Education
PhD in Electrical & Computer Engineering. UC San Diego, exp June 2024.
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.
Research
I use computer vision & artificial intelligence to create systems that help keep people safe and create or enhance system capabilities. The research topics I am interested in are Computer Vision, Artificial Intelligence, and Human-Robot / Human-Computer Interaction, most often applied to the domain of Safe Autonomous Driving. Broadly speaking, my research focuses on improving deep learning models by defining new learning architectures, metrics, and feature representations.
I apply my research in two lab groups at UC San Diego: Professor Mohan Trivedi's Laboratory for Intelligent & Safe Vehicles (LISA) and Professor Shlomo Dubnov's Center for Research in Entertainment & Learning (CREL). My PhD advisor is Professor Mohan Trivedi.
With LISA, I use my research to understand driver state through analysis of visible and multimodal features (e.g. gaze and hand activity), learn salience of (and relationships between) road objects and drivers, and predict vehicle trajectories in real-world driving scenarios. I explore methods of active learning to deal with the challenges of the real world being an open set, and suffering from the long-tail problem and curse of rarity. My methods seek to quantify uncertainty and novelty in learning systems to improve data utility.
With CREL, I use my research to facilitate human-human and human-machine musical interactions, using AI to quantify and learn not only performer behaviors and symbolic & acoustic musical patterns, but also latent representations of "imagination", "creativity", and expression.
My research is supported by the Qualcomm Innovation Fellowship, IRCAM's Project REACH, as well as the generous support of lab sponsors Toyota CSRC, AWS, and the UCOP ILTI grant.
Publications
2024
Ross Greer, Mohan Trivedi. “Towards Explainable, Safe Autonomous Driving with Language Embeddings for Novelty Identification and Active Learning: Framework and Experimental Analysis with Real-World Data Sets”. Under Review, IEEE Transactions on Automation Science and Engineering.
Ahmed Ghita, Bjørk Antoniussen, Walter Zimmer, Ross Greer, Christian Creß, Andreas Møgelmose, Mohan M Trivedi, Alois C Knoll. "ActiveAnno3D--An Active Learning Framework for Multi-Modal 3D Object Detection," IEEE Intelligent Vehicles Symposium 2024.
Ross Greer, Akshay Gopalkrishnan, Maitrayee Keskar, Mohan Trivedi. "Patterns of Vehicle Lights: Addressing Complexities in Curation and Annotation of Camera-Based Vehicle Light Datasets and Metrics", Pattern Recognition Letters.
Maitrayee Keskar, Ross Greer, Akshay Gopalkrishnan, Nachiket Deo, and Mohan Trivedi. “Learning to Look at Internal Structure: Anchor-Free Detection of Vehicle Attributes”. Under Review.
Mathias Viborg Andersen, Ross Greer, Andreas Møgelmose, and Mohan Trivedi. “Solving the Missing Frames Problem with Synthetic Data Augmentation: Generating Thermal Images with RGB Cameras”. IEEE Intelligent Vehicles Symposium 2024.
Afnan Alofi, Ross Greer, Akshay Gopalkrishnan, Mohan M. Trivedi. "Pedestrian Safety by Intent Prediction: A Lightweight LSTM-Attention Architecture and Experimental Evaluations with Real-World Datasets". IEEE Intelligent Vehicles Symposium (IV), 2024.
Ross Greer, Bjørk Antoniussen, Mathias V. Andersen, Andreas Møgelmose, and Mohan Trivedi. “The Why, When, and How to Use Active Learning in Large-Data-Driven 3D Object Detection for Safe Autonomous Driving: An Empirical Exploration”. Under Review, IEEE Transactions on Automation Science and Engineering.
Ross Greer, Mohan Trivedi. "Ensemble Learning for Fusion of Multiview Vision with Occlusion and Missing Information: Framework and Evaluations with Real-World Data and Applications in Driver Hand Activity Recognition." Under Review, Pattern Recognition.
Akshay Gopalkrishnan, Ross Greer, Maitrayee Keskar, Mohan Trivedi. "Robust Detection, Assocation, and Localization of Vehicle Lights: A Context-Based Cascaded CNN Approach and Evaluations", Under Review, Machine Vision and Applications.
2023
Ross Greer, Akshay Gopalkrishnan, Sumega Mandadi, Pujitha Gunaratne, Mohan M. Trivedi, and Thomas D. Marcotte. "Vision-based Analysis of Driver Activity and Driving Performance Under the Influence of Alcohol" FAST-zero 2023.
Ross Greer, Akshay Gopalkrishnan, Jacob Landgren, Lulua Rakla, Anish Gopalan, and Mohan M. Trivedi, "Robust Traffic Light Detection Using Salience-Sensitive Loss: Computational Framework and Evaluations," IEEE Intelligent Vehicles Symposium (IV), 2023.
Ross Greer, Lulua Rakla, Samveed Desai, Akshay Gopalkrishnan, Afnan Alofi, and Mohan M. Trivedi, "Pedestrian Advisories for Enhanced Safety Using Behavior Maps: Computational Framework and Experimental Analysis With Real-World Data," IEEE Intelligent Vehicles Symposium (IV), 2023.
