About
I am a Research Scientist in the AI for Medical Devices team at Haag-Streit, where I develop cutting-edge deep learning solutions for surgical skill assessment, virtual reality guidance, and automated video analysis in ophthalmology. My work bridges AI research and real-world clinical applications, focusing on enhancing surgical precision, improving diagnostic accuracy, and optimizing workflow efficiency in medical imaging and surgical video analysis.
Prior to joining Haag-Streit, I conducted postdoctoral research at the University of Bern’s AI for Medical Imaging lab, where I led projects in domain adaptation, semi-supervised learning, and phase recognition in surgical videos. My PhD research at Klagenfurt University focused on advanced deep learning models for surgical video analysis, including phase and action recognition, real-time anomaly detection, and relevance-based video compression. My work has contributed to AI-driven surgical content retrieval systems currently in use at major hospitals, supporting both clinical decision-making and surgical training.
News
Negin Ghamsarian #unibern believes that #deeplearning can overcome current constraints in the feasibility of #AI techniques for surgical video analysis to better predict postoperative complications and allow more precise surgical interventions: https://t.co/dONUxaiPYO. pic.twitter.com/r5WnrzhM2W
— Universität Bern (@unibern) August 30, 2023
Fields of Expertise & Research
Domain
- Computer Vision & Deep Learning
- Medical Image & Video Analysis
- AI for Medical Devices & Healthcare
- Image & Video Compression
- Information Theory
Core AI Techniques
- Supervised, Self-Supervised, and Semi-Supervised Learning
- Domain Adaptation & Generalization
- Generative Modeling & Diffusion Models
- Large Language Models (LLMs) & Multimodal Learning
- Retrieval-Augmented Generation (RAG) & LangChain
Applications in Healthcare AI
- Semantic Segmentation & Object Detection – Surgical scene understanding, pathology detection
- Action Recognition & Irregularity Detection – Surgical skill assessment, anomaly detection
- Virtual Reality & AI-assisted Surgery – Real-time guidance, augmented intelligence for medical professionals
- Edge & Cloud AI for Medical Devices – Optimizing AI models for real-time hospital deployment
Education
Ph.D. in Computer Science
03.2019 - 09.2021
Department of Information Technology, Alpen-Adria-Universität Klagenfurt, Austria
Dissertation Title: "Deep-Learning-Assisted Analysis of Cataract Surgery Videos"
Supervisors:
Assoc. Prof. Dr. Klaus Schoeffmann
Prof. Dr. Christian Timmerrer
Examiners:
Prof. Dr. Henning Müller, HES-SO Valais and University of Geneva, Switzerland
Prof. Dr. Raphael Sznitman, University of Bern, Switzerland
Grade: 1 - excellent
Visiting Scholar
08.2021 - 09.2021
HES-SO, University of Applied Science Western Switzerland
M.Sc. in Electrial Engineering
09.2013 - 10.2016
Department of Electrical Engineering, Ferdowsi University of Mashhad, Iran
Thesis Title: "Undetectable Video Steganography Based on Statistical Differences of Motion Vectors, Before and After Embedding"
Supervisor:
Prof. Morteza Khademi
Examiners:
Ass. Prof. Dr. Seyed Alireza Seyedin, Ferdowsi University of Mashhad, Iran
Prof. Dr. Raphael Sznitman, Ferdowsi University of Mashhad, Iran
Employment
Research Scientist
08.2024 - Present
Haag-Streit
- Developing AI-powered solutions for surgical skill assessment, including both subjective and automated evaluation in wetlab cataract surgery.
- Leading research on real-time intraoperative AI for surgical video analysis, optimizing procedural workflows and improving decision support.
- Implementing virtual reality guidance systems for cataract surgery, enhancing precision and intraoperative visualization.
- Developing AI-driven quality assessment models for slit-lamp videos, enabling automated relevance detection and active learning.
- Bridging AI research with clinical applications to ensure model robustness, validation, and seamless real-world integration.
Postdoctoral Researcher
02.2022 - 07.2024
ARTORG Center for Biomedical Engineering Research, Department of Medicine, University of Bern
- Conducted research on semi-supervised learning and domain adaptation for medical image analysis.
- Focused on semantic segmentation, phase recognition in surgical videos, and AI-driven workflow analysis.
