Wikipedia

Rayid Ghani

Rayid Ghani is a Distinguished Career Professor in the Machine Learning Department (in the School of Computer Science) and the Heinz College of Information Systems and Public Policy at Carnegie Mellon University. Previously, he was the director of the Center for Data Science and Public Policy, research associate professor in the department of computer science, and a senior fellow at the Harris School of Public Policy at the University of Chicago. He was also the co-founder of Edgeflip, an analytics startup that grew out of the Obama 2012 Campaign, focused on social media products for non-profits, advocacy groups, and charities. Recently, it was announced that he will be leaving the University of Chicago and joining Carnegie Mellon University's School of Computer Science and Heinz College of Information Systems and Public Policy.[1]

Rayid Ghani
Born1977 (age 46–47)
Karachi, Pakistan
Alma materUniversity of the South, TN
Carnegie Mellon University, PA
Scientific career
FieldsComputer Science, Machine learning, Data science, Artificial Intelligence, Social Good, Public Policy
InstitutionsCarnegie Mellon University

Ghani started and runs the Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship.[2][3] He's also the co-founder of Coleridge Initiative, a nonprofit organization working with governments to ensure that data and evidence is used more effectively for policymaking.

Education and career edit

Ghani completed his schooling at the Karachi Grammar School, in Karachi, Pakistan.[4] Ghani completed his graduate studies in the machine learning department at Carnegie Mellon University with Tom M. Mitchell on machine learning and text classification and received his undergraduate degrees in computer science and mathematics from University of the South.

Before his role at the University of Chicago, he was the chief scientist of the Obama 2012 Campaign.[5][6] Before that, he was a senior research scientist and director of analytics research at Accenture Labs, where he led a technology research team focused on applied R&D in analytics, machine learning, and data mining for large-scale and emerging business problems.

Policy efforts edit

Ghani has been actively working with government agencies and non-profits on designing AI and Machine Learning Systems to help tackle societal problems in public health,[7] criminal justice,[8] social services,[9] education,[10] economic development, and workforce development[11]

He has also testified in front of the US Senate (Testimony) and the US House of Representatives (Testimony) on AI Governance and Regulation.

Research contributions edit

Ghani's research focuses on developing and applying machine learning, data science, and artificial intelligence methods to large-scale social problems in areas such as education, healthcare, economic development, criminal justice, energy, transportation, and public safety.[12] His work has previously focused on text analytics,[13] fundraising, volunteer, and voter mobilization[14] using analytics, social media,[15] and machine learning.,[16][17] and data mining.[18] Rayid's research contributions have been in the areas of text mining, co-training, active learning, consumer behavior modeling,[19] and fraud detection.

He has given keynote speeches on Analytics and the Presidential Elections (for example at Predictive Analytics World,[20] Digital Leaders Forum,[21] Carnegie Mellon University,[22] and CeBIT Australia[23][24]), on Business Applications of Data Mining,[25] and Data Science for Social Good.

Selected publications edit

  • Big Data and Social Science: A Practical Guide to Methods and Tools. Editors: Ian Foster, Rayid Ghani, Ron Jarmin, Frauke Kreuter, Julia Lane. CRC Press 2016.
  • Data Mining for Business Applications. Editors: Carlos Soares, Rayid Ghani. Book. IOS Press 2010.
  • Mining the Web to Add Semantics to Retail Data Mining. R. Ghani. Invited Paper. Web Mining: From Web to Semantic Web. Springer Lecture Notes in Artificial Intelligence, Vol. 3209. Berendt, B.; Hotho, A.; Mladenic, D.; van Someren, M.; Spiliopoulou, M.; Stumme, G. (Eds.) 2004

