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The Festival of Genomics, Biodata & AI keynote speakers are all world-leaders in their field, invited for their impact and pioneering, innovative work. Expect to be inspired, educated and also leave these sessions with useful insights and practical tactics and strategies that will make a difference to your work.
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Session: Rewriting the Human Genome: From Fragmented References to True Diploid Genomics
J. Craig Venter is one of the most influential figures in modern genomics. As founder of the J. Craig Venter Institute, he led the private effort to sequence the human genome, fundamentally accelerating the pace and competitive spirit of the Human Genome Project.
Venter’s work has consistently pushed scientific boundaries — from pioneering whole-genome shotgun sequencing to creating the first synthetic bacterial cell controlled by a chemically synthesized genome. His contributions have redefined what is technically possible in biology.
Never content with incremental progress, Venter has focused on bold, high-impact science that challenges conventional thinking. Whether decoding life’s blueprint or engineering it, his career embodies scientific ambition at the highest level. In his keynote, you can expect insights from someone who has not only witnessed the genomics revolution - but actively driven it with future-focused projects.
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Session: The AI-Driven Future of Health: From Genomes to Wearables and Predictive Wellness
Few scientists have shaped modern biology as profoundly as Leroy Hood. A pioneer of systems biology, Hood co-founded the Institute for Systems Biology and has long championed a predictive, preventive, personalized, and participatory model of healthcare.
Hood’s innovations include co-inventing the automated DNA sequencer - a foundational technology for the Human Genome Project - and advancing the integration of big data, biology, and medicine. Today, through Phenome Health, he is working to transform healthcare from reactive disease treatment to proactive health optimization.
His career spans decades of transformative impact, yet his focus remains resolutely future-facing. Hood’s vision challenges traditional boundaries between disciplines and calls for a data-driven reinvention of medicine itself. Hearing him speak at FOG Boston means engaging with one of the architects of modern genomics - and a relentless advocate for its next evolution.
Stacey Gabriel
Executive Vice President, Platforms and Scientific Execution, Broad Institute of MIT & Harvard
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Panel Discussion: Multi-Modal Data at Scale: Discovery, Governance, and Trust
Stacey Gabriel is a driving force behind some of the world’s most ambitious genomics efforts. As Executive Vice President of Platforms and Scientific Execution at the Broad Institute, she oversees large-scale genomic programs that have generated foundational datasets for human disease research.
Gabriel has played a central role in population-scale sequencing initiatives, advancing technologies that make high-throughput, high-quality genomics possible at unprecedented scale. Her leadership has enabled discoveries across cancer, rare disease, and complex trait genetics.
Known for operational excellence and scientific rigor, Gabriel ensures that bold ideas translate into executable, impactful science. She represents the critical bridge between innovation and implementation — where transformative genomic insights are made possible through robust platforms and collaborative execution.
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Session: AI for Genomic Medicine: A Multimodal Deep Learning Journey from Molecules to Single Cells
At the frontier of artificial intelligence and human biology, Manolis Kellis is redefining how we decode the genome. As a Professor at MIT and a core member of the Broad Institute, Kellis has pioneered computational approaches that reveal how genetic variation shapes disease, helping translate DNA sequences into functional insight.
Kellis is known for bringing together machine learning, evolutionary biology, and large-scale genomics to answer some of medicine’s hardest questions. His research doesn’t just generate data - it builds the frameworks that make that data meaningful. For anyone interested in AI-driven biology, functional genomics, or the next era of precision medicine, Kellis offers a rare combination of technical brilliance and biological vision.
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Panel Discussion: From Hype to Translational Value: AI & Machine Learning Powering Precision Drug Discovery
Justin Scheer is helping reshape drug discovery for the AI era. As Vice President of In Silico Discovery at Johnson & Johnson Innovative Medicine, he leads efforts to integrate computational modeling, data science, and machine learning directly into therapeutic innovation pipelines.
Scheer’s work sits at the critical intersection of biology and predictive modeling - where algorithms guide target selection, molecular design, and decision-making long before compounds reach the clinic. By embedding advanced analytics into early discovery, he is accelerating timelines and increasing the probability of success in areas of high unmet need.
His perspective offers a behind-the-scenes look at how one of the world’s largest pharma companies are transforming R&D through AI-enabled discovery.
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Panel Discussion: From Hype to Translational Value: AI & Machine Learning Powering Precision Drug Discovery
John Chan leads one of the most ambitious digital transformations in global pharma. As Global Head of Digital, Informatics and AI at Novartis, he oversees the integration of advanced analytics, AI platforms, and data strategy across the organization’s research and development engine.
