Organization Team

Ilknur Icke, PhD

Ilknur Icke has been a researcher in Pharma R&D for more than a decade (Merck, Takeda, Bayer and Novo Nordisk) driving new opportunities in digital science, data, and AI collaborating with scientists and technologists. Her interests lie in complex systems, at the intersection of sensing and computational modeling. For over a decade in pharmaceutical R&D, she has developed capabilities in modeling and simulation for PK/PD analysis, molecular imaging for neuroscience and oncology, cellular profiling and multi-omics data analysis, and generative modeling for de-novo compound design. She has contributed to various publications and patents in biomedical R&D. She also serves as a reviewer for the MICCAI conference.

Chao-Hui Huang, PhD, Director at Oncology Research Division, Pfizer

Chao-Hui Huang 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.

Ming Tommy Tang, PhD, Director of Bioinformatics, AstraZeneca

Tommy Tang is a Director of Bioinformatics at Astrazeneca in the Oncology Data Science and AI division. He has over 12 years of experience in genomics, epigenomics, and single-cell transcriptomics. He earned his PhD from the University of Florida, trained at MD Anderson, and held non-tenure-track faculty roles at Harvard and Dana-Farber. At AstraZeneca, he leads epigenetics bioinformatics for oncology. A former wet-lab biologist, Tommy is passionate about open science and helping biologists gain computational skills [ https://divingintogeneticsandgenomics.com/].

Program Committee

Alex Drong, PhD

Alex Drong is Bioinformatics Scientist with a focus on integrating single cell and bulk RNAseq with genomics in the context of metabolic and liver diseases. Experience in large-scale population GWAS, Exome-seq and Biobanks. Strong academic background in Genomic Medicine and Statistics (PhD) and Chemistry (MChem). Language-learning and outdoors enthusiast who is always open for new adventures.

Tim Pagliaro

Tim Pagliaro is an imaging scientist with over ten years of experience applying theoretical and systems-based processes to medical and consumer technology. With a background that includes an MS in Bioimaging and ARRT-accredited MRI certification, he operates at the intersection of R&D and clinical medicine. His technical expertise encompasses MRI processing, segmentation, and classification, as well as the implementation of AI and machine learning workflows. Tim has worked with multidisciplinary teams across Fortune 500 firms, Harvard-affiliated teaching hospitals, and biotechnology companies to support research efficiency and technology development.

Mahnaz Maddah, PhD, Director of Machine Learning, Broad Institute

Mahnaz Maddah is the Director of Machine Learning for Health (ML4H) and a principal investigator at the Broad Institute of MIT and Harvard. Dr. Maddah leads the Machine Learning for Health (ML4H) team, which, in close collaboration with clinicians, develops AI/ML methods for improving health outcomes using clinical data and genomics. Dr. Maddah has twenty years of experience in research and industry, with multiple patents and AI products for biomedical applications. Dr. Maddah has served as a principal investigator on multiple grants from the NIH, FDA, and the American Heart Association, and holds a PhD in Electrical Engineering and Computer Science from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL).