Dean Abbott is an internationally recognized thought leader and innovator in data science and predictive analytics, with more than three decades of experience solving problems in customer analytics, fraud detection, risk modeling, text mining, survey analysis, and many more. He is frequently included in lists of the top pioneering and influential data scientists in the world. Mr. Abbott is the author of Applied Predictive Analytics (Wiley, 2014) and coauthor of The IBM SPSS Modeler Cookbook (Packt Publishing, 2013). He is a popular keynote speaker and bootcamp/workshop instructor at conferences worldwide and serves on advisory boards for the UC/Irvine Predictive Analytics and UC/San Diego Data Science Certificate programs. He holds a bachelors degree in computational mathematics from Rensselaer Polytechnic Institute and a masters degree in applied mathematics from the University of Virginia. 

Vladimir Barash is Director Graphika Labs. He has received his Ph.D. from Cornell University, where he studied Information Science and wrote his thesis on the flow of rumors and virally marketed products through social networks. At Graphika, Vladimir's research focuses on deep learning applications of network analysis, detection and deterrence of disinformation operations on networks, and causal mechanisms of large-scale social behavior.

In addition to his research duties, Vladimir has a decade's experience working with big data, from scientific computing (Matlab, scipy) to parallel processing technologies (Hadoop / Hive) to data storage and pipelining (Redis, mongodb, MYSQL) at the terabyte scale. At Graphika, Vladimir has co-designed and implemented systems that process tens of millions every six hours to deliver timely information on influencers and conversation leaders in online communities tailored to client interests. Vladimir is proficient in over a dozen programming languages and frameworks and has designed production-ready systems for every stage of big data analysis, from collection to client-facing presentation via web, spreadsheet or graphic visualization.

Vladimir has been active in the Social Media Research Foundation (SMRF) and the NodeXL project, helping build a network analysis package that brings relational data analysis at scale to the fingertips of any interested user, without requiring specialized knowledge or technical training beyond familiarity with Microsoft Excel. NodeXL has enabled users in academia, industry and the general public to analyze tens of thousands of social networks, from networks of politicians voting on bills to networks of motorcycle enthusiasts working together. As part of his work with SMRF and the NodeXL team, Vladimir has contributed a chapter on Twitter analysis to Analyzing Social Media Networks with NodeXL: Insights from a Connected World.

Vladimir's work has received awards at the International Conference for Weblogs in Social Media and Bits on Our Minds. He has presented his research at academic and industrial campuses all over North America and Europe, including: Xerox/PARC, Microsoft, Colgate University, Northeastern University, UMCP and Oxford University (Oxford Internet Institute). He currently resides in Somerville, MA.

Bardia Beigi works at Microsoft as an Applied Scientist II in the Industry AI group delivering AI/ML based solutions to various industries within Azure. Bardia has a master's degree in Computer Science from Stanford University, as well as Bachelor of Applied Science in Engineering Physics from the University of British Columbia. In his spare time, Bardia enjoys traveling, trying out new dessert spots, and learning new life hacks.

Leo Betthauser works at Microsoft Research in Redmond, Wash. Leo has a Ph.D. in mathematics from the University of Florida where he studied applied algebraic topology. Leo is currently exploring the application of deep neural techniques to cyber security. In his spare time, Leo enjoys traveling, cooking, and skiing.

Christopher Brossman leads the enterprise ML/AI teams and Data Engineering teams that enable scale and profitability at The RealReal. Experienced ML/AI engineer executive with wide track record in creating products that embed computer vision, machine learning, statistical modeling, and optimization to create demonstrable value.

Clinton Brownley, Ph.D., is a data scientist at WhatsApp, where he’s responsible for a variety of analytics projects designed to improve messaging and VoIP calling performance and reliability.  Before WhatsApp, Clinton was a data scientist at Facebook, working on large-scale infrastructure analytics projects to inform hardware acquisition, maintenance, and data center operations decisions.  As an avid student and teacher of modern analytics techniques, Clinton is the author of two books, “Foundations for Analytics with Python” and “Multi-objective Decision Analysis,” and also teaches Python programming and data science courses at Facebook and in the Bay Area. Clinton is a past-president of the San Francisco Bay Area Chapter of the American Statistical Association and is a council member for the Section on Practice of the Institute for Operations Research and the Management Sciences. Clinton received degrees from Carnegie Mellon University and American University.