- Supervised MSc and PhD students in deep learning applications for medical imaging.
Postdoctoral Researcher
10.2019 - 12.2021
Department of Information Technology, Alpen-Adria-Universität Klagenfurt, Austria
- Developed real-time intraoperative irregularity detection systems for surgical safety enhancement.
- Designed deep learning models for postoperative complication prediction, leveraging intraoperative data and patient-specific metrics.
Research Assistant
03.2019 - 09.2021
Department of Information Technology, Alpen-Adria-Universität Klagenfurt, Austria
- Developed deep learning architectures for surgical phase recognition, object localization, and instance tracking.
- Contributed to relevance-based compression techniques for efficient storage and retrieval of surgical videos, now deployed in major eye hospitals in Austria.
- Focused on surgical scene segmentation, overcoming challenges like occlusion, motion blur, and transparency.
Teaching
Biomedical Engineering Laboratories
02.2024 - 05.2024
University of Bern
Master's Course, Biomedical Engineering
Biomedical Engineering Laboratories
02.2023 - 05.2023
University of Bern
Master's Course, Biomedical Engineering
Biomedical Engineering Laboratories
02.2022 - 05.2022
University of Bern
Master's Course, Biomedical Engineering
Web Technologies
10.2019 - 01.2020
University of Klagenfurt
Bachelor's Course, Computer Science
Image and Video Processing with Matlab
06.2016 - 09.2016
Ferdowsi University of Mashhsad
Workshop, Electrical Engineering
Image Processing with Matlab
06.2015 - 09.2015
Ferdowsi University of Mashhsad
Workshop, Electrical Engineering
Fields and Waves Electromagnetics
09.2014 - 01.2015
Eqbal Institute of Higher Education
Bachelor's Course, Electrical Engineering-Electronics and Electrical Engineering-Robotics
Technical Skills
Programming Languages
- Python (Expert)
- C++ (Intermediate)
- C (Intermediate)
- Matlab (Intermediate)
- Web Development (HTML, CSS, JavaScript, NodeJS - Advanced)
AI & Deep Learning Frameworks
- PyTorch (Expert)
- TensorFlow (Intermediate)
- Keras (Advanced)
Data Processing & GPU Acceleration
- Image & Video Processing (OpenCV, FFmpeg - Intermediate)
- Medical Image Analysis (MONAI - Intermediate)
- GPU Acceleration (CUDA, cuDNN - Intermediate)
Model Optimization & Inference
- ONNX (Model Interoperability - Intermediate)
- TensorRT (High-Performance Inference - Intermediate)
- Triton Inference Server (Scalable AI Deployment - Intermediate)
AI Deployment & Cloud Services
- Cloud AI (AWS, Azure, Google Cloud - Intermediate)
- Model Compression (Quantization, Pruning, Knowledge Distillation - Advanced)
- Edge AI (Optimized AI for Low-Power Devices - Intermediate)
- Federated Learning (FLARE - Intermediate)
Selected Publications
- All
- PhD Dissertation
- Conference Papers
- Journal Papers
Academic Services
Journal Reviewer
- IEEE Transactions on Medical Imaging (TMI)
- Medical Image Analysis
- IEEE Transactions on Multimedia
- Multimedia Tools and Applications (MTAP)
- Multimedia Systems
- Journal of Clinical Medicine
- Expert Systems with Applications
- Biocybernetics and Biomedical Engineering
Program Committee Member
- MICCAI 2024 – International Conference on Medical Image Computing and Computer-Assisted Interventions
- MICCAI 2023
- ACM ICMR 2021 – International Conference on Multimedia Retrieval
- MMM 2021 – 27th International Conference on Multimedia Modeling
- LSC'21 – Fourth Lifelog Search Challenge at ACM ICMR
- CBMI 2021 – 18th Conference on Content-Based Multimedia Indexing
- ACM MM Asia 2020
- ACM MM 2020 – ACM Multimedia Conference
- ICMR 2020 – International Conference on Multimedia Retrieval
Organization Committee
- Best Poster/Demo Committee, ACM International Conference on Multimedia Retrieval (ICMR 2020)
Contact
Location:
ARTORG Center for Biomedical Engineering Research, Murtenstrasse 50, 3008 Bern, Switzerland
Email:
negin.ghamsarian@unibe.ch
Call:
+41 31 632 75 91