References edit

  1. ^ "Rayid Ghani, Pioneer in Applying AI to Social Issues, Joins Carnegie Mellon".
  2. ^ "Eric and Wendy Schmidt Data Science for Social Good Summer Fellowship".
  3. ^ Kaye, Kate (2013-04-16). "Obama's Data Scientist Runs Social Good Program | DataWorks - Advertising Age". Adage.com. Retrieved 2013-07-07.
  4. ^ Haqqi, Salman (21 January 2013). "'Obama's secret weapon in re-election: Pakistani scientist Rayid Ghani'". Dawn.com. Retrieved 21 Feb 2015.
  5. ^ Tim Murphy. "Meet Obama's Digital Gurus". Mother Jones. Retrieved 2013-07-07.
  6. ^ Scherer, Michael (2012-11-07). "Obama Wins: How Chicago's Data-Driven Campaign Triumphed | TIME.com". Swampland.time.com. Retrieved 2013-07-07.
  7. ^ Potash, Eric; Ghani, Rayid; Walsh, Joe; Jorgensen, Emile; Lohff, Cortland; Prachand, Nik; Mansour, Raed (2020-09-01). "Validation of a Machine Learning Model to Predict Childhood Lead Poisoning". JAMA Network Open. 3 (9): e2012734. doi:10.1001/jamanetworkopen.2020.12734. ISSN 2574-3805. PMC 7495240. PMID 32936296.
  8. ^ Bauman, Matthew J.; Boxer, Kate S.; Lin, Tzu-Yun; Salomon, Erika; Naveed, Hareem; Haynes, Lauren; Walsh, Joe; Helsby, Jen; Yoder, Steve; Sullivan, Robert; Schneweis, Chris; Ghani, Rayid (2018-06-20). "Reducing Incarceration through Prioritized Interventions". Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies. COMPASS '18. New York, NY, USA: Association for Computing Machinery. pp. 1–8. doi:10.1145/3209811.3209869. ISBN 978-1-4503-5816-3. S2CID 49349834.
  9. ^ "Reducing the Risk of Homelessness through Prioritized Distribution of Rental Assistance Resources". 2022-07-13. Retrieved 2023-09-20.
  10. ^ Lakkaraju, Himabindu; Aguiar, Everaldo; Shan, Carl; Miller, David; Bhanpuri, Nasir; Ghani, Rayid; Addison, Kecia L. (2015-08-10). "A Machine Learning Framework to Identify Students at Risk of Adverse Academic Outcomes". Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. KDD '15. New York, NY, USA: Association for Computing Machinery. pp. 1909–1918. doi:10.1145/2783258.2788620. ISBN 978-1-4503-3664-2. S2CID 207227441.
  11. ^ Zejnilovic, Leid; Lavado, Susana; Soares, Carlos; Martínez De Rituerto De Troya, Íñigo; Bell, Andrew; Ghani, Rayid (August 2021). "Machine Learning Informed Decision-Making with Interpreted Model's Outputs: A Field Intervention". Academy of Management Proceedings. 2021 (1): 15424. doi:10.5465/AMBPP.2021.264. ISSN 0065-0668. S2CID 238773301.
  12. ^ "What the Obama Campaign's Chief Data Scientist Is Up to Now - Alexis C. Madrigal". The Atlantic. 8 May 2013. Retrieved 2013-07-07.
  13. ^ Issenberg, Sasha (13 January 2012). "Project Dreamcatcher: How cutting-edge text analytics can help the Obama campaign determine voters' hopes and fears. - Slate Magazine". Slate.com. Retrieved 2013-07-07.
  14. ^ "Data-Crunched Democracy". Annenberg School for Communication, University of Pennsylvania.
  15. ^ Alter, Jonathan (2013). The Center Holds: Obama and His Enemies|Simon and Schuster. Simon and Schuster. p. 107. ISBN 978-1451646078.
  16. ^ Johnson, Geoffrey (2012-07-24). "Can Obama Data-Mine His Way to Victory?". Chicagomag.com. Retrieved 2013-07-07.
  17. ^ Rutenberg, Jim; Zeleny, Jeff (2012-03-08). "Obama Campaign's Vast Effort to Re-Enlist '08 Supporters". The New York Times.
  18. ^ "Rayid Ghani - Google Scholar Citations". Retrieved 2013-07-07.
  19. ^ Baker, Stephen (2009). The Numerati. Houghton Mifflin Harcourt. pp. 44–64. ISBN 978-0618784608. Rayid.
  20. ^ "Predictive Analytics World 2013".
  21. ^ "Digital Leaders Annual Lecture". Archived from the original on 2013-07-24.
  22. ^ "Carnegie Mellon University Machine Learning Distinguished Seminar Series".
  23. ^ Taylor, Josh (2013-05-27). "Compulsory voting changes Australia election data game: Obama's data scientist".
  24. ^ Tadros, Edmund (2013-05-30). "Obama's election data guru says how the Labor and Liberal campaigns are getting it right – and wrong". Financial Review.
  25. ^ "Interactive Data mining and Business Applications". ACM KDD Conference.

External links edit


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