Contact Information
| Name | Atif Quamar |
| Professional Title | Visiting Researcher at MBZUAI |
| mohammad.atif@mbzuai.ac.ae | |
| Website | https://www.atifquamar.com |
Professional Summary
I study efficient and reliable reasoning in foundation models. 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.
Experience
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Visiting Researcher
Mohamed bin Zayed University of Artificial Intelligence
Exploring self-consistency and uncertainty in language model reasoning.
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Research Intern
University of Virginia
Developed 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.
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Research Intern
University of California - San Diego
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.
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Research Intern
Purdue University
Proposed an 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.
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Co-Founder
Insituate
Built agentic software for the Supreme Court of India, Mizuho Bank, PNC Bank and Indian High Courts.
Education
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2020 - 2024 New Delhi, India
Bachelor of Technology
IIIT - Delhi
Computer Science and Biosciences
Interests
Publications
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2025 Logit-Entropy Adaptive Stopping Heuristic for Efficient Chain-of-Thought Reasoning
NeurIPS 2025 - Efficient Reasoning Workshop
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2025 Decoding Histone Modification Signatures of Non-Coding RNAs via Foundation Models
NeurIPS 2025 - FM4LS Workshop