ワークショップ | 23rd Bio-IT World Conference & Expo 2024 公式サイト

2024年4月15日（月）8:00 - 10:00 am

W1: Generative AI 101: Demystifying for Drug Discovery Research

This workshop offers a fundamental understanding of generative AI, along with key concepts and technologies. We will delve into essential topics like variational autoencoders, generative adversarial networks, transformer fundamentals, and the significance of large language models within the context of drug discovery in the chatGPT era. The objective is to provide attendees with the essential knowledge and skills required to effectively utilize generative AI in the realm of biomedical research.

Parthiban Srinivasan, PhD, Professor, Data Science and Engineering, Indian Institute of Science Education and Research, Bhopal

8:00 am

Generative AI 101: Demystifying for Drug Discovery Research

Parthiban Srinivasan, PhD, Professor, Data Science and Engineering, Indian Institute of Science Education and Research, Bhopal

INSTRUCTOR BIOGRAPHIES:

Parthiban Srinivasan, PhD, Professor, Data Science and Engineering, Indian Institute of Science Education and Research, Bhopal

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.

W2: Data Science in Practice: Embracing the Challenges, Unleashing the Possibilities

To accelerate scientific discovery, many systems need to be in place, including traditional bioIT systems (e.g., HPC systems, national network systems, cloud computing systems, data management systems) to other types of complex systems (e.g., software, organizations, policies, and procedures, and data ecosystems). A key factor in the success of these systems is designing for change-achieving change and accommodating change. This workshop shares best-practice approaches to solving complex technology and data science problems that slow scientific research. Use cases will be shared along with tips and best practices to implement.

Ari E. Berman, PhD, CEO, BioTeam, Inc.

Simon Twigger, PhD, Principal Consultant, BioTeam, Inc.

8:00 am

Data Science in Practice: Embracing the Challenges, Unleashing the Possibilities

Ari E. Berman, PhD, CEO, BioTeam, Inc.

Simon Twigger, PhD, Principal Consultant, BioTeam, Inc.

INSTRUCTOR BIOGRAPHIES:

Ari E. Berman, PhD, CEO, BioTeam, Inc.

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 Twigger, PhD, Principal Consultant, BioTeam, Inc.

Simon specializes in building software that is actually useable by scientists. Formerly an Assistant Professor working in the areas of Genomics and Biotechnology, he joined BioTeam in 2013. Since then, he has continued his focus on harnessing the cloud to build software tools for scientists while also embracing the power of DevOps to create the dynamic computing architectures needed for modern informatics. Simon has a Ph.D. in Biochemistry from the University of Nottingham in the UK and worked on Ubiquitin and related proteins for his postdoctoral work at the Medical College of Wisconsin in Milwaukee. His growing interest in software development led him into bioinformatics and he joined Prof. Howard Jacob’s group at the Medical College developing software for genomic mapping projects and became a faculty member in 2001. His research focused around genomics and genome databases. He was a principle investigator on a number of prominent bioinformatic projects-the Generic Model Organism Database (GMOD), the Rat Genome Database, the Gene Ontology Consortium, the National Center for Biomedical Ontology-along with directing the bioinformatics components for the MCW NHLBI National Proteomics Center and the MCW Center of Excellence in Genomics Science. His research group focused on promoting emerging software development tools such as Ruby on Rails and cloud computing and his group published the first example of a cloud-based analysis platform for proteomics in 2009. For three years prior to leaving MCW in 2011, he was the Biomedical Informatics Key Function Director for the MCW’s CTSA center, the South Eastern Wisconsin Clinical and Translational Science Institute.

W3: Semantic Management Technologies and Processes: An Agile Framework to Enable Innovation

In this workshop, we will focus on holistic integration of data ecosystems by leveraging semantic management to support information sharing and data harmonization and to accelerate improved decision-making. We will explore key prerequisites for analysis and reporting such as data and semantic modeling, ontologies and ontology engineering, integration of ontologies into data models and schema, coordination of use via system-level integration, and delivery of fit-for-purpose point-of-service processes and applications. Semantic management elevates the ecosystem and makes more data available to machine learning and AI development. We will highlight examples of hands-on applications in life sciences informatics workflows such as biomarker data harmonization and clinical trial data flow.

