Speakers

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.

Cheryl has 13 years experience in Statistical Physics, Computational Modeling, Data Science and Digital technologies having worked with both public and private sectors in developing strategic solutions using Machine Learning and Agent-Based Models. At AWS, Cheryl is a Principal Solution Architect for Autonomous Computing with a focus on Predictive Modeling and Simulations for Digital Twins. Prior to joining AWS, Cheryl worked at Quantum Black – McKinsey and Solvay as Data Science Lead defining digital architectures, and delivering Advanced Analytics and AI assets covering various industries including Chemicals Manufacturing, Agriculture, Aviation, R&I, Procurement, Commercial, Supply Chain, Finance and Energy. Prior to that, she worked on insider threat detection, computer vision for marketing, investment banking trading technologies and geospatial analytics for telecommunications. Cheryl obtained her Ph.D. in Physics from Nanyang Technological University in 2017 where she focused on analytical, graph and computational models for urban, linguistic and genetic systems. She also received a B.S. in Applied Physics from the University of the Philippines with specializations in Neural Network and Complex Systems.

Juan Acevedo is an Enterprise machine learning architect at Google where he helps customers optimize models for large scale distributed training and serving with accelerators such as GPUs and TPUs.

Bardia Beigi works at Microsoft as a Senior Applied Scientist 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.

Dr. Chakrabarti is a Senior Research Scientist in Hitachi's Financial Innovation Lab. in Santa Clara. He works at the intersection of data science and finance, and has been doing industrial research for over ten years . He did his MS-PhD in Electrical and Computer Engineering at Rice University, and afterwards did his Master of Financial Engineering at U C Berkeley. Dr. Chakrabarti's research publications and patents have collectively been cited over one thousand times.

Vash Doshi is the Manager of Industry Relations for UCLA Anderson's Master of Science in Business Analytics program.  Daily, Vash strives to show employers why UCLA Anderson's MSBA has been ranked the #2 place in the world for the past four years to study, build an analytics career, and recruit from. He is driven to help students and UCLA MSBA’s hundreds of partner firms find each other to create the perfect analytics fit. Vash believes in the magic of people. Whether through developing and advocating for reciprocal market access for American firms so that more Americans can find meaningful jobs and grow their businesses via internships at U.S. Departments of State and Commerce, or by counseling over 500 students to help them find their perfect career, he has over five years of experience helping people make magic happen.  He is currently finishing up his Ph.D. in Political Science at UCSB and holds an M.A. in International Studies from the University of Denver’s Josef Korbel School of International Studies.

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.

Sarah Kalicin leads Achieve More with Data, LLC, where her focus is to elevate business performance with Data Science. With her deep experience, she formulates strategic plans for the adoption of analytics that bolster business outcomes. Her diverse analytic background spans roles at Intel Corp, Becton Dickinson (BD), Kraft Foods, Nabisco, Ford, and the USDA/National Agriculture Statistics Service, giving her valuable insights into the operational success of data-centric organizations. She possesses a Master’s in Applied Statistics from the University of Michigan and holds Bachelors’ degrees in Mathematics and Psychology from SUNY Oswego.

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.

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.

Wes is CEO and Co-founder of Kurve, Inc.. Prior to founding Kurve Wes was running an MLOps consulting business for 4 years, where he faced data discovery and feature engineering inefficiencies at many customers. Additionally, he brings a wealth of experience building end to end MLOps pipelines with success across multiple industries. Wes was an Entrepreneur In Residence at SRI International where he and SRI incubated Kurve.

Terry Miller is founder and director of the applied AI startup Bōwdee. Previously, he led a global team of data scientists and data engineers to solve problems in the Services business for Johnson Controls. Deploying the best practices of Machine Learning and Predictive Analytics, he facilitates outcomes in Customer Retention, Pricing, and other enterprise applications.

Long before the buzz surrounding Generative AI emerged, Martin Musiol already advocated for its significance in 2016. Since then, he has frequently appeared at conferences, podcasts, and panel discussions, addressing the technological advancements, practical applications, and ethical considerations surrounding Generative AI, Autonomous AI Agents, and Artificial General Intelligence.

In 2018, Martin Musiol founded GenerativeAI.net. There, he lectured to over 10,000 students on AI and published the newsletter 'Generative AI: Short & Sweet,' reaching over 43,000 subscribers. Additionally, he authored "Generative AI - Navigating the Course to the Artificial General Intelligence Future," published by Wiley.

As the GenAI Lead for EMEA at Infosys Consulting (formerly IBM), Martin Musiol assisted companies globally in harnessing the power of Generative AI, especially LLMs, to gain a competitive advantage.

Now, he is building AI Agents that take over software engineering tasks.

Martin’s LinkedIn Profile: https://www.linkedin.com/in/ma...

GenerativeAI.net's Webpage: https://generativeai.net/

Martin’s Newsletter: https://generativeai.net/newsl...

[book] Generative AI - Navigating the Course to the Artificial General Intelligence Future: https://a.co/d/ehyIKoX 

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.

Marina Petzel is a Machine Learning Engineer at Autodesk. In her role, she develops ML solutions to further improve the AutoCAD users experience; Autodesk's flagship design and drafting tool. Marina leads the data collection and labeling processes through automation using ML.

