Highly accomplished AI/ML researcher and engineer with a 9.195/10 CGPA from IIT Roorkee, specializing in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Computer Vision. Proven ability to develop and evaluate advanced AI systems, evidenced by multiple research internships, publications in top-tier workshops (NeurIPS, AAAI), and innovative projects. Seeking to leverage deep technical expertise and research acumen to drive impactful advancements in AI development.
Remote, India
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Summary
Pioneered the development of advanced AI benchmarks and contributed to reinforcement learning frameworks for vision-language models at a leading research firm.
Highlights
Developed a novel benchmark, inspired by ZeroBench, for complex visual reasoning, integrating an automated question-generation pipeline to train and evaluate vision-language models on GPT-level reasoning tasks.
Contributed to a reinforcement learning-based training framework, specifically designed to enhance models' ability to ground reasoning in visual inputs, reducing reliance on textual cues.
Pioneered the creation of a sophisticated evaluation system for next-generation AI models, setting a new standard for visual-language understanding.
Remote, India
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Summary
Explored and optimized Retrieval-Augmented Generation (RAG) architectures, establishing robust local benchmarking setups for Large Language Models (LLMs).
Highlights
Explored and analyzed cutting-edge agentic Retrieval-Augmented Generation (RAG) architectures to optimize information retrieval and synthesis for complex queries.
Established a robust local benchmarking setup using tools like Ollama, enabling efficient deployment and performance evaluation of Large Language Models (LLMs).
Boston, MA, US
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Summary
Investigated self-awareness in Large Language Models (LLMs) and evaluated fine-tuning methods to understand model behavior and generalization.
Highlights
Investigated self-awareness in Large Language Models (LLMs) through in-depth analysis of alignment between internal reasoning and external outputs.
Evaluated the performance of SFT, DPO, and GRPO tuned models on tasks involving bias, risk, and reward hacking, providing critical insights into model vulnerabilities.
Designed and executed comprehensive experiments to rigorously test the awareness of learned behaviors and generalization of reasoning across diverse domains.
Core Member
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Summary
Actively participated in ACM chapter activities, contributing to initiatives that advance computer science education and community engagement at IIT Roorkee.
Highlights
Collaborated with fellow members to promote computer science and foster a vibrant academic community.
Contributed to the development and dissemination of technical knowledge through participation in group projects and discussions.
Supported the chapter's mission to provide resources and opportunities for students interested in computing.
Head of Projects
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Summary
Led project planning and execution, fostered an active Deep Learning community, and moderated discussions within the Vision and Language Group at IIT Roorkee.
Highlights
Orchestrated the overall planning and moderation of research projects, contributing to strategic direction and successful project outcomes.
Organized and moderated paper discussions, enhancing knowledge sharing and collaborative research initiatives within the group.
Actively contributed to the development of an active Deep Learning community on campus, fostering growth and engagement among students.
Published by
AAAI'26
Summary
Analyzed self-awareness and reasoning alignment in Large Language Models (LLMs) across various scenarios, evaluating the impact of SFT, DPO, and GRPO fine-tuning on model behavior, including bias, risk, and reward hacking.
Published by
NeurIPS’24 Math-AI Workshop
Summary
Conducted a study on LLMs' ability to utilize hints in mathematical problem-solving on the MATH dataset, benchmarking zero-shot, few-shot, chain-of-thought, and adversarial hinting against traditional prompting.
Founder, Lossfunk, Wingify