Bimjhana Bishwokarma, MS, ALM, Senior Business Analyst, Takeda Pharmaceuticals

Julia Fox, PhD, Director, Takeda Data Sciences Institute

Julie Gorenstein, Director, Takeda Data Sciences Institute

Samantha Lipsky, Associate Director, Systems & Architecture, Takeda

8:00 am

Semantic Management Technologies and Processes: An Agile Framework to Enable Innovation

Bimjhana Bishwokarma, MS, ALM, Senior Business Analyst, Takeda Pharmaceuticals

Julia Fox, PhD, Director, Takeda Data Sciences Institute

Julie Gorenstein, Director, Takeda Data Sciences Institute

Samantha Lipsky, Associate Director, Systems & Architecture, Takeda

INSTRUCTOR BIOGRAPHIES:

Bimjhana Bishwokarma, MS, ALM, Senior Business Analyst, Takeda Pharmaceuticals

As a Business Analyst in Clinical Data Flow Transformation team within Takeda’s Data Science Institute, Bimjhana Bishwokarma leads use case metadata curation & validation, and cross-system metadata alignment. She contributes to ensuring study-level metadata integrity, facilitating establishment of R&D Ontology, and supporting metadata-driven approaches in collaboration with Clinical Sciences, Therapeutic Areas, and Information Sciences across R&D. Bimjhana leverages her scientific expertise in Immuno-Oncology, Tissue Engineering, and Translational Science to bridge the gap between complex Clinical Trial data and meaningful insights.

Julia Fox, PhD, Director, Takeda Data Sciences Institute

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, Director, Takeda Data Sciences Institute

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, Associate Director, Systems & Architecture, Takeda

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.

2024年4月15日（月）10:30 - 12:30 pm

W4: Large Language Models and Their Practical Applications within Novartis: Best Practices and Use Cases

This workshop aims to present state-of-the-art achievements, capabilities and limitations of Large Language Models (LLMs), and explores range of their practical applications, revealing their transformative potential in the dynamic realm of pharmaceuticals. Join us as we delve into practical use cases, showcasing the profound impact of these models on knowledge building, advancing scientific discovery, processes automation and enhancing communication within Novartis and beyond.

Rishi R. Gupta, PhD, Associate Director, Data Science, Novartis Institutes for Biomedical Research, Inc.

Hubert Misztela, Director, Data Science, AI Researcher, Novartis Institute for Biomedical Research, Inc.

10:30 am

Large Language Models and Their Practical Applications within Novartis: Best Practices and Use Cases

Rishi R. Gupta, PhD, Associate Director, Data Science, Novartis Institutes for Biomedical Research, Inc.

Hubert Misztela, Director, Data Science, AI Researcher, Novartis Institute for Biomedical Research, Inc.

INSTRUCTOR BIOGRAPHIES:

Rishi R. Gupta, PhD, Associate Director, Data Science, Novartis Institutes for Biomedical Research, Inc.

Rishi has over 15yrs of experience in Pharma in various capacities. He is currently an Associate Director within the GDC/CADD group at Novartis Institutes for Biomedical Research, at Cambridge, MA. He is leading several efforts in developing and applying cheminformatics, data science, AI/ML and molecular modeling methods for advancing drug discovery and development. Prior to Novartis, Rishi was at AbbVie where he led the Data Science and Informatics group. At AbbVie, he conceptualized and developed a web-based infrastructure to expose suite of Cheminformatics tools called AIDEAS. He developed and deployed machine-learning models for a variety of bioassay data including ADMET endpoints. In his extended role within Competitive Intelligence (CI), Rishi developed web based visual-analytics for several organizations.

Hubert Misztela, Director, Data Science, AI Researcher, Novartis Institute for Biomedical Research, Inc.

With over a decade of experience spanning from programming and research up to business stakeholder management, he has demonstrated proficiency in delivering complex solutions in artificial intelligence, software development, and applied mathematics. His expertise extends across a variety of sectors, including pharmaceuticals, high-tech, government, and education. During his recent five-year tenure at Novartis, he made significant strides. Initially, he focused on optimizing commercial activities through AI applications, collaborating closely with the European leadership team. In the following three years, he played a pivotal role in the development of AI solutions for small molecule design, partnering with numerous teams across the company and with Microsoft Research.