Ross Greer, Nachiket Deo, Akshay Rangesh, Pujitha Gunaratne, and Mohan M. Trivedi, "Safe Control Transitions: Machine Vision Based Observable Readiness Index and Data-Driven Takeover Time Prediction," 27th Enhanced Safety of Vehicles Conference, 2023.
Ross Greer, Nachiket Deo, Akshay Rangesh, Pujitha Gunaratne, and Mohan M. Trivedi, "Salient Sign Detection In Safe Autonomous Driving: AI Which Reasons Over Full Visual Context," 27th Enhanced Safety of Vehicles Conference, 2023.
Ross Greer, Lulua Rakla, Samveed Desai, Afnan Alofi, Akshay Gopalkrishnan, and Mohan M. Trivedi, "CHAMP: Crowdsourced, History-Based Advisory of Mapped Pedestrians for Safer Driver Assistance Systems," 27th Enhanced Safety of Vehicles Conference, SSTDC Semi-Finalist, 2023.
Ross Greer, Lulua Rakla, Anish Gopalan, and Mohan M. Trivedi, "(Safe) SMART Hands: Hand Activity Analysis and Distraction Alerts Using a Multi-Camera Framework," 27th Enhanced Safety of Vehicles Conference, SSTDC Finalist, 2023.
2022
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.
2021
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.
*Work supported by University of California Office of the President Innovative Learning Technology Initiative Grant.
News & Media
I am the recipient of a Postdoctoral Networking Fellowship from the Germany's Academic Exchange Service; my research bio is featured in their program.
Professor Shlomo Dubnov presented our research in AI & Visual Cues for Musical Improvisation at the 10th annual Improtech conference.
My colleague Lulua Rakla and I won the Grand Prize for the AWS Automotive Day competition at IEEE Intelligent Vehicles Symposium, for implementing a drowsy driving detection system using AWS cloud solutions.
My poster for Safe, Multi-View Activity Recognition by Tracking Hands: Robust Visual Learning with Missing Data won the Grand Prize and Department Best Poster Award at the 2023 Jacobs Research Expo. Thank you to collaborators Lulua Rakla, Akshay Gopalkrishnan, Anish Gopalan, and Professor Trivedi. Press Release
Our research project SMART Hands was selected by NHTSA as the North American representative for the final round of the Safety Design Competition for the 2023 International Technical Conference on the Enhanced Safety of Vehicles in Yokohama, Japan.
Two of our research projects (CHAMP, SMART Hands) were selected by NHTSA as regional finalists in the Safety Design Competition for the 2023 International Technical Conference on the Enhanced Safety of Vehicles.
My Polygence blog post High School Computer Science Research: The Complete Guide from “Hello, World!” to the Real World has climbed the ranks of Google Search!
My research partner Kuan-Lin Chen & I are finalists for winners of (!) 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.
My work with Professor Shlomo Dubnov in restoring nonverbal communication to virtual classrooms was featured in NewScientist magazine, Engineering.com, and CSE News,
I was interviewed by Pianist Tiffany Poon for an episode of Together With Classical, where we discussed the intersection of A.I. & Music.
I spoke at the Winter 2021 Educational Innovation Expo @ UCSD.
Teaching
University
Course Designer
UCSD ECE 172A "Intelligent Systems" (Winter 2023, Winter 2024)
Teaching Assistant
UCSD ECE 180 "Autonomous Driving in the Real-World" (Spring 2022)
UCSD ECE 285 "Autonomous Vehicles" (Spring 2021, 2022)
UCSD ECE 172A "Intelligent Systems" (Winter 2021, 2022)
UCSD ECE 253 "Digital Image Processing" (Fall 2020, 2021, 2023)
UCSD CSE 190 "Machine Learning for Music & Audio" (Summer 2020, 2021, 2022, 2023)
Additional Teaching
Polygence Pods "Thinking about Language through ChatGPT" (Spring 2023), Research Mentorship
UCSD COSMOS "Music & Technology" (Summer 2021)
Research Mentor to MS and BS students of LISA and visiting scholars
CV
Current CV available by email (regreer@ucsd.edu).
About
As an Electrical & Computer Engineering PhD student at UC San Diego, I use computer vision & artificial intelligence to create systems for effective, safe, and ethical human use. The research topics I am interested in are Computer Vision, Robotics, Artificial Intelligence, and Human-Robot / Human-Computer Interaction. My research focuses on improving deep learning models by defining new metrics and feature representations. I use my research to predict vehicle trajectories in real-world driving scenarios, estimate driver state, and understand human gaze. I work on projects with Professor Mohan Trivedi's Laboratory for Intelligent & Safe Vehicles (LISA) and Professor Shlomo Dubnov's Center for Research in Entertainment & Learning (CREL). I am advised by Professor Mohan Trivedi.
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.
In the process of developing safer models for intelligent vehicles, my interests in HRI/HCI and vision have inspired my research developments in gaze and attention modeling and tracking in domains outside of automobiles. This includes virtual classrooms, teleconferences, and musicians' environments. My work seeks to better perceive & present nonverbal human communication, in the form of eye gaze and directed gesture; two immediate problems driving my work are gaze prediction and gaze correction using deep learning.
Outside of my research, I advise the Symphonic Student Association, and field direct & write music for the University of California Marching Band.