Vision and Immersive Realities Lab CS@UTSA

Email:
ofmriazrahman.aranya@utsa.edu

Office:
SP1 Room: 340J, 506 Dolorosa St, San Antonio, TX 78204

CV:
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About Me

I’m currently a doctoral student in Computer Science at the University of Texas at San Antonio (UTSA). Before starting my Ph.D., I worked as a software engineer at several software companies based in Dhaka, Bangladesh, where I gained hands-on experience in full-stack development and real-world software engineering.

My research interests lie in image segmentation and generative AI, with a particular focus on applications in the medical domain. I’m passionate about leveraging cutting-edge deep learning techniques to solve challenging problems in healthcare and biomedical imaging. My current work involves developing robust and explainable segmentation models that can assist in medical diagnosis and treatment planning.

Research Interests

  • Vision language model
  • Image segmentation
  • Generative AI
  • Synthetic data

Work Experience

  • Graduate Teaching Assistant, UTSA (Aug 2023 - Present)
  • Software Engineer, RedDot Digital Ltd (Mar 2023 - Jul 2023)
  • Jr. Software Engineer, Nascenia Ltd (Dec 2020 - Feb 2023)

Education

  • BSc in Computer Science and Engineering, Khulna University of Engineering & Technology, 2020

Awards

  • 1st Runner UP, LICT Project Showcasing Jashore IT park, 2019

Recent Publications

TRACE: Temporal Radiology with Anatomical Change Explanation for Grounded X-ray Report Generation
TRACE: Temporal Radiology with Anatomical Change Explanation for Grounded X-ray Report Generation
OFM Riaz Rahman Aranya, Kevin Desai
arXiv  ·  05 Feb 2026  ·  DOI: https://doi.org/10.48550/arXiv.2602.02963
SRA-Seg: Synthetic to Real Alignment for Semi-Supervised Medical Image Segmentation
SRA-Seg: Synthetic to Real Alignment for Semi-Supervised Medical Image Segmentation
OFM Riaz Rahman Aranya, Kevin Desai
arXiv  ·  05 Feb 2026  ·  DOI: https://doi.org/10.48550/arXiv.2602.02944
Comprehensive benchmarking of deep learning approaches for automated astrocyte segmentation in traumatic brain injury
Comprehensive benchmarking of deep learning approaches for automated astrocyte segmentation in traumatic brain injury
Amirhossein Bagherian, OFM Riaz Rahman Aranya, Allison Kosub, Marissa Redington, Kevin Desai, Marzieh Memar
Oxford University Press  ·  27 Oct 2025  ·  DOI: https://doi.org/10.1093/jnen/nlaf114