Parthiban Srinivasan, an experienced data scientist, earned his PhD from Indian Institute of Science, specializing in Computational Chemistry. After his PhD, he continued the research at NASA Ames Research Center (USA) and Weizmann Institute of Science (Israel). Then he worked at AstraZeneca in the area of Computer Aided Drug Design for Tuberculosis. Later, he headed informatics business units in Jubilant Biosys and then in GvkBio before he floated the company, Parthys Reverse Informatics and later an AI consultancy, Vingyani. Currently, he is a Professor at Indian Institute of Science Education and Research (IISER) Bhopal, teaching Data Science.

Ari received his Ph.D. in Molecular Biology with a focus on Neuroscience in 2005 from the University of Texas at Austin (UT). His graduate work focused on studying the effects of genetics on addictive behaviors such as alcoholism. His postdoctoral fellowships at the University of California, San Francisco (UCSF) and the Buck Institute for Research on Aging focused on improving our understanding of neurodegenerative diseases of aging (specifically, Parkinson’s and Alzheimers Disease) by utilizing a combination of laboratory science and animal models, as well as bioinformatics and computational biology. Ari is also an expert in Scientific Computing specializing in high performance computing (HPC), high-performance networks, data centers, storage, cloud, general IT infrastructure, and bioinformatics and data analytics. He has been designing, building, and operating scientific computing environments for 27 years and strives to advocate for science and empower researchers to make discoveries from their complex datasets. His ultimate goal is to help create a dynamic enough abstraction of flexible infrastructure from research end-users to enable anyone to analyze and gain knowledge from very complex datasets.

Simon works with organizations to help them identify and address the broad challenges impacting modern biomedical data science – FAIR data, data management, use of the cloud, sustainability of data resources, and enabling ethical and responsible AI. He was an early pioneer in the cloud, with his group publishing one of the first papers to use the Amazon cloud for biomedical research in 2009. At BioTeam, he has built PaaS applications on AWS, variant annotation pipelines (that led to a 2017 Nature Neuroscience paper) on GCP, and supported the NIH STRIDES program to help move data platforms onto the cloud. He has led projects to outline the goals for national data ecosystems and define the needs for large-scale biomedical search and data discovery, as well as broad initiatives to enable research IT at federal institutions, biotech and pharma, research hospitals, and academic medical centers. Simon’s practice uses approaches from design and systems thinking combined with a strong emphasis on visual communication to create effective holistic solutions to his client’s BioIT challenges.

Julia Fox is part of the Clinical Data Flow Transformation team in Takeda’s Data Science Institute, where she leads multiple efforts to broadly define and support metadata-driven approaches in Clinical Trial & Data management, in close collaboration with Clinical Sciences, Therapeutic Areas, Information Sciences and across R&D. Julia has a background in developmental genetics, genomics and drug discovery informatics specializing in scientific semantics, data curation and annotation. She will share approaches to developing aligned common data models for institutionally shared metadata object definitions supported by scientific and clinical ontologies. Harmonized metadata and richly annotated data sets accelerate analysis and innovation.

Julie Gorenstein is part of the Clinical Data Systems & Architecture team in the Data Science Institute at Takeda, where she co-leads efforts to streamline data processes and technological pipeline for sample-based, imaging and device clinical data. After building her analytical toolkit while obtaining degrees in Biomedical Engineering and Bioinformatics, Julie focused on target evaluation and molecule identification within oncology R&D, followed by tenure in scientific software development & consulting. She hopes to share her learnings regarding necessity of semantic management of clinical metadata to enable its use in AI/ML.

Samantha Lipsky (she|her) is an Associate Director in the Data Science Institute at Takeda, currently specializing in technical solutions for metadata-driven data harmonization in Clinical Data Sciences. Sam started her career as a Bioengineering postdoc focusing on biomedical microscopy and tissue engineering applications, and later transitioned to the pharma industry as a technical professional with bench expertise. She spent 8 years at AbbVie in Data Solutions and Information Research. Later as a Data Scientist in late-stage development at Biogen, she worked to devise methods to standardize and structure SOP metadata using text mining, an application ontology, and creating a full-stack app. Presently, she provides tools to reinforce data harmonization to scientists to aid in their use of semantics and contextual data management.

Seth Earley is an expert with 20+ years experience in knowledge strategy, information architecture, search-based applications and information findability solutions. He's the author of the award-winning book "The AI Powered Enterprise" and is a sought after speaker, author, and influencer. Recognized by Thinkers 360 as one of the Top 50 Global Thought Leaders and Influencers on Artificial Intelligence 2022.

