Advisory Board Members

Amy Shi-Nash

Dr. Amy Shi-Nash has been the Global Head of Analytics & Data Science at HSBC since early-2019. Previously she was the Chief Data Science Officer at Singtel. Amy has more than 15 years of industry experience in data mining, consumer analytics, loyalty, marketing, and management consulting globally. As the founding member of DataSpark at Singtel, Amy was responsible for driving data science-led innovation and product development, creating disruptive opportunities and new revenue streams, by combining unique Telco assets with advanced analytics and big data technology.

Amy is the co-chair of KDD Australia and New Zealand Chapter, Science Board Member of i-Com, and the Chair of the Industry Advisory Board at Swinburne University of Technology’s Data Science Research Institute.

She has a Ph.D. in data mining from Hong Kong Polytechnic University, a Masters in AI, a Bachelor in Computer Science and an MBA from the University of Reading.

David Hand

Professor David Hand is Senior Research Investigator and Emeritus Professor of Mathematics at Imperial College, London, where he formerly held the Chair in Statistics. He is a Fellow of the British Academy, and an Honorary Fellow of the Institute of Actuaries, and has served (twice) as President of the Royal Statistical Society. He is a non-executive director of the UK Statistics Authority, a member of the European Statistical Advisory Committee, a member of the International Scientific Advisory Committee of the Canadian Statistical Sciences Institute, and of the Advisory Board of the Cambridge Institute for the Mathematics of Information.

He has published 300 scientific papers and 29 books, including Principles of Data Mining, Information Generation, Measurement Theory and Practice, The Improbability Principle, and The Wellbeing of Nations.

In 2002 he was awarded the Guy Medal of the Royal Statistical Society, and in 2012 he and his research group won the Credit Collections and Risk Award for Contributions to the Credit Industry. He was awarded the George Box Medal in 2016. In 2013 he was made OBE for services to research and innovation.

Deepak Agarwal

Deepak Agarwal is the VP of artificial intelligence (AI) at LinkedIn. He is an expert in artificial intelligence technologies and engineering leadership, with more than twenty years of experience developing and deploying state-of-the-art machine learning and statistical methods for improving the relevance of web applications.

Deepak has worked in various positions: as chief scientist of large projects, and as a manager of large and small highly technical teams. He is experienced in conducting novel scientific research to solve notoriously difficult AI problems.

He is a Fellow of the American Statistical Association, a member of the board of directors for the Association for Computing Machinery's Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD), past program chair of KDD, and associate editor of two top-tier journals in statistics. He regularly serves on senior program committees of top-tier conferences like KDD, NIPS, CIKM, ICDM, SIGIR, and WSDM.

Greg Makowski

Greg Makowski has been Head of Data Science Services at Foghorn Systems Inc. since February 20, 2018 and heads the Data Science Services (DSS) group, providing data mining and big data consulting services for FogHorn clients. He has over 26 years of experience in data mining, deploying 90+ models for clients in globally. He was Director of Data Science at LigaDATA. He has a patent named Event Lift Forecasting, which is an automated forecasting for retail promotion events

Greg Makowski is also the Vice Chair at Chair of Data Science SIG, which is a local chapter of the Association of Computing Machinery (ACM).

Makowski has a Master degree in Computer Science from Western Michigan University.

Jeannette Wing

Jeannette Marie Wing is Avanessians Director of the Data Sciences Institute at Columbia University, where she is also a professor of computer science. Until June 30, 2017, she was Corporate Vice President of Microsoft Research with oversight of its core research laboratories around the world and Microsoft Research Connections. Prior to 2013, she was the President's Professor of Computer Science at Carnegie Mellon University, Pittsburgh, Pennsylvania, United States. She also served as assistant director for Computer and Information Science and Engineering at the NSF from 2007 to 2010.

Wing has been a leading member of the formal methods community, especially in the area of Larch. She has led many research projects and has published widely. With Barbara Liskov, she developed the Liskov substitution principle, published in 1993.

She has also been a strong promoter of computational thinking, expressing the algorithmic problem-solving and abstraction techniques used by computer scientists and how they might be applied in other disciplines.

Josh King

Josh leads the technology recruiting practice for Ridgeway Partners, a 40-person executive and board recruiting firm. He has a successful track record in placing senior-level executive and board candidates across the technology, financial services and consumer markets. In addition to having placed senior-level data science and AI/ML talent for the top tiers of the government, Josh also works closely with Private Equity and Venture Capital firms to recruit senior technology leaders to their portfolio companies.

