Experience
Selected research, industry, and open-source work. Roles and affiliations are stated explicitly.
Industry & Research
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June 2026 - Sept. 2026 Applied Scientist Intern
Microsoft - Working on multimodal reasoning for LLM agents in Microsoft 365 Copilot.
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June 2025 - Sept. 2025 Applied Scientist Intern
Amazon Supervised by Adam Gabryś and Ashwin Chandramouli - Worked on memory and personalization for Amazon Nova language models.
- Developed LikeBench, a benchmark for evaluating subjective likability in personalized LLM responses.
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Sept. 2024 - June 2026 Graduate Researcher
Vision Research Lab, UC Santa Barbara Supervised by Professor B. S. Manjunath - Studied efficient multimodal reasoning agents using self-play reinforcement learning.
- Developed transformer-based methods for multi-month trajectory anomaly detection and temporally grounded video understanding.
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Jan. 2024 - Sept. 2024 Contractor
Google (Remote) Worked with Martin Görner, Product Manager for Keras and TensorFlow - Worked on mathematical reasoning, AI-generated text detection, prompt recovery, and human-preference prediction for LLM responses.
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July 2023 - June 2024 Research Assistant
Institute of Robotics & Automation, BUET Supervised by Dr. Shaikh Anowarul Fattah - Built SONICS, a 97K-song benchmark for detecting fully synthetic music from systems including Suno and Udio.
- Designed an efficient long-audio architecture that improved F1 while reducing runtime and memory use; accepted at ICLR 2025.
Earlier Research
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Feb. 2022 - May 2023 Undergraduate Thesis
Department of EEE, BUET Supervised by Dr. Shaikh Anowarul Fattah - Developed a semi-supervised transformer for joint semantic segmentation and depth estimation, published at WACV 2024.
- Proposed local-global window transformers for monocular depth estimation, published in IEEE Sensors Journal.
- Introduced ArtiFact, a 2.5M-image benchmark for detecting synthetic images from seen and unseen generators, published at ICIP 2023.
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Feb. 2022 - May 2023 Research Collaboration
University of Texas at Dallas (Remote) Supervised by Dr. Mohammad Saquib - Developed a semi-supervised ensemble for attributing synthetic speech to known and unknown generation methods under perturbations.
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Apr. 2020 - Aug. 2020 Research Collaboration
Princeton University (Remote) Supervised by Professor Sun-Yuan Kung - Implemented and evaluated efficient methods for COVID-19 lesion segmentation from CT scans, resulting in an IEEE Transactions on Artificial Intelligence paper.
Open Source & Community
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Nov. 2019 - Present Kaggle Grandmaster
Kaggle - Reached a best rank of 5th among 61,000+ competitors in the Code category.
- Earned 48 gold and 14 silver Code medals, plus one gold and three silver Competition medals.
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Aug. 2021 - Sept. 2023 Developer Expert
Weights & Biases Developer Expert program (Remote) - Tested experiment-tracking workflows, reported issues, and created tutorials for machine-learning practitioners.
- Integrated Weights & Biases into YOLOv5 workflows for underwater object detection.
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2019 - Present Author / Contributor
Open-source machine learning - Contributed multi-backend layers, utilities, and examples to Keras and TensorFlow workflows.
- Resolved dataset and checkpointing issues in Hugging Face Datasets and YOLOv5.
- Released reproducible TensorFlow implementations of GCViT, TransUNet, Conformer, and ContextNet.