She is passionate about finding and developing efficient data driven solutions that address business needs. Marina has extensive experience in applying data science to various industries such as construction, healthcare, oil and gas, and finance.

Marina is an AI Influencer in social media where she shares AI/ML tips and best practices. She coaches and mentors young professionals in data science, engineering and career strategy.

Marina graduated from the University of Rochester, NY with a Master of Science degree in Data Science. She received her Bachelor degree in Computer Science from Moscow State University.

Steven J. Ramirez is the chief executive officer of Berkeley, Calif.-based Beyond the Arc, Inc., a firm recognized as a leader in helping companies transform their customer experiences by leveraging advanced analytics.

In addition to developing and executing the vision for Beyond the Arc, Ramirez leads teams of data and strategy consultants committed to client success. They analyze customer and social media data, combined with text analysis, to drive customer growth, improve customer retention, understand service breaks and build stronger customer loyalty.

Prior to leading Beyond the Arc, Ramirez served as an executive with Time Warner, where he was responsible for creating and successfully implementing marketing and corporate development strategies.

Ramirez earned a bachelor's degree and master's in Business Administration from the University of California at Berkeley. He as also created and taught courses in business management for UC Berkeley and been a guest speaker at the university's Haas School of Business.

Karl Rexer founded Rexer Analytics in 2002. He and his teams have built an outstanding reputation providing predictive modeling and analytic consulting to clients across many industries. Recent clients include OneBlood, PwC, Boston Scientific, Redbox, ADT Security, Interamericana University, MIT, Forward Financing, SharkNinja, and many smaller companies. In addition to leading client engagements and hands-on data work, Karl is a predictive analytics evangelist, frequently speaking at conferences, colleges, and other events. He also serves on Advisory Boards for the Business Analytics programs at both Babson College and Bentley University. Since 2007 Rexer Analytics has conducted surveys of analytic professionals, asking them about their algorithms, tools, behaviors and  views. Summary reports from these surveys are available as a free download from the Rexer Analytics website. Prior to founding Rexer Analytics, Karl held leadership positions at several consulting firms and two multi-national banks. Karl holds a PhD from the University of Connecticut.

Alejandro Jesús Castañeira Rodríguez is the Principal Data Scientist atJanzz.technology a leading developing and consulting company in jobmatching solutions, international classification systems, multilingualknowledge graphs, and processing of Human Resources(HR) information.Janzz offers SaaS/Cloud solutions as well as standard on-premise andwhite-label products in up to 40 languages for multinational jobportals, social and career networks, governmental or state-levelorganizations and public employment services(PES) worldwide. In hiscurrent role, Alejandro leads multiple stages of the product developmentcycle, from data collection, training of deep learning models,evaluation, deployment, maintenance, and customer support. He alsosupports and mentors other members of its team, providing guidance ontechnical issues, setting performance goals, and identifying areas forprofessional growth. Before coming to the HR industry, Alejandro was alecturer of Applied Mathematics and researcher, for more than 5 years atone of the most prestigious and beloved universities in Latin America,the Universidad de Oriente, Cuba. Where he graduated from a Master'sDegree in Computer Science specializing in the field of ArtificialIntelligence and Natural Language Processing.

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 and its new sister, Generative AI Applications Summit, the instructor of the acclaimed online course “Machine Learning Leadership and Practice – End-to-End Mastery,” executive editor of The Machine Learning Times, and a frequent keynote speaker. He wrote 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, as well as The AI Playbook: Mastering the Rare Art of Machine Learning Deployment. Eric’s interdisciplinary work bridges the stubborn technology/business gap. At Columbia, he won the Distinguished Faculty award when teaching the graduate computer science courses in ML and AI. Later, he served as a business school professor at UVA Darden. Eric also publishes op-eds on analytics and social justice.

Eric has appeared on Bloomberg TV and Radio, BNN (Canada), Israel National Radio, National Geographic Breakthrough, NPR Marketplace, Radio National (Australia), and TheStreet. Eric and his books have been featured in Big Think, Businessweek, CBS MoneyWatch, Contagious Magazine, The European Business Review, Fast Company, The Financial Times, Forbes, Fortune, GQ, Harvard Business Review, The Huffington Post, The Los Angeles Times, Luckbox Magazine, MIT Sloan Management Review, The New York Review of Books, The New York Times, Newsweek, Quartz, Salon, The San Francisco Chronicle, Scientific American, The Seattle Post-Intelligencer, Trailblazers with Walter Isaacson, The Wall Street Journal, The Washington Post, and WSJ MarketWatch.

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.

Evan brought his military experience to Elder Research to deliver client solutions as a Data Scientist. He now serves as the Director of Analytics Strategy, helping to marry the exciting things that analytics can do with the myriad of challenges that people are facing. Evan almost always has a smile on his face, and that smile is the widest when he is helping organizations use data in new ways to solve unique problems. Evan earned his BS in Management from Georgia Tech, his MS in Economics from East Carolina University and his MS in Analytics from the Institute for Advanced Analytics at NC State University.  He loves teaching and learning and can often be found exploring the outdoors with his wife and children.