W5: Digitalization of Pharma R&D-Master the Marathon

The digitalization of pharma R&D is not a sprint but a marathon with unique challenges, many pitfalls, and unforeseen side effects. The conversion of healthcare and technology promises game-changing breakthroughs and high rewards and makes the successful digitalization an absolute necessity for tomorrow's R&D organizations. This workshop will showcase the digitalization journey of a pharma R&D organization and critically discuss its setup and impact to increase R&D productivity.

Matthieu Croissant, Senior Solution Architect, Roche Pharma

Fabia Fricke, PhD, Pharma Research, Data & Analytics, Roche

Pedro Ivo Guimarães, PhD, Senior Scientist and Product Manager, Roche

10:30 am

Digitalization of Pharma R&D-Master the Marathon

Matthieu Croissant, Senior Solution Architect, Roche Pharma

Fabia Fricke, PhD, Pharma Research, Data & Analytics, Roche

Pedro Ivo Guimarães, PhD, Senior Scientist and Product Manager, Roche

INSTRUCTOR BIOGRAPHIES:

Matthieu Croissant, Senior Solution Architect, Roche Pharma

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.

Fabia Fricke, PhD, Pharma Research, Data & Analytics, Roche

Pedro Ivo Guimarães, PhD, Senior Scientist and Product Manager, Roche

My name is Pedro Ivo Guimarães (he/him) and I am a senior scientist and product manager at Roche's Data & Analytics Data Products & Platforms team. My goal is to transform how science is done at Roche's pharmaceutical research and early development (pRED) laboratories across the world. Since I joined Roche's Data & Analytics team a few years ago, I have worked on and led several digital lab automation projects and initiatives that are accelerating pRED's journey towards data-driven drug discovery. I am currently the product manager of a global digital lab automation platform that allows pRED scientists worldwide to build and share digital twins of lab workflows and automate several data processing and system integration steps. I believe that the boundaries between the physical and digital realms of science are almost non-existent in a modern laboratory environment so a human-centered digitalization process is essential to achieve the Lab of the Future dream. I am passionate about product work, so I am an advocate for good product management practices, continuous product discovery, and leading by outcomes and not outputs. I have a Bachelor's degree in Biotechnology from Universidade Federal do Pará (Belém, PA, Brazil) and a PhD degree in Biological Systems Engineering from Virginia Tech (USA). I am also an improv theater performer and director, a plant parent, a musician, and a dog person.

W6: Biomedical Digital Twins

With the successful and growing use of digital twin approaches in established industries such as power, propulsion, and aerospace combined with a rapidly developing biomedical ecosystem of computing, modeling, and expanding data has opened the door to develop the role of digital twins in biomedical applications. The workshop will bring together leaders in the use of digital twins and biomedical applications to provide key insights into launching digital twin efforts, factors influencing the present environment, challenges and opportunities expected along the way, and broader questions shaping the future for digital twins in biomedical applications.

Caroline Chung, MD, MSc, FRCPC, CIP, Vice President, Chief Data Officer, Director of Data Science Development & Implementation, Institute for Data Science in Oncology, MD Anderson Cancer Center

Dan Isaacs, CTO, Digital Twin Consortium

Kerstin Kleese van Dam, Director Computational Science Initiative, Brookhaven National Laboratory

Eric Stahlberg, PhD, Director, Cancer Data Science Initiatives, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Rockville, Maryland, USA

Mariano Vazquez, PhD, Co-Founder and CTO, ELEM Biotech, Barcelona, Spain

10:30 am

Biomedical Digital Twins

Caroline Chung, MD, MSc, FRCPC, CIP, Vice President, Chief Data Officer, Director of Data Science Development & Implementation, Institute for Data Science in Oncology, MD Anderson Cancer Center

Dan Isaacs, CTO, Digital Twin Consortium

Kerstin Kleese van Dam, Director Computational Science Initiative, Brookhaven National Laboratory

Eric Stahlberg, PhD, Director, Cancer Data Science Initiatives, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Rockville, Maryland, USA

Mariano Vazquez, PhD, Co-Founder and CTO, ELEM Biotech, Barcelona, Spain

INSTRUCTOR BIOGRAPHIES:

Caroline Chung, MD, MSc, FRCPC, CIP, Vice President, Chief Data Officer, Director of Data Science Development & Implementation, Institute for Data Science in Oncology, MD Anderson Cancer Center

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, CTO, Digital Twin Consortium

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.