Pranjal helped set up Cisco Innovation Labs after dropping out of his PhD and handles Machine Learning/Product there. He also serves as an Entrepreneur-in-Residence at Vonzos Partners. Previously he conducted ML research at Adobe Research, IBM Research, University of Alberta, Purdue University and Northwestern University. He attended Stanford GSB in the Ignite program and is an On Deck Fellow.

John Elder chairs America’s most experienced Data Science consultancy. Founded in 1995, Elder Research has offices in Virginia, Maryland, North Carolina, Washington DC, and London. Dr. Elder co-authored 3 award-winning books on analytics, was a discoverer of ensemble methods, chairs international conferences, and is a popular keynote speaker. John is occasionally an Adjunct Professor of Systems Engineering at the University of Virginia.

Jen Gennai leads Google’s Responsible Innovation team which is responsible for operationalizing Google’s AI Principles, ensuring that Google’s products have fair and ethical outcomes on individual users and the world. Her team works with product and engineering, leveraging a multidisciplinary group of experts in ethics, human rights, user research, racial justice and gender equity to validate that products and outputs align with our commitments to fairness, privacy, safety, societal benefit and more. Before she co-authored the AI Principles and founded Responsible Innovation, Jen worked on machine learning fairness and founded the Ethical ML team in Trust & Safety.

Sami is the co-founder and CTO of Forethought, the leading generative AI platform for customer experience. Founded in 2017, Forethought integrates with most popular helpdesk and CRM solutions, and uses a proprietary AI engine dubbed SupportGPT™ to provide automation, agent augmentation, and advanced analytics and insights solutions. Forethought's customers include Instacart, Upwork, Marriott, and many others. Prior to founding Forethought, Sami was a senior machine learning engineer on the LinkedIn Feed AI team. Sami received his undergraduate and graduate degrees in computer science from Harvard University. He was named to the Forbes 30u30 "Enterprise Technology" list in 2018.

My name is Dao Ho, I am a Senior Data Scientist at Albertsons. My current focus is personalization. At Albertsons, I have worked on several personalization models such as Buy It Again (ranking past purchases), embedding models for our products and customers. In collaboration with Ankita, I have been working on building a Wide & Deep Neural Network model for recommendations. Before Albertsons, I worked at a research lab for GAC, a Chinese car manufacture, building models to monitor the batteries of 30,000 EVs. Prior to that, I worked at a fintech company modeling market conditions. And finally, I graduated from Carnegie Mellon University with a Ph.D. degree in Physics.

Vanja Josifovski is the Co-Founder and CEO of Kumo. Prior to Kumo, Vanja was the CTO of Homes at Airbnb. Here Vanja led an organization that included horizontal groups such as Homes Engineering and Homes Data Science, as well as GM groups such as Marketplace, Relevance and Personalization, and Regulatory Frameworks. Before Airbnb, Vanja was the CTO & VP Eng at Pinterest, responsible for the overall technical vision and strategy of the company and communicating that to leadership and the teams; hiring and development of technical talent. As the head of Engineering he managed some core engineering teams. Vanja has also served as an advisor and investor for multiple startups and was the founder for Kosei which was acquired by Pinterest.

Kian Katanforoosh is the CEO and cofounder of Workera.ai, the skills intelligence platform redefining how enterprises understand, develop, and mobilize talent. Workera empowers organizations to stay ahead by unlocking the skills data needed to drive innovation. Enterprises get an objective pulse of their innovation skills through a configurable skills ontology, using AI-powered measurement of data, AI, software, cloud, and cyber skills at an atomic-level.

Kian is also a lecturer at Stanford University, where he teaches Deep Learning in the Computer Science department with Prof. Andrew Ng. Kian has been acknowledged for his teaching excellence by Stanford with the Walter J. Gores Award, Stanford’s highest teaching award, and the Centennial Award for Excellence in teaching.

Additionally, Kian is a founding member of deeplearning.ai and he co-created the Deep Learning Specialization on Coursera with Andrew Ng. From 2014 to 2016, Kian co-founded and co-led Daskit, a French start-up developing in-classroom ed-tech solutions for universities.

