Data for Good: Bloomberg and NYC Media Lab team data scientists with nonprofits to solve real world problems
PhD data scientists from across New York City dispatched to nonprofits around the world
Five unique immersions: off campus, out of the lab, and in collaboration with data-driven leadership teams at nonprofits and municipalities around the world
Across universities in New York City, graduate-level data science programs and offerings are growing each year. The field is interdisciplinary and agnostic as its methods, processes and frameworks are applicable to the corporate, nonprofit and public sectors.
It is rare for university-based data science researchers to get their hands on real-world datasets within real-world nonprofit and public sector organizations because these organizations have fewer resources to engage with academia. To offer a new opportunity for nonprofits and public sector organizations to match with university-based data scientists, Bloomberg LP partnered with NYC Media Lab to run an experiment — to provide an immersion day — actually, a few days — for data scientists to work within selected host offices at nonprofits and municipalities around the world. Following a competitive application process across New York City’s campuses, Bloomberg selected five PhD-level data scientists to participate in the Bloomberg Data for Good Exchange (D4GX) Immersion program. $20,000 will be awarded to the participating data scientists. Each nonprofit or municipality has their visiting data scientists exploring a data-driven project brief during the immersion.
Immersion Day is a chance to build connections between budding researchers and non-profit leaders who are starting to figure out their data strategy. NYC Media Lab, with their strong connections in academia were the perfect partners to set this in motion. — Gideon Mann, Head of Data Science, Bloomberg LP
While gaining access to unique data sets at the host organizations, the data scientists are sharing technical assistance and expertise. These interdisciplinary collaborations are intended to help host institutions investigate how emerging fields like computer science, computer engineering, and information systems can aid in realizing social missions. Throughout the Immersion program, the primary focus is to identify beneficial resources, encourage a shared vocabulary between university PhD candidates and nonprofit professionals, and work to uncover best practices for solving data science problems.
Several questions for the immersion include:
- What kinds of data are relevant to civic organizations?
- How can university researchers help create a roadmap or set of suggestions for nonprofits?
- And perhaps most crucial, how can data science be applied to influence social good?
NYC Media Lab is proud to introduce the data scientists who were selected for the immersion program. An overview of each collaboration will be presented at the annual D4GX Conference on Sunday, September 25th 2016, where Bloomberg will invite stakeholders to reflect on potential futures for data-driven governance. The conference will include keynote and workshop sessions regarding economic development, social justice, security, and public service.
The 5 NYC Data Scientists Participating in the Data for Good Exchange Immersion
Xavier Gonzalez, Columbia University
Nonprofit organization host: Benefits Data Trust in Philadelphia, USA
Xavier Ignacio González is a Data Scientist with +15 years of experience in the Industry and Academia.
In Argentina, his home country, he completed an Industrial Engineering Major in the University of Buenos Aires. Before graduation, he started working for big companies like IBM and General Motors. Since then, he has gained business experience in diverse areas such as Operations, Marketing, and Strategic Sales Planning.
After a 2-year assignment to General Motors do Brazil, he became professor of Operations Research in the public University of Buenos Aires, where he also conducts research. His contributions in the fields of Decision Making, Optimization and Agent Based Modeling extend to +20 papers and presentation. He also leads the research project: ‘Big Data in Robust Decision Making in Agriculture Decisions’ founded by Argentine Government.
He received the ‘Argentine Presidential Fellowship Award’ to pursue MS degree in Data Science in Columbia University and the Peruilh Scholarship Award to fund his PhD studies. During his staying in NYC, his team’s projects won the first prize in the ‘MINDS Innovation Challenge’ and the ‘Microsoft API prize’ in the DEVFEST Hackathon.
Nowadays, he works part-time as an independent consultant for the Oil Industry.
Xavier is also a digital art enthusiast. His artistic pieces are frequently published in his Tumblr dashboard, currently with 5 followers but growing.
