloud Compression Framework for Roadside LiDARs in Intelligent Transportation Systems
20248 papers
- National Academies of Sciences, Engineering, and Medicine: Transportation Review Board, Automated Road Transportation SymposiumBeyond Driver Assistance: Neural Networks Which Learn and Explain Novel Situations and Driver Behavior for Safe Driving in the Open World
- CVPR WorkshopDriver Activity Classification Using Generalizable Representations from Vision-Language Models
- National Academies of Sciences, Engineering, and Medicine: Transportation Review Board, Automated Road Transportation SymposiumMeasuring Driver Readiness and Control Transitions: Design of Novel Experiments and Vision Algorithms using Real-World Autonomous Driving Studies
- —Patterns of Vehicle Lights: Addressing Complexities in Curation and Annotation of Camera-Based Vehicle Light Datasets and Metrics
- IVPedestrian Safety by Intent Prediction: A Lightweight LSTM-Attention Architecture and Experimental Evaluations with Real-World Datasets
- —preprint pdf (opens in a new tab)
- IVSolving the Missing Frames Problem with Synthetic Data Augmentation: Generating Thermal Images with RGB Cameras
- ECCV (T1)Transfer Learning from Simulated to Real Scenes for Monocular 3D Object Detection
20237 papers
- —(Safe) SMART Hands: Hand Activity Analysis and Distraction Alerts Using a Multi-Camera Framework
- —CHAMP: Crowdsourced, History-Based Advisory of Mapped Pedestrians for Safer Driver Assistance Systems
- —Pedestrian Advisories for Enhanced Safety Using Behavior Maps: Computational Framework and Experimental Analysis With Real-World Data
- —Robust Traffic Light Detection Using Salience-Sensitive Loss: Computational Framework and Evaluations
- —Safe Control Transitions: Machine Vision Based Observable Readiness Index and Data-Driven Takeover Time Prediction
- —Salient Sign Detection In Safe Autonomous Driving: AI Which Reasons Over Full Visual Context
- —Vision-based Analysis of Driver Activity and Driving Performance Under the Influence of Alcohol
Where alumni went65 listed
Apply to UCSDFall 2027
UCSD CSE Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
Similar labsnearest by research summary
- USUIUC
Saurabh Gupta
- Manipulation & robot learning
- USGeorgia Tech
Frank Dellaert
- Robot perception & SLAM
- USCMU
Abhinav Gupta
- Manipulation & robot learning
- CAToronto
Raquel Urtasun
- Autonomous vehicles & drones
- DETUM
Eckehard Steinbach
- Soft, surgical & micro robots
- USUCSD
Henrik I. Christensen
- Robot perception & SLAM
Your notes
Save this lab to keep notes.
Data
Some numbers could not be verified:
- The member list could not be found on the lab site.
- Collected
- Verified
- Papers
- The lab homepage
- Members
- Lab homepage
- Alumni
- Lab homepage
Tiers are venue classifications, not lab rankings.
UCSDcloses