Sagar is an accomplished Big Data and Machine Learning Architect with a passion for designing innovative solutions that accelerate digital transformation and simplify data management and analytics. With extensive experience combining multiple transactional and operational systems, Sagar excels at implementing simplified Data Lake, Lake Houses, MLOps Platform, Customer Data Platform, and Data Mesh environments. His focus is on delivering actionable insights through descriptive and predictive analytics. Sagar specializes in collaborating with strategic clients delivering actionable insights through descriptive and predictive analytics.

Sagar has held numerous positions across Data Engineering, Platform Management, and Enterprise Architecture teams. He is also an enthusiastic public speaker at conferences and events, sharing his expertise and insights with fellow industry professionals.

Diego Klabjan is a professor at Northwestern University, Department of Industrial Engineering and Management Sciences. He is also Founding Director, Master of Science in Analytics and Director, Center for Deep Learning. His work is focused on machine learning, deep learning and analytics (modeling, methodologies, theoretical results) with concentration in finance, insurance, sports, and bioinformatics. Professor Klabjan has led projects with large companies such as Intel, Baxter, Allstate, Anthem, and many others. He is also a co-founder of Videspan, LLC after successfully starting Opex Analytics, a Coupa company.

Jared P. Lander is Chief Data Scientist of Lander Analytics, the Organizer of the New York Open Statistical Programming Meetup and the New York and Government R Conferences, an Adjunct Professor at Columbia Business School, and a Visiting Lecturer at Princeton University. With a masters from Columbia University in statistics and a bachelors from Muhlenberg College in mathematics, he has experience in both academic research and industry. Jared oversees the long-term direction of the company and acts as Lead Data Scientist, researching the best strategy, models and algorithms for modern data needs. This is in addition to his client-facing consulting and training. He specializes in data management, multilevel models, machine learning, generalized linear models, data management, visualization and statistical computing. He is the author of R for Everyone (now in its second edition), a book about R Programming geared toward Data Scientists and Non-Statisticians alike. The book is available from Amazon, Barnes & Noble and InformIT. The material is drawn from the classes he teaches at Columbia and is incorporated into his corporate training. Very active in the data community, Jared is a frequent speaker at conferences, universities and meetups around the world.

Michelle Li is a Data Scientist at Paychex and work on predictive modeling, text analytics and business intelligence. Before joining Paychex, Michelle received a PhD degree in Earth Science and spent over 10 years analyzing and modeling data in a variety of fields including satellite imagery, weather prediction, environmental protection, and child welfare.  

Dr. Ankita Mangal is a Senior Data Scientist at Albertsons Companies. She has a broad experience applying data science & analytics solutions at companies like Procter & Gamble, Robert Bosch and Tata Steel Ltd. She is an accomplished leader in the field of retail and marketing science, who is championing data informed decision making in the Retail and Consumer Packaged Goods industry. Dr. Mangal is passionate about efficient cross functional collaborations for creating successful ML solutions. In her current role, she provides technical leadership, mentorship and develops interpretable and accurate models for business strategy decisions. Dr. Mangal has a doctoral degree from Carnegie Mellon University and is an alumnus of IIT Kharagpur.

Mrinal Mohit heads machine learning at Glean, a Sequoia-backed unicorn building the next generation of enterprise search. Mrinal previously worked as a Machine Learning engineer at Facebook, where he built conversational systems powering Facebook Portal, Oculus Quest, and Ray-Ban Stories. His research has been published research at NeurIPS and EMNLP, and he co-created the open source library PyText. He holds a masters from MIT, and a bachelors from IIT.

Long before the buzz surrounding generative AI, Martin Musiol was already advocating for its significance in 2015. Since then, he has been a frequent speaker at conferences, podcasts, and panel discussions, addressing the technological advancements, practical applications, and ethical considerations of generative AI. Martin Musiol is a co-founder of generativeAI.net, a lecturer on AI to over 1000 students, and publisher of the newsletter 'Generative AI: Short & Sweet'. As a Data Science Manager at Infosys Consulting (previously at IBM), Martin Musiol helps companies globally harness the power of generative AI to gain a competitive advantage.

Ayush is the co-founder of TwelveFold, an AI start-up studio, where he manages a portfolio of MLOps and Generative AI companies with entrepreneurs. He also works as the CEO of Censius, an AI Observability platform that helps to optimize AI models' real-world performance.  As a seasoned professional, he has closely worked with customers across industry verticals, AI teams, and research projects to build reliable and compliant AI solutions to solve everyday business problems and scale models at production.

