Jessilyn Dunn, PhD, is an Associate Professor of Biomedical Engineering and Biostatistics & Bioinformatics at Duke University. She directs the BIG IDEAs Lab, which is focused on digital health innovation, wearable sensors, and the development and validation of AI-driven digital biomarkers. Dr. Dunn is the Principal Investigator of research initiatives funded by the NIH, NSF, and FDA which are developing digital biomarkers of conditions ranging from pre- and type 2 diabetes to influenza-like illness to Opioid Use Disorder. She sits on the Google Consumer Health Advisory Panel and is a recipient of the NSF CAREER Award and the IEEE EMBS Early Career Achievement Award for her leadership and innovation across engineering and medicine.

Dr. Guangyu Wang holds joint faculty appointments at Houston Methodist Research Institute and Weill Cornell Medical College, where he serves as Associate Professor and Director of the Center for Bioinformatics and Computational Biology (CB2). Trained in both mathematics and bioinformatics, his research integrates artificial intelligence with large-scale biomedical data to advance precision medicine in cardiovascular disease and cancer. His laboratory develops multimodal foundation models that connect histopathology, spatial transcriptomics, and multi-omics profiling to decode tissue architecture and cellular state at scale.

At CB2, Dr. Wang leads a cross-disciplinary team of computational scientists and biomedical researchers who design scalable AI systems for tissue analysis, risk stratification, and therapeutic response prediction. His work emphasizes biologically grounded modeling, leveraging foundation models and integrative analytics to translate complex molecular and imaging data into clinically actionable insights. 

Professor Jakob Kather holds dual appointments in medicine and computer science at the Technical University (TU) Dresden, Germany, serves as a senior physician in medical oncology at the University Hospital Dresden and holds an additional affiliation with the National Center for Tumor Diseases (NCT) in Heidelberg. His research is focused on applying artificial intelligence in precision oncology. Prof. Kather’s research team at TU Dresden is using deep learning techniques to analyze a spectrum of clinical data, including histopathology, radiology images, textual records, and multimodal datasets. Guided by the belief that medical and tech expertise needs to be combined, medical researchers in his team learn computer programming and data analysis, while computer scientists are immersed in cancer biology and oncology. Prof. Kather chairs the “Working group on Artificial Intelligence” at the German Society of Hematology and Oncology (DGHO) and is a member of the pathology task force of the American Association for Cancer Research (AACR). His work is supported by numerous European and national grants, which enable the team to develop new deep learning methods for medical data analysis techniques and to apply them in precision oncology.