Chan’s mission is clear: unlock the full value of data to drive smarter decisions, faster science, and better outcomes for patients. From scalable AI infrastructure to enterprise-wide informatics ecosystems, his work ensures that digital capability becomes embedded at every stage of drug development.
Novartis has continued to strengthen its position as a data-first organization, aligning cutting-edge technology with therapeutic innovation. Chan brings a strategic, global lens to AI in pharma - not just what’s possible, but what’s operationally transformative. His insights are will be critical for anyone navigating the rapidly evolving convergence of digital technology and life sciences.
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Panel Discussion: From Hype to Translational Value: AI & Machine Learning Powering Precision Drug Discovery
Justin H. Johnson builds the AI and data platforms that power oncology R&D at AstraZeneca. As Executive Director of Oncology Data Science, he leads a multidisciplinary organization of engineers, data scientists, AI specialists, and product managers delivering an integrated platform ecosystem, from FAIR data foundations to agentic AI execution, that researchers use daily to accelerate cancer drug development.
Johnson’s career spans two decades of turning scientific ambition into scalable infrastructure, from early large-scale genomic sequencing at the J. Craig Venter Institute to enterprise AI at AstraZeneca. He represents a hands-on model of R&D technology leadership: working closely with scientific visionaries, operationalizing their needs into platforms, and scaling through great engineering teams. For those interested in how AI platforms are tangibly reshaping drug discovery from the inside, his perspective bridges strategy and implementation.
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Panel Discussion: From Hype to Translational Value: AI & Machine Learning Powering Precision Drug Discovery
As Global Head of AI Innovations at Incyte, Aziz Nazha leads initiatives that harness advanced analytics and machine learning to improve drug development.
With a background spanning healthcare and data science, Nazha brings a uniquely translational mindset to AI strategy. His work focuses on predictive modeling, precision oncology, and the development of intelligent systems that support decision-making across the R&D continuum.
Nazha is widely recognized for bridging the gap between algorithm development and clinical utility — ensuring that AI tools are not only sophisticated, but actionable. In a landscape crowded with AI ambition, his approach emphasizes rigor, validation, and patient-centered outcomes. Audiences can expect insights grounded in both scientific depth and frontline healthcare experience.
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Panel Discussion: Multi-Modal Data at Scale: Discovery, Governance, and Trust
Melina Claussnitzer is redefining how we understand the genetic architecture of metabolic disease. As Director of the Broad Diabetes Initiative and faculty at Massachusetts General Hospital, she combines computational genomics with functional biology to uncover how non-coding variants influence disease risk.
Her research has provided groundbreaking insight into obesity and type 2 diabetes, moving beyond association studies to pinpoint causal mechanisms and biological pathways. Claussnitzer’s work exemplifies the next phase of genomics — turning statistical signals into mechanistic understanding.
By integrating AI-driven analysis with experimental validation, she bridges big data and molecular function. Her approach not only deepens our understanding of complex disease but also highlights new therapeutic opportunities. For audiences interested in the functional interpretation of genetic variation, you won’t want to miss her contributions to the panel.
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Panel Discussion: Multi-Modal Data at Scale: Discovery, Governance, and Trust
As Global Head of Discovery Sciences at Novartis, John Tallarico oversees the technologies, platforms, and scientific capabilities that power early-stage therapeutic innovation across multiple disease areas.
Tallarico’s career has centred on translating cutting-edge science into viable drug candidates, integrating chemical biology, screening technologies, and data-driven approaches to improve discovery success rates. His leadership ensures that foundational research capabilities remain aligned with strategic therapeutic priorities.
Operating at the intersection of technology, biology, and organizational scale, Tallarico brings a pragmatic view of how discovery science must evolve to meet rising expectations for speed and precision.
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Panel Discussion: Multi-Modal Data at Scale: Discovery, Governance, and Trust
Woody Sherman is a pioneer of computational drug discovery and AI-driven molecular design. As Founder and Chief Innovation Officer of PsiThera, he continues a career dedicated to transforming how medicines are conceived and optimized.
Previously instrumental in advancing physics-based modeling and structure-guided design in industry, Sherman has helped integrate computational chemistry into mainstream pharmaceutical R&D. His work has shaped approaches to small-molecule design, predictive modeling, and simulation-based discovery.
At PsiThera, he focuses on applying advanced computational methods to unlock new therapeutic possibilities with greater efficiency and precision. His perspective offers a forward-looking vision on how AI and molecular modeling are reshaping the future of drug discovery.