Scholar
Townim Faisal Chowdhury
Google Scholar ID: Jwefna0AAAAJ
University of Adelaide, Australia
Citations & Impact
Citations
149
H-index
5
i10-index
5
Publications
13
Co-authors
9
list available
Publications
Resume (English only)
Academic Achievements
- Multiple publications at top-tier venues such as CVPR, MICCAI, and ICCV.
Research Experience
- 4+ years of industry experience in software and machine learning engineering. Most recently, worked as a Research Scientist Intern at Dolby Laboratories, exploring mechanistic interpretability in multimodal large language models (e.g., AudioLLMs). Previously, held roles in data engineering and AI product development, leading teams, building ML pipelines, and working closely with clients on deploying real-world solutions.
Education
- Ph.D. in Computer Science at the Centre for Augmented Reasoning, Australian Institute for Machine Learning (AIML), University of Adelaide, supervised by Dr. Zhibin Liao, Dr. Johan Verjans, and Dr. Vu Minh Hieu Phan; B.Sc. in Computer Science & Engineering (Summa Cum Laude) from North South University, Dhaka, Bangladesh, where he worked as a research assistant with Dr. Shafin Rahman on meta-learning for 3D point cloud data and with Dr. Ahsanur Rahman on graph algorithms.
Background
- Research interests include explainable and trustworthy AI (XAI) for medical image analysis and multimodal foundation models. Focuses on developing transparent, reliable, and clinically meaningful AI systems that help clinicians understand not just what a model predicts, but why. Broader research interests span multimodal AI, model's interpretability, generative AI, meta-learning, and continual learning.
Miscellany
- Actively seeking Research Scientist, Applied Scientist, and Postdoctoral opportunities. Enjoys bridging research and application, whether that’s developing interpretable AI for healthcare or tackling new challenges in large-scale ML systems that have real impact on human lives.
