I am a PhD student in the Machine Learning Department at MBZUAI, advised by Prof. Zhiqiang Shen. My work explores how to retain the most useful supervision while reducing the data, storage, and computation required to train modern models.
Previously, I received an M.Sc. in Machine Learning from MBZUAI and a B.Sc. (Hons) in Artificial Intelligence and Computer Science with First-Class Honours from the University of Edinburgh.
- Aug 2026 — PIXAR accepted to ECCV 2026.
- Apr 2026 — HALD accepted to ICML 2026.
- Apr 2026 — LLMSurgeon accepted to ACL 2026.
- Sep 2025 — FADRM accepted to NeurIPS 2025.
| Project | Venue | What it explores | Links |
|---|---|---|---|
| PIXAR | ECCV 2026 | Pixel-grounded, semantic-aware VLM image tampering | Paper · Code |
| HALD | ICML 2026 | Hard labels as semantic anchors for storage-efficient dataset distillation | Paper · Code |
| LLMSurgeon | ACL 2026 | Diagnosing and repairing data mixtures in large language models | Project coming soon |
| FADRM | NeurIPS 2025 | Fast and accurate data residual matching for dataset distillation | Paper · Code |
| CV-DD | Preprint | Dataset distillation through committee voting | Paper · Code |
For the complete publication list, visit my homepage or Google Scholar.
University of Edinburgh MBZUAI MBZUAI
B.Sc. AI & Computer Science → M.Sc. Machine Learning → Ph.D. Machine Learning
2019–2024 · First-Class Honours 2024–2026 2026–2030 (expected)
I am always open to academic collaboration and discussions around data-centric AI, dataset distillation, and efficient learning. If our interests overlap, feel free to send me an email.