Anshul Pandey, NYU Tandon School of Engineering
Nonprofit organization host: Benefits Data Trust in Philadelphia, USA
Anshul is a PhD candidate in computer science at New York University — Tandon School of Engineering, specializing in data science and visualization. He has founded several startups, ranging from robotics, e-governance to financial technologies. Currently, he is the co-founder of Accern.com, a big data startup that analyzes unstructured/text web content and identified actionable information to make intelligent investment decisions. Accern serves both institutional and retail traders through products like quantitative data feeds and visual analytics platforms for trading signal discovery. In the past, he has worked extensively on wearable technologies, human computer interaction and natural user interfaces, with projects extensively covered by Wired, Discovery, NewScientist, ExtremeTech, among other media agencies. He has received several awards in the fields of statistics, robotics, data visualization and entrepreneurship.
Travis Riddle, Columbia University
Nonprofit organization host: MakeSense in Mexico City, Mexico
Travis Riddle is a postdoctoral research scientist at Columbia University. Using empirical methods from multiple disciplines, his research examines the causes and consequences of group disparities in education, health, criminal justice, and access to public goods. He developed these interests while pursuing his BA at San Francisco State University, where he was involved in research on stereotype threat — the fear of confirming negative stereotypes about one’s group. Following his undergraduate degree, he completed his PhD at Columbia University, where he conducted research on basic social cognition and perception, developing the computational methodological techniques he uses today.
His recent work focuses on a written educational intervention previously shown to reduce racial and gender disparities in educational achievement. Using text mining techniques, he’s demonstrated that racial and gender groups show fundamental differences in what they write during this intervention. Currently, he’s developing a more robust statistical model to describe the effect of the intervention, and is beginning a new line of work using social media data to examine behavioral and mental health outcomes of group-based macro stressors such as the events of Ferguson in August of 2014. You can find him at www.travisriddle.com or follow him on twitter @triddle42.
Cristian Felix, NYU Tandon School of Engineering
Municipality host: Rio de Janeiro, Brazil
Cristian Felix is a Ph.D. Candidate in Computer Science at New York University, working in the computer and information systems field since 2004. Before joining NYU, he received his bachelor in Information Systems from Makenzie Presbyterian University and worked for 10 years on a non-profit organization, that conducts educational projects in poor communities in Sao Paulo — Brazil, as IT coordinator, managing the user support, infrastructure and software development teams. Also, he worked as web development consultant for a software company for their web CRM system development. At NYU, his research focuses on data visualization techniques for text analysis, researching techniques that allow seamless exploration of unstructured text and associated structured data. Supported by a Knight Foundation Prototype grant, he created a tool that allowed investigative journalists to write stories based on online reviews. His work has also received top honors on the United Nations #VisualizeChange Challenge, being featured on the global consultation for the World Humanitarian Summit in Geneva. Currently, he is expanding his research on visual text analysis, investigating additional aspects like text streaming and visual keyword-based text summaries.
Agustín Indaco, CUNY Graduate Center
Municipality host: Miami, USA
Agustín Indaco is a Ph.D. student in Economics at CUNY, The Graduate Center. His research interests lie in the intersection of applied econometrics, big data, and labor economics. He is particularly interested in exploring ways in which we can study economic behavior through data collected from social media. Prior to his graduate studies, he was a Junior Professional Associate at The World Bank, where he worked in the Poverty Reduction and Economic Management unit for Latin America. Agustín is a research fellow for Dr. Lev Manovich at the Software Studies Initiative, where he launched the Inequaligram project. He is also a research assistant for a National Science Foundation funded project studying the economic impact of high-skilled immigration in the US. Agustín has worked as an adjunct professor at City Tech College and as a consultant at The World Bank. He is also a columnist for El Economista, an economic newspaper in Argentina.
Please contact Amy Chen (firstname.lastname@example.org), Manager of Partnerships at NYC Media Lab, with any questions about this program.
Use #D4GX on social media to join the Data for Good Exchange conversation.