David Talby

CTO

David Talby is the Chief Technology Officer at John Snow Labs, helping companies apply artificial intelligence to solve real-world problems in healthcare and life science. David is the creator of Spark NLP – the world’s most widely used natural language processing library in the enterprise. He has extensive experience building and running web-scale software platforms and teams – in startups, for Microsoft’s Bing in the US and Europe, and to scale Amazon’s financial systems in Seattle and the UK. David holds a Ph.D. in Computer Science and Master’s degrees in both Computer Science and Business Administration. He was named USA CTO of the Year by the Global 100 Awards and Game Changers Awards in 2022.

Veysel Kocaman

Head of Data Science at John Snow Labs

Veysel is a Lead Data Scientist and ML Engineer at John Snow Labs, improving the Spark NLP for the Healthcare library and delivering hands-on projects in Healthcare and Life Science. He is a seasoned data scientist with a strong background in every aspect of data science including machine learning, artificial intelligence, and big data with over ten years of experience. He’s also pursuing his Ph.D. in ML at Leiden University, Netherlands, and delivers graduate-level lectures in ML and Distributed Data Processing. Veysel has broad consulting experience in Statistics, Data Science, Software Architecture, DevOps, Machine Learning, and AI to several start-ups, boot camps, and companies around the globe. He also speaks at Data Science & AI events, conferences and workshops, and has delivered more than a hundred talks at international as well as national conferences and meetups.

Shay Sayed

Principle Solutions Engineer at ClosedLoop

Shay Sayed is the Principal Solutions Engineer at ClosedLoop, where he collaborates with health systems and payers to prototype analytical solutions that improve both clinical and administrative processes. Prior to this, he worked in the high-fashion space as well as the finance industry, incorporating machine learning to innovative products. Outside the office, he enjoys reaading about the history of US healthcare and listening to behavioral science podcasts.

Christine Swisher

Chief Scientific Officer Project Ronin

Christine Swisher is Chief Scientific Officer at Project Ronin leading multidisciplinary teams of data scientists, statisticians, informaticists, and machine learning experts to build technologies that solve challenging clinical problems. Together, they have delivered safe and ethical artificial intelligence-based that personalize key clinical decisions, NLP and generative AI innovations, and demonstrated causal impact on clinical and institutional outcomes with the use of the Ronin platform. Before joining Ronin, she spearheaded several FDA-cleared AI-based products, CLIA LDTs, and other clinical decision support/AI capabilities across the ML lifespan and led analytics functions. She is an advocate and champion for Responsible AI and holds over 20 patents in machine learning and AI. Prior to working for Fortune 500, fast growth companies, and startups, she completed her PhD in biomedical engineering with an emphasis on computer science jointly at Berkeley and UCSF and continued her academic career at Harvard Medical School and MGH.

Harsha Gurulingappa

Head of Text Analytics Merck Group

Dr. Harsha Gurulingappa is a part of Merck Data Office within Merck Group, a leading science, and technology company in the area of Healthcare, Life Science, and Electronics businesses. He works as Head of Text Analytics group responsible to drive development and adoption of practices leveraging text analytics and natural language processing across organizational sectors. He did his Ph.D. in the area of biomedical text mining and has over a decade of dedicated experience in both research and production implementation of text analytics solutions for various business domains.

Alberto Oteo Garcia

Data Scientist Merck Group

Alberto works as a Senior Data Scientist at Merck KGaA within Merck Group Functions with an academic background in Mathematics and Artificial Intelligence. Alberto has worked in various fields such as finance working on the Spanish and Swiss stock exchange or healthcare as a lecturer and data scientist at the University of Valencia. He is responsible for the Data Science aspects of CONAN

Luis Gehrmann

Data and Analytics Architect at Merck Group

As a corporate student at Merck KGaA, Luis collected experience in the fields of Cloud Engineering and AI. With the academic background of business informatics, Luis Gehrmann is working as a Data Architect on solution design and architecture of applications. He is responsible for the CONAN infrastructure configured inside AWS.

