Aditeya Baral

I am a Masters in Computer Science student at New York University’s Courant Institute of Mathematical Sciences, where I am advised by Shauli Ravfogel and Tal Linzen at the CILVR lab and collaborating with Jackson Petty at the Computation and Psycholinguistics lab.

My research primarily focuses on language understanding, reasoning and interpretability. My work spans representation learning, pre-training and transfer learning techniques, with a focus on studying the training and inference dynamics of language models – how they encode and represent knowledge, apply it to solve tasks, and how we can control and interpret their internal representations.

Previously, I was an Applied Researcher at Cisco Webex AI where I fine-tuned on-prem LLMs to integrate secure and cost-effective AI solutions with the Webex AI Assistant. I have also worked as an Applied Research Scientist Intern at Intel (VSG) Research, where I was advised by Dr. Anbumani Subramanian and Anay Majee to develop attention mechanisms for vision, aimed at autonomous driving in unconstrained, heterogenous traffic environments like India.

Even earlier, I worked as a Research Assistant at the Center for Cloud Computing & Big Data during my undergraduate studies at PES University, where I was advised by Dr. KV Subramanium and worked on analysing tail latencies for latency-critical applications ranging from language to vision.

You can read about my current and my published research on my publications page!