Yasmeena Akhter is a Kashmiri-born researcher currently holding a Visiting Researcher Position at MBZUAI. She works with Professor Marcos Matabuena in the Department of Epidemiology. She completed her PhD in the Department of Computer Science and Engineering at the Indian Institute of Technology, Jodhpur, Rajasthan, India. She worked with Professor Mayank Vatsa and Professor Richa Singh at the Image Analysis and Biometrics Lab, IIT Jodhpur, Rajasthan, IN. She is a specialized in healthcare AI for resource-constrained environments. Her research focuses on developing efficient deep learning frameworks through a multimodal approach, with a particular emphasis on lightweight and interpretable model architectures that deliver accurate automated diagnosis under computational and infrastructural constraints. She is driven by a commitment to democratizing advanced diagnostic AI, bridging the gap between state-of-the-art AI research and the realities of underserved healthcare systems globally.

Research Interests: Pattern recognition, Interpretable deep learning, HealthcareAI, Medical imaging, and Trusted AI.

• Paper got accepted at MICCAI 2026, Strasbourg, France

• Selected to attend AHLI Summer health camp 2024, University of Washington, Seattle

• Paper got accepted at AAAI 2026, Singapore

• Paper got accepted at MICCAI 2025, Deajeon, Korea

• Received a Travel grant to attend IJCAI and MICCAI 2025

• Paper got accepted at IJCAI 2025, Montreal, Canada

• Selected to present our work at CHIL DC,  University of Berkeley

• Paper got accepted in Nature Scientific Data

• Selected to attend the Google DeepMind Research Symposium 2025 by Google in Bangalore.

• Paper accepted at ISBI, 2024

• Selected to attend  Google Research Week 2024 by Google in Bangalore.

• Presented Paper at IJCAI, Macau, SAR, 2023

• Selected to attend  Maitreyee 2023 by IBM in Bangalore.

• Received a travel grant from Microsoft Research to attend IJCAI'23 in S.A.R Macau

• Selected for the Doctoral Symposium, CHIL 2023

• Selected for the Doctoral Consortium, MIDL, 2023

• Paper accepted at IJCAI, 2023

• The Review paper was published at Frontiers in Big Data 2023

• Our work got accepted for poster presentation at the WiCV CVPR workshop 2023