Itay Zitvar

Software engineering team lead (NLP) Hyro

A language enthusiast. Served as an officer in an elite intelligence unit in the IDF and studied computer science and linguistics in Tel Aviv university. For the past few years, Itay has been leading the the effort in Hyro of developing engaging, goal-oriented conversational AI for enterprise healthcare organizations across the US.

Durga Borkar MD, MMCi

Medical Advisor Verana Health

Durga Borkar, MD, MMCi, is a medical advisor at Verana Health. She also serves as an assistant professor of ophthalmology at Duke University School of Medicine and is a board-certified, fellowship-trained adult vitreoretinal surgeon at Duke University Eye Center, as well as a board-certified clinical informaticist. In her role at Verana Health, Dr. Borkar advises on ophthalmology clinical strategy and leads real-world evidence-based (RWE) research studies utilizing curated real-world data from the American Academy of Ophthalmology IRIS® Registry (Intelligent Research in Sight) to better understand patient experiences and clinical outcomes

Romain Bogaerts

Director of AI Product Management Real Chemistry

Romain Bogaerts is Director of AI Product Management at Real Chemistry. His team develops AI algorithms that empower the creative human ideas from the agency to become exponentially more insightful with Data and AI solutions. Romain leads the design and development of advanced new products that use Machine Learning and AI to help clients optimize their field force and implement marketing segmentation and targeting. The Real Chemistry teams also use NLP to understand complex patient journeys and the sentiment associated with navigating the health system. Prior to his current position, Romain led a team at CVS Health that created an AI-enhanced experience for in-store pharmacists by generating real-time alerts for patient safety, drug pricing, and insurance claims.

Pavithra Rajendran

Senior Data Scientist at Great Ormond Street Hospital NHS Trust

Pavithra Rajendran is a Senior Data Scientist and NLP Technical Lead in the DRE team within GOSH and has around 7 years of academic and commercial experience as an NLP (Natural Language Processing) specialist. Previously, worked at KPMG UK as an NLP data scientist and has experience using both traditional and deep learning-based NLP techniques for various client projects in both public and private sectors, from Proof-of-Concept to Production (Healthcare, Oil and Gas, Travel, Finance etc.) and, translating academic knowledge/research for commercial settings as well as latest commercial technologies by identifying the gaps and presenting with appropriate solutions for the business problems. She holds a Masters in Advanced Computing (Machine Learning, Data Mining and High Performance Computing) and a PhD in Computer Science (Natural Language Processing).

Stephanie Grim

Health Care Researcher at University of Colorado

Stephanie is a health researcher at University of Colorado. She specializes in the use of predictive analytics and language processing techniques to solve modern healthcare problems. Stephanie has received two Master’s Degrees from the University of Colorado. The first in Business Analytics with a specialization in Big Data Techniques received in 2018 followed by Applied Biostatistics MS in 2021. She uses this combined skillset to apply a breadth of inferential, predictive and prescriptive analysis to inform and develop meaningful telehealth policies and interventions.

Dr. Gary Curhan

CMO at OM1

Dr. Gary Curhan is the CMO at OM1, Inc. He is a practicing nephrologist in Boston. He has published widely on the epidemiology of many medical conditions including cardiovascular disease, hypertension, kidney stones, gout, hearing loss and others. His research in several large cohort studies, including the Nurses’ Health Studies and the Health Professionals Follow- Up Study, focuses on the prevention of common diseases by investigating scientifically and clinically important questions and exploring the role of modifiable factors and has been supported continuously for over 25 years by the National Institutes of Health. He was the Editor-in-Chief of the Clinical Journal of the American Society of Nephrology, a leading nephrology journal. He has served on many national and international advisory committees, including the National Institutes of Health. He has mentored numerous individuals, many of whom now hold leadership positions at major academic institutions and public companies. Dr. Curhan is a graduate of Harvard Medical School and Harvard School of Public Health. Prior to joining OM1, he was a Professor of Medicine at Harvard Medical School and Professor of Epidemiology at Harvard School of Public Health.

