Atif Quamar

Atif Quamar

Visiting Researcher at MBZUAI

About

I am currently a Visiting Researcher at MBZUAI, where I work under the supervision of Prof. Junpei Komiyama. Previously, at UC San Diego, I worked on latent reasoning in vision-language models, and at Purdue University, my work was focused on inference-time alignment of language models. I also founded Insituate, where we shipped agentic systems to banks and judiciary. I earned my bachelors degree in Computer Science and Biosciences from IIIT Delhi in 2024.

I like to understand how foundation models reason and how we can make that reasoning more efficient and trustworthy. A lot of what I do spans language and vision, with a focus on keeping these models safe, reliable and aligned with human values.

Interests
  • Multimodal Reasoning
  • Trustworthy AI
  • AI Alignment and Safety
  • Reinforcement Learning
Education
  • B.Tech in Computer Science and Biosciences, 2020-2024

    IIIT - Delhi

Publications

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(2025). Adaptive Blockwise Search: Inference-Time Alignment for Large Language Models.

Project arXiv

(2025). Learning Modal-Mixed Chain-of-Thought Reasoning with Latent Embeddings. Under review at The 43rd International Conference of Machine Learning (ICML 2026).

Project arXiv

(2025). STARS: Segment-level Token Alignment via Rejection Sampling in Large Language Models. Frontiers in Probabilistic Inference: Sampling Meets Learning Workshop at NeurIPS 2025.

Project arXiv

(2025). Logit–Entropy Adaptive Stopping Heuristic for Efficient Chain-of-Thought Reasoning. Efficient Reasoning Workshop at NeurIPS 2025.

arXiv OpenReview

(2025). Decoding Histone Modification Signatures of Non-Coding RNAs via Foundation Models. Multi-modal Foundation Models and Large Language Models for Life Sciences Workshop at NeurIPS 2025.

OpenReview

Experience

 
 
 
 
 
MBZUAI
Visiting Researcher
Feb 2026 – Present Abu Dhabi, UAE
Working with Dr. Junpei Komiyama on advancing the reasoning capabilities of language models.
 
 
 
 
 
University of Virginia
Research Intern
Oct 2025 – Feb 2026 Charlottesville, Virginia, United States
Worked on developing a drift-resilient memory framework for code-execution agents using KL-constrained adapter updates, mitigating embedding distribution shifts during online learning to reduce unsafe code generation without compromising task success rates.
 
 
 
 
 
University of California - San Diego
Research Intern
Jul 2025 – Oct 2025 San Diego, California, United States
Worked on multimodal reasoning – interleaving text and visuals within the chain-of-thought, enabling models to “think” with sketches, diagrams, and images. This work bridges language and vision to solve complex problems with richer, more interpretable reasoning.
 
 
 
 
 
Purdue University
Research Intern
Feb 2025 – Jul 2025 West Lafayette, Indiana, United States
Worked on inference-time alignment method that outperforms Best-of-N decoding by over 30%, while reducing reward model calls by 20%. Aligned LLMs in reducing harmlessness, improved reasoning and positive sentiment generation.
 
 
 
 
 
Insituate
Co-Founder
Sep 2023 – Feb 2025 New Delhi, India

Built agentic software for the Supreme Court of India, Mizuho Bank, PNC Bank and Indian High Courts.

Insituate is a no-code platform that enables companies to make custom AI agents for industry-specific needs, and allowing them to productionize these copilots 10x faster securely on their data.

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