I am a software engineer by training with a passion for solving complex issues related to manufacturing and research. I love to bring client requirements to life through software and see the impact of their ideas on their fields. I have conducted multiple software projects over the last 10 years ranging from blank sheet customer software to complete validated IT landscape integration projects. My current focus in Roche is around integrating and developing various application and data sources to help our scientist deliver medicine quicker to patients.

I am a product lead at the Science & Research domain of Roche Informatics focused on transforming how science and R&D is done across labs across the word. I am building cutting-edge products at the forefront of technological innovation in Science and Research that are making the Lab of the Future a reality now by working with and guiding cross-functional product teams to translate emerging technology trends and complex R&D challenges into strategic roadmaps, solve customer problems and create a leading product management organization at Roche. I have led the development and scaling of digital products throughout my career as a scientist and product manager. I am passionate about product management, continuous product discovery and leading by outcomes and not outputs. I am also a part-time improviser, plant influencer and a dog person.

Strategic, visionary leader with an established track record of building and leading multidisciplinary, global Informatics and IS/IT teams, driving change and simplification and delivering value through innovation. Over 20 years’ experience in the biotechnology and pharmaceutical industry working in both Discovery and Development leading projects, managing complex portfolios, driving change programs, identifying opportunities for strategic initiatives, and translating scientific and medical questions into innovative solutions. Areas of particular strength include: strategy development and implementation, translational medicine, biomedical and health informatics, evidence-based decision makings, data and decision science, and "Big Data" exploitation.

Dr. Chung is Vice President and Chief Data Office and Director of Data Science Development and Implementation of the Institute for Data Science in Oncology at MD Anderson Cancer Center. She is a clinician-scientist, and associate professor in Radiation Oncology and Diagnostic Imaging with a clinical practice focused on CNS malignancies and a computational imaging lab focused on quantitative imaging and modeling to detect and characterize tumors and toxicities of treatment to enable personalized cancer treatment. Motivated by challenges observed in her own clinical and research pursuits, Dr. Chung has developed and leads institutional efforts to enable quantitative measurements for clinically impactful utilization and interpretation of data through a collaborative team science approach, including the Tumor Measurement Initiative (TMI) at MD Anderson. Internationally, Dr. Chung leads several multidisciplinary efforts to improve the generation and utilization of high-quality, quantitative data to drive research and impact clinical practice, including her role as Vice Chair of the Radiological Society of North America (RSNA) Quantitative Imaging Biomarker Alliance (QIBA), Co-Chair of the Quantitative Imaging for Assessment of Response in Oncology Committee of the International Commission on Radiation Units and Measurements (ICRU) and National Academies of Sciences, Engineering, and Medicine (NASEM)-appointed committee addressing Foundational Research Gaps and Future Directions for Digital Twins. Beyond her clinical, research, and administrative roles, Dr. Chung enjoys serving as an active educator and mentor with a passion to support the growth of diversity, equity, and inclusion in STEM, including her role as Chair of Women in Cancer ( http://www.womenincancer.org/ ), a not-for-profit organization that is committed to advancing cancer care by encouraging the growth, leadership, and connectivity of current and future oncologists, trainees and medical researchers.

Dan Isaacs is Chief Technology Officer of Digital Twin Consortium, where he is responsible for setting the technical direction for the Member Consortium, liaison partnerships and business development support for new memberships. Previously, Dan was Director of Strategic Marketing and Business Development at Xilinx where he was responsible for emerging technologies including AI/Machine Learning, including defining and executing the ecosystem strategy for the Industrial IoT. Prior to joining the Digital Twin Consortium, Dan was responsible for Automotive Business Development focused on Automated Driving and ADAS systems. Dan represented Xilinx to the Industrial Internet Consortium (IIC). He has more than 25 years of experience working in automotive, Mil/Aerospace and consumer-based companies including Ford, NEC, LSI Logic and Hughes Aircraft. An accomplished speaker, Dan has delivered keynotes, presentations and served as panelist and moderator for IIC World Forums, Industrial IOT Global conferences, Embedded World, Embedded Systems, and FPGA Conferences. He is a member of international advisory boards and holds degrees in Computer Engineering: EE from Cal State University, B.S. Geophysics from ASU.