Ryan Boch

Senior Software Engineer at OM1

Ryan Boch is a Senior Software Engineer at OM1 and part of the greater Text Intelligence Team. Ryan has 10 years’ experience in analytics spending time as a Data Analyst and Data Scientist at Oracle Cerner before joining OM1. Ryan has experience across a broad spectrum of analytics including natural language processing. At OM1, Ryan focuses on creating solutions to solve large scale complex NLP problems for text extraction and pattern recognition as well as maintaining the internal text extraction platform. Ryan graduated from the University of Kansas with a BS in Mathematics and a MS in Applied Statistics.

Nafiseh Mollaei

Postdoc at Loyola University Chicago

Dr. Nafiseh Mollaei is a Postdoc Research Associate in the Department of Health Informatics and Data Science in the Center for Health Outcomes and Informatics Research at Loyola University Chicago. Dr. Mollaei received her PhD in Biomedical Engineering from NOVA University of Lisbon (Portugal) in 2022. Prior to joining Loyola, she was Research Assistant in the Department of Medical Department in VolkswagenAutoeuropa in Portugal for 4 years. Dr. Mollaei’s research generally lies in the intersection of decision science and artificial intelligence (AI), which furthers knowledge of monitoring of and predictive analytics for healthcare systems. In the past few years, Dr. Mollaei has been working on designing AI-based models in critical care.

Sonali Tamhankar

Senior Clinical Data Scientist Fred Hutch Cancer Center

Sonali is an innately curious deep thinker who has the hands-on expertise to productize her ideas. She runs a meetup called Destination Health Equity, works as a data scientist in healthcare, has been actively involved in non-profit governance, was a tenure-track physics professor, and writes poems combining technical physics concepts with life philosophy. She is happiest working with whip smart people passionate about understanding and appreciating this magical world and making a positive difference.

Harvey Castro

Author of ChatGPT Healthcare

As a physician, healthcare consultant, and serial entrepreneur, my career has promoted digital health awareness and instigated positive changes. My journey spans various roles, including serving as a CEO, practicing physician, and medical correspondent for major media outlets (Fox News, NBC, and Telemundo). I am known for my innovative thinking and proven track record in creating impactful healthcare solutions. This includes developing several healthcare apps and consulting for numerous healthcare organizations. My written contributions are multiple, appearing in medical publications and my books. I am the author of the book series “Chat GPT Healthcare,” available on Amazon. These volumes encapsulate my rich insights and experiences within the healthcare industry, providing practical guidance for aspiring professionals. My plans involve joining a corporate board where I can lend my expertise to support the growth and success of the organization. As an international public speaker, I’ve had the opportunity to share my knowledge at various prestigious events, including: Keynote Speaker at the Healthcare Information and Management Systems Society (HIMSS) Speaker at AI MED Speaker at various conferences in Germany and Australia Through my work, I strive to inspire and assist individuals and organizations in their journey to succeed in healthcare and digital health. I believe in the power of reinvention and invite you to join me on this journey. Please visit my website for more information about my work and how you can get involved. This summary integrates your extensive experience, achievements as a healthcare professional and entrepreneur, writing accomplishments, and ambition to join a corporate board. It acknowledges your keynote and other speaking engagements and invites readers to join you in your mission to innovate and succeed in digital health.

Yizhen Zhong

ML Scientist at Freenome

Yizhen’ work at Freenome centers around the development of a multi-omics machine learning model for early cancer detection through liquid biopsy. Furthermore, she conducts research on NLP methods and infrastructure to leverage real-world data for enhancing cancer screening. She earned her PhD in Biomedical Informatics from Northwestern in 2020. Her doctoral research concentrated on creating novel computational methods to investigate pharmacogenomics in African Americans. She served on the student editorial board for JAMIA from 2019-2020. She is passionated about application of AI methods to reduce health disparities.

