I am interested in the operational challenges behind the deployment and use of AI systems. I use deep learning and data-driven optimization for problems where the typical forms of large-scale data collection and model tuning are prohibitive. My work addresses ML technology (e.g., computer vision systems), healthcare (e.g., personalized medicine), and finance (e.g., portfolio optimization). I am also interested in general data science problems (e.g., sports analytics).
Students interested in (Undergraduate/Masters/PhD) supervision at Telfer are welcome to contact me here with a CV and transcript.
Graduate students interested in internships at NVIDIA are welcome to contact me here with a CV and summary of research interests.
|Jan 15, 2024
|Our paper Translating Labels to Solve Annotation Mismatches Across Object Detection Datasets was accepted at ICLR 2024.
|Oct 20, 2023
|Our review paper Inverse Optimization: Theory and Applications was accepted at Operations Research.
|Oct 16, 2023
|Our paper Got (Optimal) Milk? Pooling Donations in Human Milk Banks with Machine Learning and Optimization won First Place for the Pierskalla Best Paper Award in Healthcare!
|Oct 3, 2023
|I will be speaking about our recent work on optimizing data collection at the ICCV 2023 Tutorial on Learning with Noisy and Unlabeled Data for Large Models beyond Categorization
|Sep 30, 2023
|Our paper Got (Optimal) Milk? Pooling Donations in Human Milk Banks with Machine Learning and Optimization was accepted at M&SOM.
|Sep 19, 2023
|Our paper Learning To Optimize Contextually Constrained Problems for Real-Time Decision Generation was accepted with minor revisions at Management Science.
|Aug 20, 2023
|Our paper Bridging the Sim2RealGap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting was accepted with minor revisions at TMLR.
|Jun 24, 2023
|Our paper Got (Optimal) Milk? Pooling Donations in Human Milk Banks with Machine Learning and Optimization is a Finalist for the MSOM 2023 Practice-Based Research Competition and will be presented in a special seminar at MSOM 2023.