Tajamul Ashraf
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I am currently a Research Engineer at MBZUAI, working in the Intelligent Visual Analytics Lab (IVAL). I am primarily advised by Prof. Salman Khan and Prof. Fahad Khan, and I also closely collaborate with Prof. Rao Anwer. Previously, I was a Research Intern at Microsoft Research India in Bengaluru. Recently, I completed my Master's degree in Computer Science from the Indian Institute of Technology Delhi under the guidance of Prof. Chetan Arora. My academic journey began with Bachelor's degree in Information Technology from the National Institute of Technology, Srinagar.

Outside of work, I enjoy playing badminton and swimming quite often. I'm also passionate about making a positive impact on the society which led me to initiate Ralith Milith, an anti-drug society in Kashmir.

"What is now proved was once only imagined." -William Blake.

News

  • June 2025 : Thrilled to share that our paper TITAN has been accepted to the prestigious ICCV 2025!
  • June 2025 : Excited that our paper ToolSeg is accepted to MICCAI 2025!
  • Feb 2025 : Honored to serve as a reviewer for: ACM MM 2025, MICCAI 2025, WACV 2025, and ICCV 2025.
  • Dec 2024 : Humbled to be nominated as a Diversity Intern by Microsoft Canada! [Watch the announcement]
  • Oct 2024 : Grateful to receive the RISE-MICCAI travel grant to attend MICCAI 2024 in person!
  • Oct 2024 : Our work HF-Fed was accepted as an oral presentation at MICCAI-W 2024. Best Student Paper Award!
  • June 2024 : Successfully defended my Master’s synopsis at IIT Delhi
  • May 2024 : Proud to announce that D-MASTER has been accepted to MICCAI 2024!
  • Nov 2023 : Our paper got accepted at WACV 2024 – looking forward to sharing it with the community!
  • July 2023 : Presented our work at CVIP 2023. Grateful for the opportunity!
  • Mar 2023 : Our research was accepted at ICDSA 2023!
  • Jan 2023 : Contributed as a reviewer for CVIP 2022/23 and HPEC 2023.
  • Aug 2022 : Began my Master’s journey at IIT Delhi. An exciting chapter begins!
  • June 2022 : Graduated from NIT Srinagar with the prestigious Gold MSLA Award!
  • Feb 2021 : Won India’s largest National Entrepreneurship Challenge hosted by IIT Bombay. A game-changing experience!

Research

My research interests lie at the intersection of multimodal systems in vision and language domains, with a focus on enhancing reasoning and decision-making capabilities. I am particularly interested in addressing the challenges faced by large multi-modal models across discriminative, generative, and perceptual understanding tasks, especially in Out-Of-Distribution (OOD) and federated scenarios. My work explores domain adaptation, reinforcement learning, causal reasoning, and knowledge distillation techniques to improve the robustness and generalization of AI models in complex, real-world environments such as healthcare and robotics.

Publications

  • Selected
  • All
* indicates equal contribution, † indicates my role as mentor
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TITAN: Query-Token based Domain Adaptive Adversarial Learning
Tajamul Ashraf, Janibul Bashir
Accepted at ICCV 2025

webpage | abstract | code

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MIRA: A Novel Framework for Fusing Modalities in Medical RAG
Jinhong Wang*, Tajamul Ashraf*, Zongyan Han, Jorma Laaksonen, Rao Mohammad Anwer
Accepted at ACM Multimedia 2025

webpage | abstract | code

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D-MASTER: Mask Annealed Transformer for Unsupervised Domain Adaptation in Breast Cancer Detection from Mammograms
Tajamul Ashraf, Krithika Rangarajan, Mohit Gambhir, Richa Gabha, Chetan Arora
Accepted at MICCAI 2024

webpage | abstract | presentation | code| poster

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TransFED: A way to epitomize Transformer based Focal Modulation using Federated Learning
Tajamul Ashraf, Fuzayil Mir, Iqra Altaf Gillani
Accepted at WACV 2024

webpage | abstract | presentation code | poster |

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HF-Fed: Hierarchical Based Customized Federated Learning Framework for X-Ray Imaging
Tajamul Ashraf, Tisha Madame
Accepted at MICCAI DeepBreath 2024 (Oral) Best Student Paper Award!