Dia Trambitas

Head of Product at John Snow Labs

Dia Trambitas is a computer scientist with a specialized focus on Natural Language Processing (NLP). Serving as the Head of Product at John Snow Labs, Dia oversees the evolution of the NLP Lab, the best-in-class tool for text and image annotation in the healthcare domain. Dia holds a Ph.D. in Computer Science focused on Semantic Web and ontology-based reasoning. She has a vivid interest in text processing and data extraction from unstructured documents, a subject she has been working on for the last decade. Professionally, Dia has been involved in various information extraction and data science projects across sectors such as Finance, Investment Banking, Life Science, and Healthcare. Her comprehensive experience and knowledge in the field position her as a competent figure in the realms of NLP and Data Science.

Ke Ji

Senior Lead Data Scientist at American Family Insurance

Meet Ke, Senior Lead Data Scientist at American Family Insurance, driven by a passion for crafting transformative data-driven solutions that fuel technical innovation and business growth. She plays a vital role in shaping the technical strategies and cultivating innovation within the data science and engineering team, guiding the design and execution of AI solutions that bridge short-term business needs with long-term vision. With over 7 years of data science mastery, Ke’s journey is marked by her innate ability to unravel data-driven complexities, formulate robust data science strategies, and build scalable end-to-end ML applications tailored for production in insurance business. Holding a Master’s degree in Statistics from UIUC and a B.S. in Statistics from Renmin University in China, her proficiency spans machine learning model development, predictive analytics, advanced statistics, ingenious problem-solving for intricate business challenges, and particularly shines in the realm of Natural Language Processing.

Matthew Robinson

Engineering Lead at Unstructured Technologies

Vice President – Data Science responsible for defining, leading and evangelizing analytics solutions leveraging Data Science offerings. Directing end-to-end model development and deployment lifecycle, accomplishing mission-critical user-centric deliveries using Scrum methodology to write succinct user stories or epics in agile framework. I deliver thought leadership and innovation in process, technique, and implementation.

Aayush Mudgal

Senior Machine Learning Lead at Pinterest

Aayush Mudgal is a Senior Machine Learning Engineer at Pinterest, currently leading the efforts around Privacy Aware Conversion Modeling. He has a successful track record of starting and executing 0 to 1 projects, including conversion optimization, video ads ranking, landing page optimization, and evolving the ads ranking from GBDT to DNN stack. His expertise is in large-scale recommendation systems, personalization, and ads marketplaces. Before entering the industry, Aayush conducted research on intelligent tutoring systems, developing data-driven feedback to aid students in learning computer programming. He holds a Master’s in Computer Science from Columbia University and a Bachelor of Technology in Computer Science from Indian Institute of Technology Kanpur.

Lovedeep Saini

Data Science Manager at Arthur J Gallagher

Lovedeep Saini, Ph.D., has over 15+ years of experience in data science and analytics. She is passionate about machine learning and AI-driven innovations that help businesses to grow and improve their outcomes. She leads leveraging large datasets to develop predictive models and other insights to solve challenging, high profile business problems. Lovedeep has been with Gallagher since July 2018 and holds a PhD in experimental high energy physics. Prior to joining Gallagher, she was a particle physicist in academia, where she co-discovered Higgs boson and measured properties of several other exotic physics phenomena like extra dimensions and dark-matter; using statistical and machine learning techniques. Having been trained at Large Hadron Collider, arguably the biggest scientific experiment of human history – she brings to the table a taste for problem solving, natural curiosity and excellent background in computer programming, statistics, probability and research management. Outside work, she is a marathon runner and enjoys spending time reading and hiking with audiobooks and podcasts.

Dishant Banga

Sr Data Analyst at Bridgetree

Dishant Banga received his bachelor’s degree in Mechanical and Automation Engineering from Guru Gobind Singh Indraprastha University, Delhi, India in 2014 and Master’s in systems Engineering and Engineering Management with specialization in Data Analytics/ Data Science from the University of North Carolina, Charlotte in 2018. His interest includes applications of Machine Learning and Data Science to solve complex business problems. He has participated in various national and international level competitions and secured good rank by developing solutions for complex business problems. Currently, he is working as a Sr. analyst at Bridgetree, LLC. His research interests include developing statistical and machine learning models and applications, artificial intelligence

Fatema Nafa

Professor at Salem State University

I am a data scientist researcher who examines how to design and exploit algorithms to study time series datasets. I am committed to using my love and talent for teaching and research to empower others through education to make a difference in the world. Inspiring and motivating students by providing a thorough understanding of a variety of computer and data science technology concepts, subjects, and current research issues. I offer a demonstrated history of successfully implementing technology-driven learning tools and assessment methods. My current research interests are broad and varied, but generally fall into Machine Learning, Data Visualization, and large natural language models.

