I work on problems relating to Multimodal Understanding: Object Segmentation, Multiple Object Tracking, Action Localization/Detection. Broadly, I am interested in solving real-life problems (agriculture, autonomous driving, medicine, drug discovery) using discrete / continuous optimization, deep learning, and machine learning. I also like to work on computer graphics and image processing problems. 

Please refer to my Projects page for details on current and previous works of mine.

Academic Profile:

• I defended my PhD (Dec - 2014) on Video Understanding (Unsupervised Segmentation, Metric Learning) at STARS TEAM, INRIA, France (Thesis). [Supervised by Guillaume Charpiat and Monique Thonnat]

  • I have also had the opportunity to collaborate with Mike Jones, Dhruv Batra, and Tim Marks.

• I hold MS in ECE from University of Florida and BS in ECE from Manipal University.

Community Services and Acknowledgments:

• 2023: 1000+ citations! in Google Scholar.

• Awarded outstanding reviewer! for CVPR.

• Program Committee/Reviewer: REID-MTMC'17, Prediction in Wild 18, AIC, WACV'19 '20,

IPAS'18, CCIP'15, IJCNN'19-24. TIP, MVA, CVPR'20 '21 '22 '23' 24, ECCV' 22, '24 ICCV '19 '21 '23

Talks/Tutorials:

• Invited lecture at Georgia Tech on Visual embedding and advancements.

• Invited keynote talk on Multi-Camera Object Tracking & Deep Metric Learning at IEEE IPAS.

• I authored a chapter on Visual Embeddings in Deep Learning for Vision Systems.

• Invited tutorial at IEEE Silicon Valley Chapter, on Re-identification in Camera Networks and Deep Learning.

News:

• Patent Granted! (Pending patents are in my Scholar Page)

  • @Argo/Latitude AI - Auto-magically produce Amodal (true extent) cuboids from Modal Labels.

  • @NVIDIA - Vehicle re-identification using deep learning with low latency.

  • @NVIDIA - Smart Garage using AI (I led the perception architecture).

  • @NVIDIA - Associating stuffs to owners in multi-person scene using deep learning (real time!).

  • @NVIDIA - Simulation Engine for Smart Garage Environments.

• Argoverse-2 accepted! in Neurips 2021.

• CVPR 2019 Paper accepted for Oral! session (top 5%).

• IJCNN 2019 Oral! Paper acceptance.

• PAMTRI (How to effectively mix synthetic and real data for training deep nets) accepted in ICCV 2019.