Josh is also the Founder of HireAi, a Ridgeway-incubated startup and online talent marketplace which connects companies to the best early-stage data science, AI and machine learning talent. Previously, Josh led B2B partnerships at a PE-backed flight data aggregation company. Josh serves on the Advisory Board of B/Spoke, the Harvard Club of Boston's Digital Advisory Board, Handel & Haydn Society's Digital Advisory Board and as an Advisor to MassChallenge, a global startup accelerator and competition with a focus on high-impact, early-stage entrepreneurs.

Josh advises companies on how to attract and retain digitally transformative talent at the board and executive level. He has assembled digital advisory boards in addition to appointing digital advisory directors with expertise in data analytics, machine learning, cybersecurity, e-commerce, cloud infrastructure, demand generation, social media and digital marketing.

Juan Escobar

Juan Escobar is Head of Data Solutions at Diffbot. He manages efforts in building strategic relationships and partnerships with data science teams all over the world that leverage Diffbot's Knowledge Graph, the World's Largest Database of Structured Public Data. Juan started helping Diffbot grow in 2014 - Diffbot AI over the years has been adopted by hundreds of companies to access structured datasets from billions of web pages across the internet. Juan advises data leaders covering various industries on ways they can leverage AI to solve data challenges for their respective products/applications, services and business processes.

Prior to Diffbot, over a decade Juan built his career at companies such as Google, LinkedIn, IDEO, DreamWorks, Intuit, Symantec, Kellogg's and many others. He’s built expertise in business development, operations, recruiting and finance through his work. Juan has also contributed to many startups and non-profit initiatives with advisory counsel and leadership development.

Juan graduated from San Jose State University in Marketing and Accounting in 2009.

Kamelia Aryafar

As Overstock.com’s Chief Algorithms Officer, Dr. Kamelia Aryafar leads the company’s machine learning, data science, data engineering and analytics functions across the organizations. Since joining Overstock.com in 2017, Kamelia’s teams have integrated state-of-the-art machine learning and artificial intelligence algorithms across various product teams, including personalization, pricing, ranking, search, recommender systems, marketing, CRM, advertising technologies, email, sourcing and supply chain.

Kamelia transitioned from academia to industry as a Senior Machine Learning Scientist and Lead at Etsy in 2013, where she worked with different product teams across several platforms to integrate machine learning and artificial intelligence algorithms throughout the organization.

Kamelia holds a Ph.D. and M.Sc. in computer science and machine learning from Drexel University and a B.Sc in computer engineering from Sharif University of Technology. She has published several papers in scientific journals and conference proceedings. An active member of the machine learning community, she frequently speaks at academic and industry conferences focusing on advancing the field of artificial intelligence.

Kate Strachnyi

Kate Strachnyi is the author of Journey to Data Scientist and The Disruptors: Data Science Leaders. She is also the founder and host of Humans of Data Science (HoDS) - a project that works on showing the human side of data science.

Kate is a manager working for Deloitte, currently working in the data visualization & reporting space. She previously served as an insight’s strategy manager and research analyst, where she was responsible for enabling the exchange of information in an efficient and timely manner. Prior to working with data, she focused on risk management, governance, and regulatory response solutions for financial services organizations.

Before joining the consulting world, she worked for the chief risk officer of a full-service commercial bank, where she was in charge of developing an ERM program, annual submission of ICAAP, and gap analysis of Basel II/III directives. Additionally, she worked as a business development associate at the Global Association of Risk Professionals (GARP).

Kate received a bachelor of business administration in finance and investments from Baruch College, Zicklin School of Business.

Kirk Borne

Dr. Kirk Borne is a data scientist and an astrophysicist. He is Principal Data Scientist in the Strategic Innovation Group at Booz-Allen Hamilton since 2015. He was Professor of Astrophysics and Computational Science in the George Mason University (GMU) School of Physics, Astronomy, and Computational Sciences during 2003-2015. He served as undergraduate advisor for the GMU Data Science program and graduate advisor to students in the Computational Science and Informatics PhD program. Prior to that, he spent nearly 20 years supporting NASA projects, including NASA's Hubble Space Telescope as Data Archive Project Scientist, NASA's Astronomy Data Center, and NASA's Space Science Data Operations Office.

He has extensive experience in large scientific databases and information systems, including expertise in scientific data mining. He was a contributor to the design and development of the new Large Synoptic Survey Telescope (LSST), for which he contributed in the areas of science data management, informatics and statistical science research, galaxies research, and education and public outreach.

Kjersten Moody

Kjersten Moody joined State Farm in July 2017 as Vice President and Chief Data & Analytics Officer in Bloomington, Illinois. Previously, Kjersten led Data & Analytics and IT groups at global companies, such as FICO (Braun), Thomson Reuters and Unilever. She has a record of delivering tangible business results, and a depth of experience in scaling operations, planning mission-critical business initiatives and achieving profitability objectives.

