Biomedical Imaging & AI Laboratory

MedVIS Lab

Medical Vision & Intelligence Systems

We are recruiting!

Looking for motivated B.Tech students to join as research interns

Apply Now

Mission

The MedVIS Lab at UPES Dehradun develops data-efficient and interpretable deep learning systems for clinical medical image analysis. Our work spans novel segmentation architectures, adaptive loss function design, and explainable classification for breast ultrasound, gastrointestinal, and brain imaging modalities. We prioritise methods that generalise across devices and institutions, making high-accuracy AI diagnostics viable in low-resource clinical environments.

Research Themes

Efficient Architectures

Lightweight encoder-decoder networks for real-time clinical deployment

Papers: EfficientU-Net, MSCT-Trans, FAB-Net

Loss Function Innovation

Adaptive and uncertainty-aware training objectives for class-imbalanced medical data

Papers: UMA-Net, DyWAEn, FRS Loss

Interpretable Classification

Explainability-first models that generalise across imaging domains

Papers: SGAN, GA-Ensemble, MSCT-Trans

Team

NameRoleResearch Focus
Dr. Mohsin Furkh DarLab Director, Assistant ProfessorMedical image segmentation, loss function design, interpretable AI
[MTech Student Name]MTech Research Scholar (Co-supervised)[Her research area]

Open Positions — Recruiting B.Tech Students

We are looking for motivated B.Tech students (CSE, IT, or related) to join as research interns. No prior research experience is required — curiosity, consistency, and willingness to learn are what matter most.

What you will gain

  • Hands-on experience with published deep learning research
  • Opportunity to co-author a paper (for strong contributors)
  • Letter of recommendation for higher studies or placements
  • Mentorship in academic research methods and scientific writing

What we expect

  • Basic Python programming (even introductory level is fine)
  • 6–8 hours per week commitment
  • Attend weekly lab meetings
  • Willingness to read one research paper per week

Entry-level tasks available

Dataset annotation and preprocessing
Literature review and summarisation
Code reproduction of baseline papers
Experiment logging and result tracking

How to Apply

Email mohsin.dar@ddn.upes.ac.in with subject "Lab Internship Application"

Attach: A brief paragraph about why you want to do research, and your latest transcript.

Research Translation

ShifaAI

Translating lab research into real-world clinical diagnostic tools. ShifaAI is an AI-powered healthcare platform providing automated medical image analysis and intelligent clinical decision support.

Explore ShifaAI