We believe that students need to hear from a wide array of perspectives to be successful data scientists. The faculty in the program are experts, appointed from across the world to provide a comprehensive experience across different fields and industries. Our faculty and advisors are leaders in the industry with professional and academic backgrounds in the field of data science.
Alessandro worked as a data scientist for both Path and Glassdoor, where he analyzed terabytes of customer activity logs to provide insights for product development. He also applied machine learning to user-generated content such as salaries and reviews. He received a BA in Computer Science from UCSC and MS in Behavioral & Neural Science at Rutgers University. He taught statistics, psychology, and neuroscience at Lehman College of the City of New York, Notre Dame de Namur University, the California Institute of Integral Studies, and the University of San Francisco, the last of which awarded him the Innovation in Teaching Award in 2011.
Program Director & Visiting Scholar
Having served as a principal data scientist and economist, Nir is experienced in leading teams to deliver industry applications and creating value. Nir was the lead instructor for data science at General Assembly, a scholar in the Economics Department at the University of California, Berkeley, and an independent data science consultant. Nir completed PhD coursework in Economics, with application to Industrial Organizations, Finance and Marketing at the University of California, Berkeley. He holds a BA in Economics and Business Administration from the IDC Herzliya, Israel.
Visiting Assistant Professor
Jared is an interdisciplinary scientist with years of experience applying methods of machine learning and simulation to diverse problems in computational biology, including protein structure and dynamics, drug design, and cell circuit analysis.Jared acts as a technological advisor to a number of startup companies and maintains active research in the development and application of unsupervised machine learning methods. He has been an educator of scientists and medical professionals for over ten years and takes great pleasure in seeing his students succeed. He received his PhD in Computational and Theoretical Biophysical Chemistry from Purdue University.
Visiting Assistant Professor
Brian has taught statistics at both the undergraduate and graduate level for over 10 years. He received his PhD in Cognitive Neuroscience from the University of California, Santa Barbara in 2009. He was a post-doctoral research associate fellow and lecturer at Colorado State University and The University of Maryland. He was named a Maryland Neuroimaging Center Summer Institute Fellow in 2013 for his work in the statistical analysis of large-scale fMRI (functional magnetic resonance imaging) data.His academic research used mathematics and computer programming to better understand the human brain and behavior. More recently, he has been working as a data scientist building scalable machine learning solutions and leading analytic teams. He is active in the San Francisco data science community through volunteering, mentoring and organizing talks.
Amy received a MA in Statistics from Harvard University where she taught statistics at Harvard University for over four years, and she is passionate about making statistics accessible, understandable and useful for everyone. Previously, she was part of a startup team at the Harvard Innovation Lab, developing quantitative analysis application for non-statisticians.
Donatella earned her bachelor’s degree in Economics and Finance and master’s degree in Financial Markets and Institutions at the University of Bologna, Italy. She then earned her PhD in Finance, Financial Markets, and Institutions in the Department of Business and Economics of Bologna, Italy. During her graduate studies, Donatella worked as a visiting scholar at the Westminster Business School in London, Stern School of Business at New York University, and Haas School of Business at the University of California, Berkeley. Donatella is currently a lecturer at Haas School of Business and at the Fung Institute for Engineering Leadership at the University of California and a faculty member at Hult International Business School in San Francisco.
Dr. Michael (Mike) Bowles holds a bachelor’s and master’s degrees in Mechanical Engineering from Oklahoma State University, an MBA from the University of California, Los Angles, and a ScD in Instrumentation from Massachusetts Institute of Technology. He has worked in academia, technology and business. Mike currently works with startup companies where machine learning is integral to success. He serves variously as part of the management team, a consultant or advisor. He also teaches machine learning courses at Hacker Dojo, a co-working space and startup incubator Mountain View, Calif. After working as a construction engineer in Southeast Asia, he went to Cambridge for ScD and then held the C. Stark Draper Chair at MIT after graduation. Mike left Massachusetts to work on communications satellites at Hughes Aircraft Company in Southern California. After completing an MBA at UCLA, Mike moved to the San Francisco area to accept positions as founder and CEO of two successful venture backed startups.
Director of Admissions & Enrollment
Molly has worked in education for over 8 years. She started out as a 4th grade teacher in NYC, and has worked in a variety of education and non-profit roles since. At Galvanize, she runs the admissions process for all of our education programs.
Prior to Galvanize, Bonny advised New York University's Program Board, and worked in NYU's MBA Admissions and Graduate Financial Aid. Additionally, Bonny served as Director of Operations at the Institute for China-US Law & Policy Studies, where she work closely with the leadership at Peking University's School of Transnational Law. Bonny holds a bachelor's in psychology from the University of San Francisco, and a master's degree in Higher Education from New York University.
Paco Nathan, is a "player/coach" who has led innovative Data teams building large-scale apps for several years. He has expertise in distributed systems, machine learning, functional programming, and cloud computing, and is an O'Reilly author, Apache Spark open source evangelist with Databricks, and an advisor for Amplify Partners and GalvanizeU. He received his BS Math Sci and MS Comp Sci degrees from Stanford University, and has 30+ years technology industry experience ranging from Bell Labs to early-stage start-ups.
Lyle Ungar is a Professor of Computer and Information Science at the University of Pennsylvania. He received a B.S. from Stanford University and a Ph.D. from MIT. Dr. Ungar directed Penn's Executive Masters of Technology Management (EMTM) Program for a decade, and served as Associate Director of the Penn Center for BioInformatics (PCBI). He has published over 200 articles and holds eleven patents. His current research focuses on statistical natural language processing, spectral methods, and the use of social media to understand the psychology of individuals and communities.
Alexy Khrabrov is a computer scientist working at the intersection of startups, “big" data, and functional programming. Alexy founded Scala for Startups, a meetup in San Francisco focused on doing more startups with fewer but more effective people, and merged SF Scala with it to grow the largest Scala meetup in the world, sfscala.org. He was early adopter of Apache Spark, which he used at Klout, and a co-founder of the Spark Users meetup, spun off of the Scala for Startups and now one of the largest meetups in technology. Alexy founded and runs SF Scala yearly conference, called Scala By the Bay (scala.bythebay.io), and organizes new conferences on applied Natural Language Processing (text.bythebay.io) and Big Data Scala (bigdatascala.org).
Adam Gibson is the co-founder of Skymind, an enterprise deep-learning and NLP firm, and creator of the distributed, open-source frameworks Deeplearning4j.org and ND4J.org. Adam has taught machine-learning at Zipfian Academy and is currently deep-learning specialist in residence at GalvanizeU. Adam is the author of the forthcoming O'Reilly book “DeepLearning: A Practicioner's Approach”