We are glad to announce the first International Workshop on Artificial Intelligence for Omics Research in Aging and Cancer (AI4OmicsAC). This inaugural event aims to foster a vibrant and interdisciplinary community at the intersection of artificial intelligence (AI), multi-omics, aging, and cancer research, bringing together rapidly advancing and synergistic fields.

AI4OmicsAC will serve as an international forum to showcase cutting-edge advances in computational multi-omics, with a particular focus on the modeling, analysis, and systems-level interpretation of large-scale omics data in the contexts of aging and cancer.

Aging is broadly defined as the time-dependent decline in physiological functions essential for survival and reproduction. It is also the strongest known risk factor for cancer, due to cumulative molecular damage, genomic instability, cellular senescence, immune system decline, and other biological changes that create a pro-tumorigenic environment. Shared mechanisms such as oxidative stress, mitochondrial dysfunction, and epigenetic alterations underlie both aging and cancer, contributing to complex, organ-specific disease pathways. As a result, biomarkers associated with aging and cancer are increasingly studied in parallel, often with overlapping diagnostic and prognostic value across different tissues and cancer types.

This workshop is designed to provide a focused, interdisciplinary platform that brings together computational scientists, systems biologists, geroscientists, and oncologists, offering strong potential to catalyze new collaborations and drive translational research that applies advanced AI methodologies to some of the most pressing challenges in human health.

Recent advances in machine learning (ML) and AI are transforming the analysis of large-scale omics data, opening up exciting opportunities to unravel biomarkers and the complex biological mechanisms underlying aging and cancer. This workshop will convene researchers from computational biology, bioinformatics, aging research, and oncology to explore how state-of-the-art AI techniques can be applied to multi-omics datasets—such as genomics, epigenomics, transcriptomics, and proteomics—to identify biomarkers, model aging trajectories, and uncover molecular pathways.

AI4OmicsAC will provide a unique platform for interdisciplinary exchange, encouraging discussions of challenges, innovations, and breakthroughs in integrating AI and omics data for translational applications, including personalized interventions, cellular rejuvenation, and the discovery of shared and exclusive mechanisms between aging and cancer.

Schedule

 8:30- 8:40  Introduction and Welcome - (Hayan Lee)

             Session 1 (Chair: Rob Kulathinal)

 8:40- 9:10  Keynote speaker - Harnessing AI and Informatics for Precision Medicine in Dementia (Li Shen, PhD)

 9:10- 9:30  Research Talk 1 - EnsembleAge Clock: A reliable and robust epigenetic age clock service (Hayan Lee, PhD)

 9:30- 9:50  Research Talk 2 - AI for Better Aging: Personalizing Smart Care for Rare ALS (Huanmei Wu, PhD)

 9:50-10:20  Coffee Break

             Session 2 (Chair: Hayan Lee, Rob Kulathinal)             

10:20-10:40  Research Talk 3 - Multi-omics to decipher neuron degeneration (Lu Chen, PhD)   

10:40-11:00  Research Talk 4 - Generative AI for Genomics and Epigenomics (Mindy Shi, PhD)

11:00-11:30  Keynote speaker - Large Language Models for improving phenotype-driven rare disease diagnosis (Kai Wang, PhD)

11:30-12:10  Panel discussion (All speakers and Rob Kulathinal)

Let us know if you'll be attending!

Nooshin Kianvashrad said, "Among all the workshops I attended on the first day of ACM-BCB, I found AI4OmicsAC the most engaging. I particularly enjoyed the presentations — the keynote talks were truly at the cutting edge of science and research and deeply motivating."

Seyed Mehedi Azim said, "I was able to attend one complete talk which was by Dr Wang and found that really impressive. He talked about the research in his group focusing on Large Language Models for improving phenotype-driven rare disease diagnosis where he discussed a few methods they developed so far which was really great."