Ajay Rajendra Kumar

I am a researcher interested in building AI systems that can reliably reason over visual, temporal, and contextual information. In particular, my current work focuses on multimodal reasoning and understanding how AI systems can integrate information across modalities to make more reliable and informed decisions. I hold a Master's in Computer Science from Northeastern University and a Bachelor's in Computer Science from Manipal Institute of Technology, Manipal.

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Research

My research focuses on building AI systems that can reason over heterogeneous multimodal information, with an emphasis on long-horizon reasoning, evidence grounding, and reliable decision-making. I am particularly interested in how multimodal models can identify, retrieve, and integrate context-relevant evidence to reason over spatial, temporal, and causal relationships. At Prof. Lorenzo Torresani's Lab, I worked on video understanding and multimodal reasoning with vision-language models. Previously, at Prof. Huaizu Jiang's Visual Intelligence Lab, I worked on efficient visual SLAM, developing dense visual perception methods for real-time deployment on edge devices.

A dense visual SLAM system designed specifically for stereo and RGB-D sensors, optimized to run real-time on resource-constrained edge devices.

Combines transformer-based language models with user association dynamics to detect and counter vaccine misinformation on social media platforms.

Design and source code from Jon Barron's website