CV

PhD in Computer Science

The University of Texas at Dallas, Texas, USA

• PhD candidate in Computer Science for the Intelligent Systems track.
• Research Assistant with Prof.Rishabh Iyer at the CARAML lab.

MS in Computer Science

The University of Texas at Dallas, Texas, USA

• MS in Computer Science for the Intelligent Systems track.

B.Tech in Electrical and Electronics Engineering

Vellore Institute of Technology, Chennai, India

• Graduated as a gold-medalist in the department by scoring a GPA of 9.68/10.0.
• Worked as a Undergrad Researcher at the Smart Grid Lab, advised by Prof. Gnana Swathika O.V.

Research Intern

Dolby Laboratories, San Francisco, CA

• Developed a Multi-Modal Generative Model (GenAI) for improving Video-Language understanding in long-form video sequences. To be submitted to CVPR'26.
• Inspired from Live Sports and Cinema content, not all frames in a video is relevant to understanding tasks, we developed a combinatorial approach to identify a set of video segments relevant to answering the question achieving \(\sim\)4% boost in performance on several Video LLMs.

Research Intern

Fujitsu Research of America (FRA), Santa Clara, CA

• Developed a Multi-modal Foundation Model, TabGLM towards cross-table generalization in tabular data. This work has been accepted to AAAI'25.
• TabGLM minimizes the consistency between graph (learnt from a Graph Transformer network) and text (learnt from a BART based Large Language Model (LLM) encoder) modalities generated from each record in large tables.

Data and Applied Scientist II

Microsoft, India

• Developed an Entity Centric Language model to improve identification of products, brands etc. resulting in 12% revenue gain in Search Advertising.
• Mentored an intern to develop an evaluation framework to benchmark entity centric language models which is used across 3+ teams in Microsoft Advertising.

Applied Research Scientist

Intel, India

• Led the development of Few-Shot Object Detection (FSOD) and Few-Shot Incremental Learning (FSIL) algorithms in Pytorch for detecting rare or unseen road objects in unconstrained driving environments.
• Mentored two interns whose work on Few-Shot Object Detection has been submitted to conferences like ICCV and WACV.

Undergraduate Technical Intern

Intel, India

• Developed Edge Inferencing framework to deploy Computer Vision models on multiple edge hardwares including Intel Neural Compute Sticks.

• Appointed as a Reviewer for ICCV'25, NeurIPS'25, WACV'26, ICLR'26.

• Appointed as a Reviewer for ICLR'25, CVPR'25, WACV'25, TPAMI (journal).
• Appointed as a Research Assistant for Fall 25 and Spring 26.

• Appointed as a Reviewer for ICLR'24.
• Delivered a Keynote at VIT Chennai on Virtual Electrical Networks, Seamless Integration and Fault Clearance in Reconfigurable Microgrids.
• Appointed a Research Assistant at CARAML lab.

• Appointed a Teaching Assistant at Department of Computer Science, UT Dallas.