Podium presentation at USCAP (Boston, USA). Mar 2025
Amritpal Singh
Dr. Amritpal Singh is a physician-scientist with training that bridges medicine, computer science, and artificial intelligence. With an M.B.B.S. from Maulana Azad Medical College and an MS in Computer Science from Georgia Tech, he has built a foundation that spans clinical care and advanced computation. His early work at the BioML Lab involved deep learning, causal inference, multimodal modeling, and medical robotics, focusing on Alzheimer’s disease, genomics, and imaging. He has also contributed as a reviewer and program committee member for major AI conferences.
He is now pursuing his PhD at Emory University under the mentorship of Dr. Anant Madabhushi, where his research centers on developing quantitative multimodal biomarkers that integrate radiology, pathology, genomics, and ocular imaging to predict patient outcomes in colorectal and lung cancer and cardiovascular disease. His broader work includes AI-driven early diagnosis, risk prediction, surgical autonomy, and continual learning, with the aim of creating clinically actionable tools that improve decision-making and transform patient care.
Publications
Please refer to myGoogle Scholar profile for the full list.
European Journal of Cancer, Volume 220, 2025, 115390, ISSN 0959-8049
Digital poster presentation at AHA 2024
GraphPrint: Combining Traditional Fingerprint with Graph Neural Networks For Drug Target Prediction
Combining traditional molecular and protein features with 3D features from graph neural network for drug target affinity prediction.
Class-Incremental Continual Learning for General Purpose Healthcare Models
Building medical imaging AI that can learn new diseases without catastrophic forgetting on previous tasks, in different medical modalities, specialties, and hospitals.
Multi-Modal Deep Feature Integration for Alzheimer’s Disease Staging
Learning Alzheimer’s disease stage classification using multimodal data: MRI, PET, EHR, and Genomics data. Published at IEEE BIBM conference 2023
Autonomous Soft Tissue Retraction Using Demonstration-Guided Reinforcement Learning
Learning to control DaVinci surgical robot for soft tissue manipulation using expert demonstrations.
Multi-Modality Deep Learning Methods to Learn Alzheimer’s Disease Classification
Paper presentation at Suddath Symposium(Biomedical Informatics and AI for Biodiscovery and Healthcare) Georgia Institute of Technology. Mar 2023
Roadmap to Autonomous Surgery - A Framework to Surgical Autonomy
We break down the path of surgical automation into features required and current challenges and advances required to make this happen
We describe CovBaseAI, an explainable tool using an ensemble of three DL models and an expert decision system (EDS) for COVID-Pneumonia diagnosis, trained entirely on pre-COVID-19 datasets.
Personalized Brain State Targeting via Reinforcement Learning
We propose a novel use of reinforcement learning as an active closed-loop assistive system that learns in real time to lead any brain state to a given goal state.
Deep learning based model to re-purpose drugs drugs to new diseases(Neurofibromatosis 2 Vestibular Schwannoma). Part of submission for Hack4Rare hacakathon by MIT.
Project links
(click on image)
Warehouse Robot Optimisation
Team Coordination to Play Football
Robotic Arm for Suturing
Android App to Detect Eye Diseases
Surgical Tracking
Ranzcr X-ray Catheter Detection
Education
- PhD: Emory University: Advisor: Dr Anant Madabhushi. (2024- Present)
- M.S. in Computer Science, Georgia institute of technology, 2022 - Apr 2024
- M.B.B.S.(Bachelor of Medicine, Bachelor of Surgery): Maulana Azad Medical College, 2021
Work experience
- Aug 2023: Research Assistant, Emory University
- Manager: Anant Madabhushi, PhD at Madabhushi Lab
- Developing quantitative multimodal (radiomics, pathomics, genomics) biomarkers to predict patient prognosis and outcomes. Disease area of focus: Colorectal, lung cancer, and Cardiovascular disease
- Program committee member and Research reviewer: Jan 2023 - Present
- NEURIPS conference 2023: Deep Generative Models for Health workshop
- NEURIPS conference 2023: GenBio(Generative AI and Biology) workshop
- IEEE COMPSAC conference 2023, Italy
- Fall 2022: Research Assistant
- Bio-Medical Informatics and Bio-Imaging Laboratory, Georgia Institute of Technology, Altanta
- Advisor: May D. Wang, Ph.D. Professor of Biomedical Engineering
- 2021: Clinical Research Physician
- Qure.ai{https://www.qure.ai} (India)
- Junior Resident: Lok Nayak Hospital:Apr 2020 - Apr 2021
- Clinical rotation at Lok Nayak Hospital and GB Pant Institute of Postgraduate Medical Education & Research(GIPMER), Delhi
- 2020: AI Research intern- CARING and Mahajan Imaging
- 2020: Kaggle x4 Expert
Teaching
- Deep learning – Teaching Assistant, Neuromatch academy, 2021
- Computational neuroscience – Teaching Assistant, Neuromatch academy, 2021