Dr. Eric Stahlberg now directs cancer data science initiatives at the Frederick National Laboratory, having led and launched several initiatives at the lab. He has been instrumental in establishing the Frederick National Laboratory’s high-performance computing initiative and in assembling scientific teams across multiple, complex organizations to advance predictive oncology. Stahlberg first joined the Frederick National Laboratory in 2011 to form and direct the National Cancer Institute’s Center for Cancer Research Bioinformatics Core, which helped build intramural research collaborations between the national laboratory and the National Cancer Institute. Since then, Stahlberg has played a leadership role in many key partnerships, including a major collaboration between the National Cancer Institute and the Department of Energy. Under the Joint Design of Advanced Computing Solutions for Cancer (JDACS4C), the National Cancer Institute and Department of Energy are accelerating progress in precision oncology and computing. The collaboration is rooted in three major national initiatives; the Precision Medicine Initiative, the National Strategic Computing Initiative, and the Cancer Moonshot. He has helped lead initiatives to transform data management approaches at the lab as well as more recently leading program efforts exploring the application biomedical digital twins for cancer applications. Stahlberg has spearheaded the Frederick National Laboratory’s contributions to a number of JDACS4C projects, including ATOM and CANDLE. He helped launch the annual meeting series, Frontiers in Predictive Oncology and Computing, and co-organizes the annual Computational Approaches for Cancer and HPC Applications of Precision Medicine workshops. In 2017, he was recognized as one of FCW‘s Federal 100. Stahlberg holds a Ph.D. in computational chemistry from The Ohio State University.

Mariano Vázquez, Ph.D. MV is co-founder and CTO / CSO of ELEM Biotech and researcher at the Barcelona Supercomputing Center (BSC). ELEM, a spinoff company of the BSC, was born to speeding up the technology transfer from BSC to the biomedical sector, by creating a supercomputer-based and cloud-deployed platform to perform in-silico clinical trials on massive populations of Virtual Humans. Virtual Humans are "avatars", a combination of sophisticate mathematical and computational modelling, and data, designed to predict the outcome of different therapies. Powered by BSC, our team develops tools which allows to study the cardiovascular and respiratory systems, with customers in both the medical devices sector and pharmaceutical industry. Infarction, ageing, damaged cardiac valves, arrhythmias, stent design or respiratory drug delivery are among the topics where such a tool can become a decisive help.

Vincent Beltrani earned his bachelor’s degree in mathematics at Stony Brook University and his PhD in chemistry at Princeton University. Vincent’s research focused on computational chemistry emphasizing electronic structure theory, molecular dynamics, novel imaging techniques, and large-scale HPC calculations. At Google, Vincent has led relationships across the healthcare and life sciences industries helping customers build multi-omics platforms, solve computational drug discovery problems at an ultra-large scale, and implement AI/ML for advancing next stage therapeutics across the drug discovery process.

Rachana Ananthakrishnan is Executive Director & Head of Products at the University of Chicago, and has a Joint Staff Appointment at Argonne National Laboratory. In her role at the university, she leads the Globus (www.globus.org) department, which delivers a research IT platform to national and international research institutions. She currently serves on the Internet2 InCommon Steering Committee, Earth System Grid Federation Executive Committee and Scientific Advisory Board for National Microbiome Data Collaborative. Her work is focused on cyberinfrastructure for enabling research across a variety of domains, and she has led security and data management for several NSF, DOE, and NIH funded initiatives. Rachana was a member of the Globus Toolkit engineering team and customer engagement teams, leading the efforts in web services and security technologies. Rachana received her MS in Computer Science at Indiana University, Bloomington.

Brigitte Raumann is a Product Manager at Globus and led the effort to enable Globus support for management of protected research data, including PHI and CUI. As the Globus Privacy Officer, she continues to oversee the Globus compliance program and incident investigations. Brigitte has focused her career on providing researchers with the software tools and data they require to advance discovery. Her decades of experience span sectors as diverse as biotech, publishing, patent law, and academic clinical research. Brigitte Raumann earned her B.A. from the University of California, Berkeley and her Ph.D. in biochemistry from the Massachusetts Institute of Technology.

Vas leads the customer team for Globus, an innovative software-as-a-service for research data management, developed and operated by the University of Chicago. He works with current and prospective users to grow adoption of the service and make it self-sustaining. Vas is also a lecturer in the Master's Program in Computer Science, where he teaches courses on Cloud Computing and Product Management. Vas has 30 years of experience in operational and consulting roles, spanning strategy, marketing, and technology. He has nurtured early-stage companies into successful businesses and consulted with companies on a wide range of strategic issues. Vas holds an MBA from the Ross School of Business at the University of Michigan, Ann Arbor, and a BS in Electrical Engineering from the University of the Witwatersrand in South Africa.