Big Data Program Advisory Committee
The Certificate in Big Data at the SJSU School of Information is governed by a Program Advisory Committee (PAC), including representatives from higher education, business, and industry. The PAC members provide input on program development, review course content and learning outcomes, identify job opportunities, advise on technology advances, and keep a watchful eye on emerging trends. Their service on the committee benefits future data scientists and analytical talent, as well as helps to shape the Big Data industry.
Natasha Balac, PhD, is the president and CEO of Data Insight Discovery, Inc. Balac has a track record of enabling businesses to discover actionable insight from vast amounts of data. Her work has spanned clients in a variety of industries for companies ranging in size from Fortune 100 companies to start-ups. Balac has founded and served as the director of Predictive Analytics Center of Excellence (PACE) at San Diego Supercomputer Center for the past five years. During her tenure at PACE she has shown a proven record of excellence in information technology planning, management and deployment across many verticals including collaborations with the School of Medicine, Smart Energy Grid, and Medicaid fraud detection to Smart City and Big Data Applications. Balac has made great impact through application of her data-intensive expertise and resources to help create the next generation of data scientists by leading a collaborative, nationwide education and training effort among academia, industry, and government. Her ongoing and recent projects with industry and government are especially focused on mining Big Data using high performance IT. Balac has presented at numerous invited presentations, conferences and meetings in the area of Big Data, Smart City and sustainability. In 2015 she has been recognized at the White House Office of Science and Technology Policy: Data to Knowledge to Action: Building New Partnerships’ launch partner recognition for the Sustainable Communities – Smart San Diego project. Balac has received her Master's and Ph.D. in Computer Science from Vanderbilt University with an emphasis in Machine Learning and Data Mining from large data sets.
Wendy Kan, PhD, is a data scientist at Kaggle, the largest global data science community. Kan is experienced in working with many companies in many industries, including Facebook, Genentech, Airbnb, Expedia, Yelp, and CERN, to solve their data science problems. She was a software engineer and researcher before joining Kaggle. She holds B.S. and M.S. degrees in Electrical Engineering from National Tsing Hua University and Ph.D. in Biomedical Engineering from The University of Texas at Austin.
Glen Mules received his B.S. in Mathematics from the University of Adelaide, South Australia, a Diplôme d’Université de Phonétique Appliquée à la Langue Française, Paris 3-Sorbonne, France, an M.S. in Computer Science from the University of Birmingham, U.K., and a Ph.D. in Education from Walden University, Minneapolis, MN., where his dissertation was "Instructor Perceptions of Delivering Meaningful and Effective Training in a Corporate Environment.” Mules has 40 years of experience in various roles in information technology, including systems programming and development, national and international standards for data interchange, management consulting, and corporate technical training—most recently working at Informix Software and IBM. He worked as a corporate technology instructor and course developer in Information Management and Data Analytics at IBM Corporation, from where he retired in 2015. He is a certified IBM Big Data Engineer and a certified IBM Big Data Architect. His research interests include big data and the Hadoop ecosystem, relational database systems, and data analytics. He is an adjunct professor in Computer Science at Iona College.
Jike Chong, PhD, is the chief data scientist of Yirendai (NYSE:YRD), the first online P2P lending company from China that is publicly listed on NYSE, where he is focusing on using data science to build trust between strangers. Prior to Yirendai, Chong established and headed the data science division at Simply Hired, a leading job search engine in Silicon Valley, with over 30 million unique visitors each month, serving job seekers in 24 countries. While at Simply Hired, he was invited to the White House multiple times to advise the U.S. Department of Labor and the White House Office of Science and Technology Policy on the design of big data related products for reducing unemployment. From 2011 to 2012, Chong led quantitative risk analytics at Silver Lake Kraftwerk, responsible for applying big data techniques to risk analysis of venture investment projects in the Kraftwerk fund.
Since 2010, Chong has been an adjunct professor and PhD advisor at Electrical and Computer Engineering at Carnegie Mellon University, where he established the CUDA Research Center and CUDA Teaching Center and has served as a co-director of these centers since their inception. Chong received his bachelor’s and master’s degrees in electrical and computer engineering from Carnegie Mellon University and a Ph.D. from University of California, Berkeley under Professor Kurt Keutzer. He holds eight US patents (five granted, three pending).
Jennifer Roth is the director for higher education at Splunk, the leading platform for operational intelligence. Splunk enables users to collect, analyze, and act upon the untapped value of big data generated by technology infrastructure, security systems, and business applications. In her role at Splunk, Roth leads the go to market strategy across the US higher education sector, and works closely with higher education institutions and education-focused technology partners to structure solutions and programs geared toward helping institutions unlock the power within the wealth of machine data that exists across today’s modern campus environment. Roth has 17 years of experience in the education technology and data analytics/big data sector and works frequently with institutions to help develop and foster recruiting and internship programs, and programs that aid in integrating big data/data science into the curriculum.