webpage | abstract | presentation | code

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Context Aware Grounded Teacher for Source Free Object Detection
Tajamul Ashraf, Rajes Manna, Partha Sarathi Purkayastha, Tavaheed Tariq, Janibul Bashir
Arxiv 2025

webpage | abstract | code

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LLM Post-Training: A Deep Dive into Reasoning Large Language Models
Komal Kumar*, Tajamul Ashraf*, Omkar Thawakar, Rao Muhammad Anwer, Hisham Cholakkal, Mubarak Shah, Ming-Hsuan Yang, Phillip H.S. Torr, Fahad Shahbaz Khan, Salman Khan
Arxiv 2025

webpage | abstract | code

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Enhancing Climate Change Understanding: A Novel Deep Learning Framework with the Climate Change Parameter Model.
Tajamul Ashraf, Janibul Bashir
MoSICom 2024

webpage | abstract | code

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Phase-Informed Tool Segmentation for Manual Small-Incision Cataract Surgery
Bhuvan Sachdeva, Naren Akash, Tajamul Ashraf, Simon Muller, Thomas Schultz, Maximilian WM Wintergerst, Niharika Singri Prasad, Kaushik Murali, Mohit Jain
MICCAI 2025

webpage | abstract | presentation | code

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FATE: Focal-modulated Attention Encoder for temperature prediction
Tajamul Ashraf, Janibul Bashir
ArXiv 2024

webpage | abstract | code

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D-MASTER: Mask Annealed Transformer for Unsupervised Domain Adaptation in Breast Cancer Detection from Mammograms
Tajamul Ashraf, Krithika Rangarajan, Mohit Gambhir, Richa Gabha, Chetan Arora
MICCAI 2024 [Poster]

webpage | abstract | presentation | code

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HF-Fed: Hierarchical Based Customized Federated Learning Framework for X-Ray Imaging
Tajamul Ashraf, Tisha Madame
MICCAI DeepBreath 2024 [Oral] Best Student Paper Award!

webpage | abstract | presentation | code

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TransFED: A way to epitomize Transformer based Focal Modulation using Federated Learning
Tajamul Ashraf, Fuzayil Mir, Iqra Altaf Gillani
WACV 2024 [Poster]

webpage | abstract | presentation | code

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PoseWatch: Advancing Real Time Human Pose Tracking and Juxtaposition with Deep Learning
Tajamul Ashraf, Balaji Prabu BV, and Omkar SN
CVIP 2023

abstract | presentation

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Climate Change Parameter Dataset (CCPD): A Benchmark Dataset for Climate Change parameters in Jammu and Kashmir
Tajamul Ashraf, Janibul Bashir
ICDSA 2023

abstract | presentation

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An Integral Computer Vision System for Apple Detection, Classification, and Semantic Segmentation,
Tajamul Ashraf, Naiyer Abbas, Mohammad Haseeb, Nadeem Yousuf, Janibul Bashir
ICMV 2022

abstract | presentation | code

Timeline

Community

    In my academic journey, I transitioned into a research-focused lifestyle, driven by a deep curiosity to explore Computer Vision and Medical Imaging. My path has been dynamic, with a domain shift from IoT to robotics, reflecting a continuous pursuit of learning and innovation. I am an advocate for open-source contributions, as they foster collective growth and help both educators and learners critically engage with the wealth of information available online. The guidance and support of my academic mentors and peers have been pivotal in shaping my early career, and their influence continues to inspire me.
    Building on this foundation, I am actively mentoring undergraduate and master’s students in computer vision, and I look forward to supporting more learners in the future. I particularly encourage students with diverse backgrounds or unconventional academic paths, similar to my own, to connect and explore opportunities for growth and research.
    If you are interested, send an introductory email that includes:
    - A brief introduction about yourself.
    - Your academic background and areas of interest.
    - Your CV (optional but preferred).