Vipul Raheja

Applied Research Scientist at Grammarly

Vipul Raheja is an Applied Research Scientist at Grammarly. He works on developing robust and scalable approaches centered around improving the quality of written communication, leveraging Natural Language Processing and Machine Learning. His research interests lie at the intersection of large language models and controllable text generation methods for text revision. He has authored multiple papers at top-tier NLP conferences such as ACL, NAACL, and EMNLP. He also co-organizes the Workshop on Intelligent and Interactive Writing Assistants (In2Writing).

Neelesh Shukla

Senior Manager – Principal AI Scientist at State Street Corporation

Neelesh is current working as Principal Scientist at State Street. He leads the AI Research and Innovation for Financial Use cases. His primary research area is NLP, FinNLP, Visual NLP and LLMs.

Michelle Banawan

Asst. Professor and Academic Program Director at Asian Institute of Management

Michelle Banawan, Ph.D. is an Asst. Professor at the Asian Institute of Management. She conducted her postdoctoral research at the Science of Learning and Educational Technology (SOLET) laboratory headed by Dr. Danielle McNamara of the Department of Psychology, Arizona State University from 2019 to 2022. Her specializations include Natural Language Processing (NLP) and Machine Learning. Her postdoc work is focused on the application of machine learning algorithms, computational linguistics and natural language processing to various components of the SOLET lab projects within the contexts of reading comprehension and writing proficiency studies. She also handles data curation, data wrangling and database management which entails writing queries to address the different data requirements of projects. She also participates in the design of intelligent tutoring systems and educational games. Her specialization and skills include data and database management, design, analysis, and visualization. The data science and machine learning tools that she is proficient on include MySQL, Python, and R. She has also more than ten years of experience in information systems analysis and design, business requirements modeling, human computer interaction, user-centered design, and systems documentation.

Zongrui Pei

Senior Staff at New York University

Dr. Pei is a senior staff at the supercomputing center of New York University, focusing on various computational materials topics, particularly those related to first-principles calculations and machine learning (include natural language processing).

Miguel Ángel Rodríguez López

Data & AI Manager at Digital Hub Acciona

Miguel Ángel Rodríguez has advanced his career in parallel with continuous learning, becoming an expert in digital transformation, data science, and artificial intelligence. He holds two PhD: the first in industrial engineering, where he developed complex neural network models for predictive maintenance; and a second PhD in Economics, where he applied advanced data science analytics and optimization techniques to design energy scenarios. Professionally, he has spent much of his career at Iberdrola, where he led significant data-driven projects for the company. He also played a crucial role at Acciona, where he currently leads the data analytics and artificial intelligence team at the Digital Innovation Hub. In this role, they embark on innovative projects involving generative AI, NLP, predictive models, computer vision, and more for the entire company.

Divya Mereddy

Data Scientist at Ascena Retail

Divya is a Data Scientist at Ascena Retail (Ann Taylor, LOFT, and Lou & Grey, Lane Bryant and Cacique). She has completed her Masters from the University of Cincinnati. Her research goal is to make the world around her a better place to live. She is interested in Vision, Cognition, Learning, and Autonomy, link: https://sites.google.com/prod/view/divyamereddy

Jennifer D’Souza

Postdoctoral researcher at TIB – Leibniz Information Center for Science and Technology

Jennifer D’Souza works as a postdoctoral researcher on the Open Research Knowledge Graph (ORKG) project. There she leads the NLP services development and heads the junior AI research group SCINEXT investigating neural-symbolic AI methods for scholarly knowledge extraction and semantification.