As the Vice President for Information and Analytics at Unilever, she was responsible for harmonizing the delivery of information management, reporting simplification, analytics at scale and master data solutions to more than 20,000 users across all of Unilever’s businesses globally. She was formerly Senior Vice President, Global Technology Operations at Information Resources, Inc. (IRI) where she successfully modernized IRI’s global infrastructure which delivered a 33% reduction in IT costs and achieved ISO 27001 certification for information security. Prior to IRI, she held the position of Vice President Technology Services at Thomson Reuters where she led the modernization of the firm’s infrastructure, data warehouse, and operations for the Healthcare and Science division.

Kjersten is a graduate of the University of Chicago.

Munther Dahleh

Munther A. Dahleh is the William Coolidge Professor of Electrical Engineering and Computer Science and Director of the Massachusetts Institute of Technology (MIT) IDSS.

Prof. Dahleh is internationally known for his contributions to Robust control theory, computational methods for controller design, the interplay between information and control, statistical learning of controlled systems and its relations to model reduction of stochastic systems, the fundamental limits of learning, decisions and risk in networked systems including physical, social, and economic networks with applications to transportation and power networks, and the understanding of the Economics of data and the design of real-time markets for data and digital goods. For his work in these areas, he was awarded the Axelby best paper award four times, the Donald P. Eckman Award for best control engineer under age 35, and the presidential young investigator award. He is a fellow of both the Institute of Electrical and Electronics Engineers (IEEE) and International Federation of Automatic Control (IFAC) societies.

Prof. Dahleh received his BS degree in Electrical Engineering from Texas A&M University in 1983, and his Ph.D in Electrical Engineering from Rice University in 1987.

Murat Bicak

Murat founded Rapid Digital Ventures in 2019 to support AI-powered digital transformations with research, advisory services, and incubation.

Before Rapid Digital Ventures, Murat served as the first Chief Strategy and Growth Officer at PMI, where he established the organization's Strategy, Innovation, M&A functions, and oversaw all growth initiatives, including PMI's strategy and operations in China and India. At PMI, he also architected and kicked off an algorithmic-, and personalization-driven digital transformation initiative.

Murat held various leadership roles at Monitor Deloitte, Honeywell, and Hoffman La Roche as well as entrepreneurial ventures. His focus is on devising strategies to help gain competitive or transient advantage through invention, innovation, acquisition and diligent execution.

He earned a BS and MS from the Swiss Federal Institute of Technology, as well as an MBA from Columbia Business School.

Nuria Oliver

Nuria Oliver is Director of Data Science Research at Vodafone and Chief Data Scientist at DataPop Alliance. Previously, she was Scientific Director at Telefónica and a researcher at Microsoft Research. She holds a PhD from the Media Lab at MIT, and is an IEEE Fellow, ACM Fellow and elected as permanent member of the Royal Academy of Engineering of Spain. She is one of the most cited female computer scientists in Spain, well known for her work in computational models of human behavior, human-computer interaction, mobile computing and big data for social good.

Nuria graduated with a degree in Telecommunications Engineering from the Universidad Politecnica de Madrid in 1994. She was awarded the Spanish First National Prize of Telecommunication Engineers in 1994. In 1995 she received a La Caixa fellowship to study at MIT, where she received her doctorate in the area perceptual intelligence. In 2000, she joined as a Research in the area of human-computer interfaces for Microsoft Research.

In 2007 she moved to Spain to work at Telefónica R&D in Barcelona as Director of Multimedia Research, the only female director hired at Telefónica R&D at the time. Her work focused on the use of the mobile phone as a sensor of human activity.

Rajesh Parekh

Rajesh Parekh is Engineering Director at Google, managing a team responsible from Semantic Image Understanding and Road Network Inference for Geography. Previously, he was on Director and VP of Analytics & Data Science roles at Yahoo, Groupon and Facebook.

Rajesh Parekh is an expert in applying big data analytics and data mining to solve challenging business problems. He has a rich experience in partnering with executive leadership on product vision and strategy. He is a seasoned leader with 20 years of industry experience building and leading large, successful data teams. He has a proven track record in identifying key insights and building large-scale data products that drove $100M+ incremental revenue, improved operational processes efficiencies, and enhanced user experience. He is a hands-on practitioner and he has excellent communication skills.

His specialties are; Applied Machine Learning, Data Science, Big Data Analytics, Computational Advertising, Recommendation Systems, Web Mining, Online Learning, Experimentation Systems, Neural Networks, and Grammatical Inference.

Rajesh holds Ph.D. and M.s. degrees in Computer Science from Iowa State University.

