As data proliferates and becomes more freely available, the power of driving impact in social sector increases.
See the many ways organizations are applying their data science infrastructure in the name of making the world a better place.
Learn through stories of success and failures, and core practices that are implemented by change makers in the social sector that can differ from industry and academia.
Get exposed to data science & Machine learning workflows and models being utilized steered towards causes like climate change, agriculture, socio-economic impacts, disaster management etc.
Dr. Lisa Amini is the Director of IBM Research Cambridge, which is also home to the MIT-IBM Watson AI Lab, and of IBM’s AI Horizons Network. Lisa was previously Director of Knowledge & Reasoning Research in the Cognitive Computing group at IBM’s TJ Watson Research Center in New York, and she is also an IBM Distinguished Engineer. Lisa was the founding Director of IBM Research Ireland, and the first woman Lab Director for an IBM Research Global (i.e., non-US) Lab (2010-2013). In this role she developed the strategy and led researchers in advancing science and technology for intelligent urban and environmental systems (Smarter Cities), with a focus on creating analytics, optimizations, and systems for sustainable energy, constrained resources (e.g., urban water management), transportation, and the linked open data systems that assimilate and share data and models for these domains. She earned her PhD degree in Computer Science from Columbia University.
Chief Strategy Officer, Professor of Computer ScienceTrifacta, Berkeley
Joe Hellerstein, PhD
Joseph M. Hellerstein is the Jim Gray Professor of Computer Science at the University of California, Berkeley, whose work focuses on data-centric systems and the way they drive computing. He is an ACM Fellow, an Alfred P. Sloan Research Fellow and the recipient of three ACM-SIGMOD “Test of Time” awards for his research. Fortune Magazine has included him in their list of 50 smartest people in technology , and MIT’s Technology Review magazine included his work on their TR10 list of the 10 technologies “most likely to change our world”. Hellerstein is the co-founder and Chief Strategy Officer of Trifacta, a software vendor providing intelligent interactive solutions to the messy problem of wrangling data. He has served on the technical advisory boards of a number of computing and Internet companies including Dell EMC, SurveyMonkey, Captricity, and Datometry, and previously served as the Director of Intel Research, Berkeley.
Vida Williams is a revered leader in the tech space. She currently serves as the Head of Data at SingleStone, and was recently named the company’s Chief Diversity Officer as an intentional approach towards mitigating bias in the Data and Technology industries. Vida is also a professor and Innovator in Resident at Virginia Commonwealth University, a gubernatorial appointee and co-chair of the Virginia Biotechnology Research Partnership Authority, and an impassioned activist for data privacy. She has contributed to TedX, TomTom Festival, The Frontier Partners, and countless client presentations. Vida also volunteers her data expertise to non-profits, offering free workshops and consulting. She leads organizations through exercises that help them to identify areas of improvement, new and better ways of showcasing their impact on the community, and how to use their data to foster growth.
Executive DirectorHuman Rights Data Analysis Group
Megan Price, PhD
As the Executive Director of the Human Rights Data Analysis Group, Megan Price designs strategies and methods for statistical analysis of human rights data for projects in a variety of locations including Guatemala, Colombia, and Syria. Her work in Guatemala includes serving as the lead statistician on a project in which she analyzed documents from the National Police Archive; she has also contributed analyses submitted as evidence in two court cases in Guatemala. Her work in Syria includes serving as the lead statistician and author on three reports, commissioned by the Office of the United Nations High Commissioner of Human Rights (OHCHR), on documented deaths in that country. Megan is a member of the Technical Advisory Board for the Office of the Prosecutor at the International Criminal Court and a Research Fellow at the Carnegie Mellon University Center for Human Rights Science. She is the Human Rights Editor for the Statistical Journal of the International Association for Official Statistics (IAOS) and on the editorial board of Significance Magazine. She earned her doctorate in biostatistics and a Certificate in Human Rights from the Rollins School of Public Health at Emory University. She also holds a master of science degree and bachelor of science degree in Statistics from Case Western Reserve University.
Machine Learning Researcher and Vanier Doctoral ScholarMila and McGill University
Charles Onu, PhD
Charles is a PhD candidate at McGill University and Mila – the Québec AI Institute. He is interested in the design and development of improved diagnostic and decision-making tools in healthcare. He leads the Ubenwa Health, a collaboration between researchers in Canada and Nigeria, developing low-cost, AI-powered mobile app for the diagnosis of perinatal asphyxia from the infant cry. At the Montreal Children’s Hospital, Charles is involved in the APEX project, where he has been developing machine learning algorithms for analyzing cardiorespiratory behaviour of preterm newborns in order to determine their readiness for extubation. He has worked with Health Experiences Research Canada contributing to the design and leading the development of the HERS mobile app – a personalized recommendation tool for breast cancer patients. Charles is a Jeanne Sauvé Fellow and a Vanier Doctoral Scholar.
