| Person | Affiliation | Description |
|---|---|---|
| Dawid Rymarczyk | Ardigen SA Jagiellonian University |
Dawid’s research focuses on applying computer vision to drug design, particularly in morphological and phenotypical profiling of molecular activity and patient data. He is also deeply engaged in explainable artificial intelligence (xAI), with a specific interest in fine-grained classification. Dawid holds a PhD in computer science from Jagiellonian University, where he is currently a post-doctoral researcher. He serves as the Director of Data Science and AI at Ardigen. Dawid has played a key role in organizing the xAI 2.0 conference special track, the xAI 3.0 workshops at ECAI 2023, and various internal research group meetings, including the Ardigen Summit. He regularly reviews for leading conferences such as CVPR, ECCV, ICCV, NeurIPS, ICLR, AAAI, and AISTATS. His research includes work on morphological profiling of cell images, histopathology slide analysis, and developing self-explainable methods for fine-grained classification. Dawid presented multiple works at conferences such as BiotechX, Discovery Europe, and IBD Summit, where he showed applications of computer vision techniques to life sciences. |
| Ilknur Icke | Novo Nordisk | Ilknur is interested in the study of complex systems, at the intersection of sensing and computational modeling for better understanding and interventions. Her prior experience includes active learning based design of real-time fMRI experiments and computational modeling of such experiments to study human brain. Ilknur has been in the pharmaceuticals R&D domain for almost a decade working in highly interdisciplinary teams developing capabilities in such areas as modeling & simulation tools for PK/PD analysis, molecular imaging applications for neuroscience and oncology, as well as analysis of multi-omics data and generative modeling for de-novo compound design. Ilknur also has been serving as a reviewer for the MICCAI conference |
| Chao-hui Huang | Pfizer | Chao-Hui is a Director at Pfizer Oncology Research Division, responsible for enabling artificial intelligence and digital image analysis technologies for supporting computational biological research. His experiences include spatial multi-omics, digital pathology, and medical image analysis. In addition, he also has a track of exploring advanced applications of large language models for assisting computational biology and drug discovery. Within his 27 years of experience, he has published 39 papers in various conferences and journals, 4 patents and 1 book chapter in the areas of artificial intelligence and machine learning-related biomedical research. |
| Gayathri Mohankumar | AstraZeneca | Gayathri is a Lead Computer Vision Scientist at Astrazeneca. With her background in the field of healthcare, she hopes to automate the various processes in this field such as automatically recognizing patients in the ER, image-guided surgeries, automatic disease diagnosis which will ultimately lead to a better healthcare service and a larger ratio of good outcomes. |
| Anne Carpenter | Broad Institute SyzOnc |
Anne E. Carpenter is a computational biologist and the director of the Imaging Platform at the Broad Institute of MIT and Harvard. She is best known for her pioneering work in developing CellProfiler, an open-source software tool designed for high-throughput image analysis, which has become widely used in biological research. Her work has significantly contributed to advancing image-based screening in biology and medicine, particularly in the field of drug discovery and genomics. |