Rayid Ghani

Rayid Ghani is the Director of the Center for Data Science and Public Policy, Research Associate Professor in the Department of Computer Science, and a Senior Fellow at the Harris School of Public Policy at the University of Chicago. He was also the co-founder of Edgeflip, an analytics start-up that grew out of the Obama 2012 Campaign, focused on social media products for non-profits, advocacy groups, and charities.

Earlier, he was a Senior Research Scientist and Director of Analytics research at Accenture Labs where he led a technology research team focused on applied R&D in analytics, machine learning, and data mining for large-scale and emerging business problems.

Ghani completed his graduate studies in the Machine Learning Department at Carnegie Mellon University with Tom M. Mitchell on Machine Learning and Text Classification and received his undergraduate degrees in Computer Science and Mathematics from the University of the South. He has given keynote speeches on Analytics and the Presidential Elections, Business Applications of Data Mining, and Data Science for Social Good.

Tom Davenport

Tom Davenport is the President’s Distinguished Professor of Information Technology and Management at Babson College, the co-founder of the International Institute for Analytics, a Fellow of the MIT Initiative on the Digital Economy, and a Senior Advisor to Deloitte Analytics. He teaches analytics and big data in executive programs at Babson, Harvard Business School, MIT Sloan School, and Boston University. He pioneered the concept of “competing on analytics” with his best-selling 2006 Harvard Business Review article.

Professor Davenport has written or edited eighteen books and over 100 articles for Harvard Business Review, Sloan Management Review, the Financial Times, and many other publications. He writes regularly for the online sites of The Wall Street Journal, Fortune, and Harvard Business Review. Tom has been named one of the top three business/technology analysts in the world, one of the 100 most influential people in the IT industry, and one of the world’s top fifty business school professors by Fortune magazine.

Tom earned a Ph.D. from Harvard University in social science and has taught at the Harvard Business School, the University of Chicago, Dartmouth’s Tuck School of Business, Boston University, and the University of Texas at Austin.

Yael Garten

Yael Garten is director of Siri data science and analytics at Apple. Garten is in charge of using data to drive the decision-making for Apple's voice assistant. Using data, Garten's team helps decide how Siri is updated or what new features the program will get. Her job involves crunching enough numbers to make product decisions. She is an acknowledged expert in the field of data science.

Before starting the job in August 2017, Garten was director of data science at LinkedIn, where she worked with data since 2011.

Before joining LinkedIn, Yael was at Stanford University, where she completed her Ph.D. in Biomedical Informatics, focusing on information extraction via natural language processing to understand how human genetic variations impact drug response. Yael advises companies on informatics methodologies to transform high throughput data into insights and is a frequent conference speaker. She has a Ph.D. from Stanford University School of Medicine and MSc from the Weizmann Institute of Science in Israel.

Yasaman Hadjibashi

Yasaman (Yassi) Hadjibashi is a business, data and technology executive. She is currently the Chief Data Officer for Barclays Africa Group, leading the big data transformation across the African continent. She joined Barclays in 2010 and has worked in senior management positions in product innovation and execution across digital and mobile, as well as client/customer experience and design. She has been fundamental in establishing big data capabilities as a group-wide function across Barclays, whilst defining the bank’s next generation Data strategy and driving the execution of a number of key big data initiatives.

As well as delivering on her strong innovation vision for Barclays Africa, Yassi has always had a keen macro-societal lens. Most recently she has launched Africa Success, an initiative which aims to engineer financial success in African youth in underprivileged communities. By combining big data and artificial intelligence, she aims to embed certain identified behaviors within youth, common to financially successful people whom they have surveyed.

She has a Bachelor of Science degree from the University of California, Berkeley.

Ying Li

Dr. Ying Li is Chief Scientist at Giving Tech Labs. Previously she served as the Chief Scientist of Eureka Analytics in Singapore, overseeing the company’s R&D of data science products and AI technologies. Dr. Li’s career has been around building various data science products and services, building and training data science teams, in large corporations and startups.

Dr. Ying Li worked at Microsoft for over 14 years in a variety of roles including Data Scientist for SQL Azure, General Manager for Advertising Division, Privacy Officer for Online Service Division, General Manager for adCenter Labs, Data Mining Manager for Internet Tracking. While at Microsoft, Dr. Li had established the data mining services to MSN businesses worldwide, and was a key founding member of Microsoft’s adCenter business, had built adCenter Labs with close partnership with Microsoft Research.

Dr. Ying Li is the winner of the 2012 ACM SIGKDD award. She has filed and holds over 80 patent applications in the area of data mining, machine learning, computational advertising, software performance optimization, computer program tracing, profiling, and analysis. Ying Li holds B.S. and M.S. degrees in Mathematics from Peking University, Beijing China, and a Ph.D. degree in Computer Science from University of British Columbia, Canada.