Dr. Oren Etzioni has served as the Chief Executive Officer of the Allen Institute for AI (AI2) since its inception in 2014. He has been a Professor at the University of Washington’s Computer Science department since 1991, and a Venture Partner at the Madrona Venture Group since 2000. He has garnered several awards including Seattle’s Geek of the Year (2013), the Robert Engelmore Memorial Award (2007), the IJCAI Distinguished Paper Award (2005), AAAI Fellow (2003), and a National Young Investigator Award (1993). He has been the founder or co-founder of several companies, including Farecast (sold to Microsoft in 2008) and Decide (sold to eBay in 2013). He has written commentary on AI for The New York Times, Nature, Wired, and the MIT Technology Review. He helped to pioneer meta-search (1994), online comparison shopping (1996), machine reading (2006), and Open Information Extraction (2007). He has authored over 100 technical papers that have garnered over 2,000 highly influential citations on Semantic Scholar. He received his Ph.D. from Carnegie Mellon in 1991 and his B.A. from Harvard in 1986.
Boeing Assistant Professor of Aeronautics and AstronauticsMIT
Julie A. Shah, PhD
Julie Shah is an Associate Professor in the Department of Aeronautics and Astronautics at MIT and leads the Interactive Robotics Group of the Computer Science and Artificial Intelligence Laboratory. Shah received her SB (2004) and SM (2006) from the Department of Aeronautics and Astronautics at MIT, and her PhD (2010) in Autonomous Systems from MIT. Before joining the faculty, she worked at Boeing Research and Technology on robotics applications for aerospace manufacturing. She has developed innovative methods for enabling fluid human-robot teamwork in time-critical, safety-critical domains, ranging from manufacturing to surgery to space exploration. Her group draws on expertise in artificial intelligence, human factors, and systems engineering to develop interactive robots that emulate the qualities of effective human team members to improve the efficiency of human-robot teamwork. In 2014, Shah was recognized with an NSF CAREER award for her work on “Human-aware Autonomy for Team-oriented Environments,” and by the MIT Technology Review TR35 list as one of the world’s top innovators under the age of 35. Her work on industrial human-robot collaboration was also recognized by the Technology Review as one of the 10 Breakthrough Technologies of 2013, and she has received international recognition in the form of best paper awards and nominations from the International Conference on Automated Planning and Scheduling, the American Institute of Aeronautics and Astronautics, the IEEE/ACM International Conference on Human-Robot Interaction, the International Symposium on Robotics, and the Human Factors and Ergonomics Society.
Director of Applied Statistics CenterColumbia University
Andrew Gelman, PhD
Andrew Gelman is a professor of statistics and political science and director of the Applied Statistics Center at Columbia University. He has received the Outstanding Statistical Application award from the American Statistical Association, the award for best article published in the American Political Science Review, and the Council of Presidents of Statistical Societies award for outstanding contributions by a person under the age of 40. His books include Bayesian Data Analysis (with John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Don Rubin), Teaching Statistics: A Bag of Tricks (with Deb Nolan), Data Analysis Using Regression and Multilevel/Hierarchical Models (with Jennifer Hill), Red State, Blue State, Rich State, Poor State: Why Americans Vote the Way They Do (with David Park, Boris Shor, and Jeronimo Cortina), and A Quantitative Tour of the Social Sciences (co-edited with Jeronimo Cortina). Andrew has done research on a wide range of topics, including: why it is rational to vote; why campaign polls are so variable when elections are so predictable; why redistricting is good for democracy; reversals of death sentences; police stops in New York City, the statistical challenges of estimating small effects; the probability that your vote will be decisive; seats and votes in Congress; social network structure; arsenic in Bangladesh; radon in your basement; toxicology; medical imaging; and methods in surveys, experimental design, statistical inference, computation, and graphics.
Chief Data Evangelist, Director of Data ScienceCisco Systems Inc.
Jennifer Redmon
Jennifer Redmon joined Cisco in 2009 and serves as its, and industry’s 1st, Chief Data & Analytics Evangelist as well as sits on Forbes’ Technology Council. Jennifer is a leader in developing data-driven cultures and organizational analytical maturity through qualitative and quantitative methods. Her approach to fostering a data-driven workforce is taught at multiple higher ed. institutions around the world. Jennifer is passionate about giving back and consequently, founded Cisco’s Data Science and AI for Good initiative. She leads the company’s award-winning Data Science and AI for Suicide Prevention Team, which, inspired by and in collaboration with WHO researchers, focus on de-stigmatizing mental illness through cultural change. Her authorship focuses on data- and analytics-driven cultures, mental health in the workplace, suicide prevention, as well as innovative applications of data science and AI including social good. Jennifer holds an international MBA from Duke University with a concentration in Strategy, Bachelor’s Degrees in Economics and Art History from UC Davis, is in Georgia Tech’s Master of Science in Analytics Spring 2021 class, and is a certified Suicide First Responder.
Annie is a leader in data science with over a decade of industry experience spanning corporate research and startups. Currently, she is the head of the Cisco Data Science Lab in Vancouver. Coming from a research background with a PhD in Computer Science from McGill, Annie is a former Research Scientist at IBM T. J. Watson Research Center in New York and a two-time winner of an ACM Distinguished Paper Award (both in applying data science to software engineering) with five patents (granted and applied). Annie is active in the data science community as a Meetup organizer (Data Science for Social Good), speaker, and mentor.
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