My primary research work aims to make driving intelligent and safer (for both pedestrians and vehicle occupants) through computer vision and artificial intelligence. Our lab emphasizes a LILO (looking inside, looking outside) approach to holistic safety. Accordingly, part of my research involves sensors outside of the cabin perceiving the surround in order to accurately estimate vehicle and pedestrian trajectories, where I have contributed new metrics and loss functions to improve state-of-the-art multimodal trajectory prediction models. The other part of my research involves understanding driver awareness and intent by analyzing in-cabin behavior using a fusion of sensors and cues.
PhD in Electrical & Computer Engineering. UC San Diego, in progress.
MS in Electrical & Computer Engineering. UC San Diego, 2018.
BS in Electrical Engineering & Computer Science. UC Berkeley, 2015.
BS in Engineering Physics. UC Berkeley, 2015.
BA in Music. UC Berkeley, 2015.
Ross Greer and Mohan M. Trivedi, "From Pedestrian Detection to Crosswalk Estimation: An EM Algorithm, Analysis and Evaluations on Diverse Datasets," ICML Workshop on Supervised Learning for Autonomous Driving, 2022.
Maitrayee Keskar, Nachiket Deo, Ross Greer, and Mohan M. Trivedi, "A Center-Based Integrated Vehicle Internal and Landmarks Detector," Presentation at IEEE IV ITSIVUE Workshop, 2022.
Greer and Trivedi. "From Pedestrian Detection to Crosswalk Estimation: An EM Algorithm and Analysis on Diverse Datasets," Accepted at Presented at IEEE IV 2nd Workshop on Prediction of Pedestrian Behaviors for Automated Driving, 2022.
Greer, Isa, Deo, Rangesh, and Trivedi. "On Salience-Sensitive Sign Classification in Autonomous Vehicle Path Planning: Experimental Explorations with a Novel Dataset," WACV, Workshop on Hazard Perception in Intelligent Vehicles, 2022.
Greer, Deo, and Trivedi. Trajectory Prediction in Autonomous Driving with a Lane Heading Auxiliary Loss. IEEE Robotics & Automation Letters, 2021.
Greer and Dubnov. Restoring Eye Contact to the Virtual Classroom with Machine Learning. 13th International Conference on Computer Supported Education, 2021.*
Rangesh, Greer, Deo, Gunaratne, and Trivedi. Autonomous Vehicles that Alert Humans to Take-Over Controls: Modeling with Real-World Data. 24th IEEE International Conference on Intelligent Transportation, 2021.
Rangesh, Deo, Greer, Gunaratne, and Trivedi. Predicting Take-over Time for Autonomous Driving with Real-World Data: Robust Data Augmentation, Models, and Evaluation. In Press, 2021.
News & Media
My partner Kuan-Lin Chen & I are finalists for the 2022 Qualcomm Innovation Fellowship. Our proposal is on Active Learning for Autonomous Driving Datasets.
My poster for Trajectory Prediction with a Novel Lane-Heading Auxiliary Loss won a Best Poster Award at the 2021 Jacobs Research Expo. Thank you Nachiket & Professor Trivedi for your guidance! Press Release
Our collaboration with Amazon's Machine Learning Solutions Lab was featured in an AWS blog post.
I spoke at the Winter 2021 Educational Innovation Expo @ UCSD.
Spring 2021, 2022 - UCSD ECE 285 "Autonomous Vehicles"
Winter 2021, 2022 - UCSD ECE 172A "Intelligent Systems"
Fall 2020, 2021 - UCSD CSE 253 "Digital Image Processing"
Summer 2020, 2021, 2022 - UCSD CSE 190 "Machine Learning for Music & Audio"
Summer 2021 - UCSD COSMOS "Music & Technology"
Teaching & Tutoring Services
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