Md. Noman Biswas Sibly

Md. Noman Biswas Sibly

B.Sc. in Electrical and Computer Engineering, RUET

Rajshahi, Bangladesh

I am a final-year B.Sc. student in Electrical and Computer Engineering at Rajshahi University of Engineering & Technology (RUET), Bangladesh. My research sits at the intersection of Trustworthy AI, deep learning, and computer vision, with a focus on building reliable, interpretable AI systems for high-stakes domains such as medical imaging.

My work centres on the reliability of machine learning systems: uncertainty quantification, mechanistic interpretability, and robustness to noisy or shifted inputs. I treat these as general properties of learning systems rather than domain-specific patches. The same questions about calibration, representation quality, and failure detection recur whether the input is a medical scan or a multimodal prompt.

I also have experience in algorithm design and analysis, developed through competitive programming.

I am actively seeking research-oriented graduate opportunities (M.S. / Ph.D.) in intelligent, reliable AI systems. If you are looking for a motivated and research-driven student, feel free to reach out at mdnomanbiswassibly@gmail.com.

Research Interests

  • Trustworthy & Explainable AI (XAI)
  • Uncertainty Quantification & Reliability Under Distribution Shift
  • Mechanistic Interpretability of Neural Networks
  • Medical Image Analysis & AI-driven Diagnostics
  • Vision–Language Models & Generative AI
  • Deep Learning & Computer Vision
  • Embedded AI & Edge Inference (TinyML)

Recent News

2026 First-author paper accepted at the MI4MedFM Workshop, MICCAI 2026 — "Which Reliability Signal to Trust? Output vs. Representation Space Uncertainty Under Distribution Shift in Pathology Foundation Models".
Jul 2026 Placed 6th at the AI Hackathon hosted at DUET — certificate awarded by the Department of Electrical & Computer Engineering, RUET.
Jun 2026 Completed a six-month training program in AI for Immersive Technology under the BDSET Project, Bangladesh Hi-Tech Park Authority, ICT Division — certificate.
2026 Joined the ELITE Research Lab as a part-time Research Assistant, working on mechanistic interpretability of neural networks.
2026 Preparing first-author manuscript JTADC-Net — an adversarial joint task-aware denoising and classification network for noise-robust gallbladder disease diagnosis.
Feb 2026 Co-authored review published in Neural Computing and Applications (Springer, Q1, IF 5.102), 38(4), Article 56 — "A comprehensive review of convolutional neural networks: foundations, enhancements and applications".
2022 Enrolled in B.Sc. ECE program at Rajshahi University of Engineering & Technology.