Rishab is the co-founder & CTO of Openlayer. Openlayer is a YC-backed company that aims to make it easy for ML teams to find failures and biases in their models, figure out their root causes and use better data to fix them. Rishab graduated from Yale in 2019, and subsequently worked at Apple on a variety of projects within their AI/ML org before founding Openlayer.

Eric Siegel, Ph.D. is a leading consultant and former Columbia University professor who helps companies deploy machine learning. He is the founder of the long-running Machine Learning Week conference series, a frequent keynote speaker, and executive editor of The Machine Learning Times. Eric authored the forthcoming book The AI Playbook: Mastering the Rare Art of Machine Learning Deployment and the bestselling Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, which has been used in courses at hundreds of universities. He won the Distinguished Faculty award when he was a professor at Columbia University, where he taught the graduate courses in machine learning and AI. Later, he served as a business school professor at UVA Darden. Eric also publishes op-eds on analytics and social justice.

Prerna Singh is currently working as an Applied Scientist II in the Industry AI group @Microsoft where she develops machine learning-based solutions for different industrial verticals including finance and sustainability. Before joining Microsoft, she obtained her master's degree in Electrical and Computer Engineering with a concentration on Machine Learning from Carnegie Mellon University (CMU). Prerna is passionate about machine learning, NLP and deep Reinforcement Learning. Besides work, Prerna enjoys traveling, Zumba and hiking in her free time.

Dr. Marc A. Smith is a sociologist specializing in the social organization of online communities and computer mediated interaction. Smith leads the Connected Action consulting group. Smith co-founded the Social Media Research Foundation (http://www.smrfoundation.org/), a non-profit devoted to open tools, data, and scholarship related to social media research. He contributes to the open and free NodeXL project (http://nodexl.codeplex.com) that adds social network analysis features to the familiar Excel spreadsheet. NodeXL enables social network analysis of email, Twitter, Flickr, WWW, Facebook and other network data sets. Along with Derek Hansen and Ben Shneiderman, he is the co-author and editor of Analyzing Social Media Networks with NodeXL: Insights from a connected world, from Morgan-Kaufmann which is a guide to mapping connections created through computer-mediated interactions. Smith has published research on social media extensively, providing a map to the landscape of connected communities on the Internet.

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 Masters degrees in both Computer Science and Business Administration. He was named USA CTO of the Year by the Global 100 Awards and GameChangers Awards in 2022.

James Taylor is the CEO of Decision Management Solutions and is a leading expert in how to use business rules and analytic technology to build decision management systems. He is passionate about using decision management systems to help companies improve decision-making and develop an agile, analytic and adaptive business. He provides strategic consulting to companies of all sizes, working with clients in all sectors to adopt decision-making technology. James is an expert member of the International Institute for Analytics and is the author of multiple books and articles on decision management, decision modeling, predictive analytics and business rules, and writes a regular blog at JT on EDM. James also delivers webinars, workshops and training. He is a regular keynote speaker at conferences around the world.

Huy Vo is a Data Science and Analytic Manager at Otrafy Technologies Inc where he spends time researching and converting Machine learning from academia into production that is helpful for Food Safety Supply Chain Management and Document Understanding. He is passionate about understanding how machine learning can leverage and understand information from Complex Documents and create valuable insights for supply chain stakeholders. Not only that, but he is also interested in solving the problem of using Small Datasets to Solve Big Problems through Data Augmentation techniques for Document AI. He held a degree in Computer Science from the University of South Australia and worked as a Research Assisstant for the University of South Australia's Industrial AI Research Centre.

Devanshi is the co-founder of Censius, an AI Observability platform that helps to optimize AI models' real-world performance. As a seasoned ML practitioner, she recognizes the significance of enterprise-level Observability to help companies solve complex challenges in AI development and incorporate AI models into production successfully. She has worked with customers across industry verticals alongside AI teams and is a strong advocate for building transparent, reliable, and compliant AI solutions.

Evan Wimpey was a Financial Management Officer in the Marine Corps and an Operations Associate at Goldman Sachs prior to joining Elder Research as a Data Scientist. He holds master's degrees in Economics from East Carolina University and in Analytics from North Carolina State University. He is currently the Director of Strategic Analytics at Elder Research. Evan has a passion for cryptocurrency and exploring more equitable access to credit markets. Evan lives in Cary, NC with his wife and two sons.