Kerstin Kleese van Dam, Director Computational Science Initiative, Brookhaven National Laboratory

Kerstin Kleese van Dam (2018 Woman of the Year Award in Science winner Brookhaven Town, 2006 British Female Innovators and Inventors Silver Award) is the Director of the Computational Science Initiative at Brookhaven National Laboratory in the USA, leading BNL's computer science and mathematics R&D portfolio reaching from leading edge research to operational infrastructure provision. CSI research focuses on data analytics @ scale - novel hardware to new AI methods for science, exascale computational modeling and quantum information science - quantum networking to optimized quantum algorithms for high energy, nuclear and condensed matter physics. We have a new, state of the art data center opened in 2021, that provides leading edge data storage and analysis capabilities.

Eric Stahlberg, PhD, Director, Cancer Data Science Initiatives, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Rockville, Maryland, USA

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 Vazquez, PhD, Co-Founder and CTO, ELEM Biotech, Barcelona, Spain

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.

2024年4月15日（月）2:00 - 4:00 pm

W7: Unlocking the Power of Data & AI for Drug Discovery

In the realm of drug discovery, the power of data and artificial intelligence (AI) is revolutionizing the way we identify, develop, and bring new therapies to patients. This transformative approach is opening up a world of possibilities, accelerating the pace of drug discovery and leading to the creation of more effective and personalized treatments. In this workshop, you'll learn how pharmaceutical and biotech organizations are reimagining R&D by combining leading AI technologies with Google Cloud's scalable and secure infrastructure to accelerate: data harmonization & knowledge extraction, small molecule drug discovery, macromolecule analysis & design and genomics and biomarker discovery. Join us in this exciting journey as we unlock the power of data and AI for drug discovery.

Vincent J. Beltrani, PhD, Life Sciences Specialist, Google Cloud

2:00 pm

Unlocking the Power of Data & AI for Drug Discovery

Vincent J. Beltrani, PhD, Life Sciences Specialist, Google Cloud

INSTRUCTOR BIOGRAPHIES:

Vincent J. Beltrani, PhD, Life Sciences Specialist, Google Cloud

W8: Instrument-Driven Discovery for the 99%: Modern Infrastructure for Research

Instruments including cryo-EM systems, light sheet microscopes, gene sequencers, and X-ray beam lines play a critical role in biomedical research, where discovery is driven by analysis of increasingly large datasets. Managing the data generated by these instruments is complicated and time-consuming, presenting challenges for the facilities that operate the instruments and researchers who use them. The common need is end-to-end solutions that streamline data management throughout the research data lifecycle.

Rachana Ananthakrishnan, Executive Director, Globus, University of Chicago

Vas Vasiliadis, Chief Customer Officer, Globus, University of Chicago

2:00 pm

Instrument-Driven Discovery for the 99%: Modern Infrastructure for Research

Rachana Ananthakrishnan, Executive Director, Globus, University of Chicago

Vas Vasiliadis, Chief Customer Officer, Globus, University of Chicago

INSTRUCTOR BIOGRAPHIES:

Rachana Ananthakrishnan, Executive Director, Globus, University of Chicago

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 Globus (www.globus.org) department, which delivers research data management services and platform to national and international research institutions. She also serves on the WestGrid Board of Directors, and is a member of the Internet2 InCommon Steering Committee. Her work is focused on research and education field, and she has worked on security and data management solutions on various projects including Earth System Grid (ESG), Biomedical Informatics Research Network (BIRN), and Extreme Science and Engineering Discovery Environment (XSEDE). Prior to that she worked on 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.

Vas Vasiliadis, Chief Customer Officer, Globus, University of Chicago

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.