Yuval Belfer

Developer Advocate at AI21 Labs

Yuval’s professional passion lies in the realm of generative AI. He actively contributes to making this intricate field more comprehensible and accessible to diverse audiences. With an engaging style and in-depth expertise, he navigates the complexities of AI, bringing clarity and insight to both peers and newcomers in the field.

John Bauer

Research Engineer at Stanford

John Bauer is a software engineer working with the NLP research group at Stanford. He has been an author on several NLP papers, including the widely used CoreNLP software package, and is currently maintaining Stanford’s Stanza software package.

Chreston Miller PhD

Assistant Professor at Virginia Tech

Dr. Miller is currently an assistant professor and the Data and Informatics Consultant within Data Services of the University Libraries at Virginia Tech. He provides consulting services for researchers at Virginia Tech centered around data-related challenges. His focus has been in Machine Learning/Deep Learning but supports a wide array of data-related areas such as data wrangling and data sensemaking. Dr. Miller’s current research interests are Applied Machine Learning, specifically Natural Language Processing, Human Behavior Analysis, and Human-Centered Computing.

Swagata Ashwani

Data Science Lead at Boomi

Swagata is a Data Scientist with 6+years of experience who meandered through the world of technology, business, design while doing Masters from CMU to finally find her calling in the world of data analytics, ML and AI. A trained classical dancer, passionate guitarist, love to live life to the fullest everyday.

Carlos Rodríguez Abellán

Lead NLP Engineer at Fujitsu

Carlos Rodríguez Abellán, Lead NLP Engineer at Fujitsu’s global Data Intelligence CoE. He spearheads NLP initiatives by designing and implementing solutions to aid in the digital transformation of customers across various industries. He holds a BSc in Telecommunications Engineering and an MSc in Signal Processing and Machine Learning (both from Universidad Politécnica de Madrid). He also serves as an adjunct professor in postgraduate programs at several universities, imparting expertise in Deep Learning and NLP. Previously worked at companies such as Telefónica, EY, Vodafone, and British Telecom.

Logesh Kumar Umapathi

Lead Machine Learning Research Engineer at Saama Technologies

Logesh is a Lead Machine Learning Research Engineer at Saama Technologies, where he is leading the Machine learning efforts for a ML/NLP product aimed to accelerate clinical trials and time to market of drugs. His expertise lies in evolving deep learning-based NLP solutions from preliminary prototypes into fully functional production-ready systems. He has also published multiple peer-review research papers. His research interests include Biomedical LLMs and code generation. Apart from his professional commitments, Logesh takes an active role in the open-source community. He is a member of the Bigcode team, contributing to the efforts in building open source code generation models. Furthermore, he actively maintains ‘Mutate’, an open-source library specifically designed for data synthesis using LLMs. Outside of his professional realm, Logesh’s interests include photography and books

Thomas Kranzkowski

Senior Data Science at Consultant Woodmark Consulting AG

Thomas is Senior Data Scientist at Woodmark Consulting AG, where he works on AI and Cloud solutions in cross-industries. He has been a speaker at various events for topics such as AI & Sustainability and Quantum Computing and has also developed online courses for Data Science & Analytics with Python. He holds a bachelor’s degree in economics from University of Kiel and studied data science in masters at Technical University of Chemnitz. He is based in Berlin.

Shir Chorev

Co-founder & CTO at Deepchecks

Shir is the co-founder and CTO of Deepchecks, an MLOps startup for continuous validation of ML models and data. Previously, Shir worked at the Prime Minister’s Office and at Unit 8200, conducting and leading research in various Machine Learning and Cybersecurity related challenges. Shir has a B.Sc. in Physics from the Hebrew University, which she obtained as part of the Talpiot excellence program, and an M.Sc. in Electrical Engineering from Tel Aviv University. Shir was selected as a featured honoree in the Forbes Europe 30 under 30 class of 2021.

