Committees

Effective Leadership through Diversity

“At the AI for Good Foundation, we strive to reach rational conclusions and take decisive action to tackle some of the world’s biggest challenges. That involves the AI research community, industry, policy makers, non-profits, and the interested public everywhere.”

–James Hodson, Executive Director

Committees are formed of members who are chosen by the Executive Director, or by consensus of the Board of Directors, to meet regularly and fulfill a particular mission. Some committees are temporary, to manage conferences or specific grants, while others are standing committees whose function endures.

Steering Committee

(Created by order of the Executive Director, April 27th, 2016)

The steering committee is responsible for reviewing the actions of the AI for Good Foundation, identifying opportunities, facilitating access to the right people at the right time, and providing guidance on strategic matters.

Damian Borth

Dr. Damian Borth is the Director of the Deep Learning Competence Center at the German Research Center for Artificial Intelligence (DFKI) in Kaiserslautern and founding co-director of Sociovestix Labs, a social enterprise in the area of financial data science.

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Damian’s research focuses on large-scale multimedia opinion mining applying machine learning and in particular deep learning to mine insights (trends, sentiment) from online media streams.

His work has been awarded by the Best Paper Award at ACM ICMR 2012, the McKinsey Business Technology Award 2011, and a Google Research Award in 2010. Damian currently serves as a member of the assessment committee for the Investment Innovation Benchmark (IIB) and several other steering- and program committees of international conferences and workshops organized by the Association of Computing Machinery (ACM). He actively promotes the use of multimedia opinion mining for social good following the UN Principles for Responsible Investment (PRI) and the AI-for-Good initiative.


Rayid Ghani

Rayid Ghani is the Director of the Center for Data Science and Public Policy, Chief Data Scientist at the Urban Center on Computation and Data, Research Director at the Computation Institute (a joint institute of Argonne National Laboratory and The University of Chicago), and a Senior Fellow at the Harris School of Public Policy at the University of Chicago.

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Ghani is currently in charge of the Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship at the University of Chicago.


Marko Grobelnik

Marko Grobelnik has worked on various aspects of AI since 1985. His focused areas of expertise are Machine Learning, Data/Text/Web Mining, Network Analysis, Semantic Technologies, Deep Text Understanding, and Data Visualization. Marko works as a researcher in AI Lab at Jozef Stefan Institute and is the CEO of Quintelligence.com specialized in solving complex AI problems for the commercial world.

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He collaborates with major European academic institutions and industries such as Bloomberg, British Telecom, European Commission, Microsoft Research, New York Times. Marko is also co-author of several books, co-founder of several start-ups and is/was involved into over 40 EU funded research projects on various fields of AI.


Estevam Rafael Hruschka Junior

Estevam R. Hruschka Jr. is co-leader of the Carnegie Mellon Read the Web project –http://rtw.ml.cmu.edu/rtw/people), and the head of the Machine Learning Lab (MaLL) at Federal University of Sao Carlos (UFSCar), in Brazil. He is also adjunct professor in the Machine Learning Department at Carnegie Mellon University, USA, and associate professor at UFSCar, Brazil.

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Estevam has been ”young research fellow” at FAPESP (Sao Paulo state research agency, Brazil) and, currently, he is ”research fellow” at CNPq (Brazilian research agency). His main research interests are never-ending learning, machine learning, probabilistic graphical models, natural language understanding, data mining and Big Data. Since 1997, he has been working on data science with many international research teams, collaborating with research groups from companies and universities.


Claudia Perlich

Claudia Perlich leads the machine learning efforts that power Dstillery’s digital intelligence for marketers and media companies. With more than 50 published scientific articles, she is a widely acclaimed expert on big data and machine learning applications, and an active speaker at data science and marketing conferences around the world.

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Claudia is the past winner of the Advertising Research Foundation’s (ARF) Grand Innovation Award and has been selected for Crain’s New York’s 40 Under 40 list, Wired Magazine’s Smart List, and Fast Company’s 100 Most Creative People.

Claudia holds multiple patents in machine learning.  She has won many data mining competitions and awards at Knowledge Discovery and Data Mining (KDD) conferences, and served as the organization’s General Chair in 2014.

Prior to joining Dstillery in 2010, Claudia worked at IBM’s Watson Research Center, focusing on data analytics and machine learning.  She holds a PhD in Information Systems from New York University (where she continues to teach at the Stern School of Business), and an MA in Computer Science from the University of Colorado.