Alex Chao

Senior Product Manager at Microsoft

Currently, Alex is building next-generation AI products at Microsoft through the Office of the CTO with an emphasis on multimodal and large language models. Over the last decade, Alex has successfully launched applied ML products across industries in health, gaming, finance, defense, energy, autonomous vehicles, semiconductors, and enterprise tech. He has held product management roles at SambaNova Systems and C3.ai building out ML Platforms and deep learning offerings to enterprise customers. Alex continues to be an active ML practitioner and was the first data science hire at Uber’s Advanced Technologies Group working on building large scale computer vision and sensor fusion algorithms for self-driving cars. Alex is motivated to help raise the next generation of data scientists and product leaders and has taught and mentored at places like General Assembly, Springboard, and Product School to equip students for their future success. He is a proud alumni of UC Berkeley! Go Bears!

Kwan-Yuet (Stephen) Ho

Data Scientist Leidos

Kwan-Yuet (Stephen) Ho, Ph.D. is an applied quantitative researcher with 10-year experience in machine learning, text mining, and other related data science and quantitative fields. He possesses exceptional mathematical abilities, and extensive experience with software development. He is seeking to advance his careers in machine learning, data analytics, and software engineering, aiming at solving business analytical (research and development) and engineering (automation) problems. Currently he is doing ground breaking research leveraging NLP, AI/ML techniques to provide solutions for National Institute of Health (NIH) Center for Scientific Review (CSR) mission of ensuring NIH grant applications receive fair, independent and timely scientific reviews and are free from inappropriate influences so NIH can fund the most meritorious research.

R. Spencer Schaefer

Chief Informatics Office at Kansas City VAMC

R. Spencer Schaefer, PharmD currently serves as the Chief Health Informatics Officer for the Kansas City VAMC, co-lead for the Medical Informatics Data Science and Emerging Technologies (MInDSET) team and is the AI Solution Architect for the VA National Artificial Intelligence Institute (NAII). He has over 20 year experience in medical informatics, software and cloud service provider development and big data analytics. His focus for the Veteran’s Health Administration is design, development, and implementation of advanced technologies to improve patient care and reduce staff burden. He is currently collaborating with VHA, Office of Research and Development, VA Innovations, academia, industry partners and VA Office of Information Technology Division of Data and Analytics to engineer world class cloud computing architecture to accelerate AI research and operational deployment for the Department of Veterans Affairs.

Surbhi Bhatnagar

Postdoctoral Research Fellow at Cincinnati Childrens Hospital

Surbhi Bhatnagar is a Postdoctoral Research Fellow at Cincinnati Children’s Medical Hospital Center (CCHMC). She is a data enthusiast committed to improving the understanding of diseases through data science and informatics research. She has a computer science and engineering background and focuses on applying machine learning and big data approaches to extract and infer insights from large-scale, noisy, structured, and unstructured biomedical data. Surbhi works with rich multimodal data sources such as Electronic Health Records (EHR), Environmental, Imaging, Genomic Sequencing, and Gene Expression and is passionate about integrating multimodal biomedical data with domain knowledge to enhance learning, further understanding, and improve healthcare outcomes.

Davis Blalock

Research Scientist at MosaicML by Databricks

Davis Blalock, Research Scientist, Databricks As the first employee of generative AI startup MosaicML, now acquired by Databricks, Davis is uniquely suited to breaking down the challenges of LLM training and deployment—and the tips and tricks he uses to make machine learning at scale accessible. Davis also runs Davis Summarizes Papers, a blog read by 13k+ ML researchers and practitioners, where he goes through all the machine learning arXiv submissions each week and summarizes 10 to 20 of his favorites papers. Prior to MosaicML, Davis received his PhD from MIT, where he designed high-performance machine learning algorithms with the goal of eliminating tradeoffs between speed, accuracy, privacy, and safety in machine learning.

Sanchit Juneja

Director-Big Data & ML at Booking.com

15+ years of industry experience in tech and product roles across India, Africa, South-east Asia, and Europe with organizations such as Booking.com, Paytm, GoJek, Rocket Internet, and National Instruments. Currently Director-Data Science & Machine Learning Platform with Booking.com.