Rediet Abebe

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Rediet Abebe
Born
Rediet Abebe

1991 (age 27–28)
ResidenceCambridge, Massachusetts, United States
Alma materCornell University (Ph.D., M.S.)
Harvard University (M.S., B.A.)
University of Cambridge (M.A.)
Known forMechanism Design for Social Good (MD4SG)
AI for social good
AwardsHarvard Society of Fellows (2019)
MIT Technology Review Innovators Under 35 (2019)
Scientific career
Fieldsartificial intelligence
algorithms
computer science
inequality
InstitutionsHarvard University
Cornell University
University of Cambridge
Microsoft Research
Doctoral advisorJon M. Kleinberg
Websitewww.cs.cornell.edu/~red/
md4sg.com

Rediet Abebe (Amharic: ረድኤት አበበ) is an Ethiopian computer scientist working in the fields of algorithms and artificial intelligence. She is a Junior Fellow at the Harvard Society of Fellows.[1] She is the sixth computer scientist and first woman computer scientist to be inducted into the Society.[2] Her research uses algorithms and AI to mitigate socioeconomic inequality.[3] She co-founded of Mechanism Design for Social Good (MD4SG), a multi-institutional and interdisciplinary research initiative working to improve access to opportunity for historically disadvantaged communities.[4] She is also an advocate for diversity and inclusion in computing and is the co-founder for Black in AI, non-profit organisation that supports and promotes Black individuals working in the field of AI.[5]

Early life and education[edit]

Abebe was born and raised in Addis Ababa, Ethiopia.[6] She was educated in the Ethiopian National Curriculum before winning a merit-based scholarship awarded to four students from the country to attend the International Community School of Addis Ababa when she was in eighth grade.[7] When she moved to the United States to start college in 2009, she was surprised to learn about the educational inequalities that Black, low-income, and other disadvantaged students face in the United States.[8]

Abebe joined Harvard University where she earned a Bachelor of Arts degree in mathematics and later a Master of Science degree in applied mathematics. As an undergraduate, she worked with Michael J. Hopkins and Richard P. Stanley on combinatorics, writing her thesis on Plethysm of Schur Functions and Irreducible Polynomial Representations of the Complex General Linear Group.[9] In addition to her undergraduate studies, she authored more than 50 articles in the Harvard Crimson on topics related to the Cambridge Public School District and other issues facing Cambridge, Massachusetts.[10] She also authored research papers in mathematics, physics, and public health.[11][12] Her JAMA Internal Medicine publication on breast cancer screening was ranked 79 in the Altmetric Top 100 in 2015[13] and was covered by outlets including the Huffington Post, FiveThirtyEight, Forbes, US News, the Washington Post, the New Yorker, NPR, L.A. Times, MinnPost, the Baltimore Sun, and other outlets.[14][15][16][17][18][19][20][21][22] She completed an M.S. in applied mathematics from Harvard SEAS, conducting research with David C. Parkes.[23]

After college, she attended the University of Cambridge as a Harvard-Cambridge scholar. [24] She lived in Pembroke College as the Governor William Shirley Scholar.[25] At Cambridge, she completed the Mathematics Tripos where she worked under the supervision of Imre Leader and Felix Fischer and wrote her thesis on Equitable Simple Allocations of Heterogeneous Goods. She earned a Master of Advanced Studies in pure mathematics from the University of Cambridge.

In 2015, Abebe started her doctoral degree in computer science at Cornell University as a researcher in theoretical computer science and artificial intelligence (AI), with a focus their applications to equity, justice, and social good concerns. She was advised by Jon Kleinberg and was a member of the AI, Policy and Practice group and the Center for the Study of Inequality.[26][27][28] Her graduate research was supported by fellowships and scholarships from Facebook Research[29] and Google.[30]

Research and career[edit]

Her research considers the intersection of AI and algorithms, with a focus on how techniques and insights from these fields can help improve access to opportunity for historically under-served and disadvantaged communities.[6] In 2018 she delivered a TED talk in Los Gatos, California.[31] She serves on the National Institutes of Health Working Group on AI.[32] Here she serves to evaluate developments of AI and data science related to biomedicine.[32]

In 2019 Abebe was selected as a Junior Fellow at the Harvard Society of Fellows.[33] Abebe was honored as a pioneer in the 2019 MIT Technology Review's Innovators Under 35.[34] Cornell University recognized Abebe with the 2019 Social Justice Award for her work using AI for good.[35]

Mechanism Design for Social Good[edit]

In 2016 Abebe co-founded the Mechanism Design for Social Good (MD4SG), a multi-disciplinary research collective that use algorithms to tackle inequality.[4] MD4SG arrange annual workshops to connect a community of researchers committed to using technology for good.[4]

Black in AI[edit]

Abebe co-founded Black in AI, a network of 1,500 researchers working on AI, with Timnit Gebru.[36][37] The network arrange annual workshops at the Conference on Neural Information Processing Systems (NeurIPS) and offers mentoring to hundreds of prospective students.

At Cornell University, Abebe has been involved with mentoring students from underrepresented groups. During her time at Cornell University and unprecedented number of students from underrepresented minority students have enrolled on their computer science doctoral program.[35] She was honored in the 2019 Bloomberg 50 list as a one to watch.[38]

References[edit]

  1. ^ "Current and Former Junior Fellows". Harvard Society of Fellows. Retrieved 2019-10-09.
  2. ^ "Current and Former Junior Fellows". Harvard Society of Fellows. Retrieved 2019-10-09.
  3. ^ "Meet the Innovators Under 35". MIT Technology Review. Retrieved 2019-10-10.
  4. ^ a b c "Mechanism Design for Social Good". md4sg.com. Retrieved 2019-10-09.
  5. ^ "Black in AI". blackinai.org. Retrieved 2019-10-09.
  6. ^ a b "Mechanism Design for Social Good – MIT Technology Review". MIT Technology Review Events. Retrieved 2019-10-09.
  7. ^ "How Ethiopia's Rediet Abebe is using algorithms and AI to address socio-economic inequality". Levers in Heels. Retrieved 2019-10-09.
  8. ^ Can Algorithms Reduce Inequality? | Rediet Abebe | TEDxLosGatos, retrieved 2019-10-09
  9. ^ "Harvard Mathematics Department Senior Thesis and PhD Thesis". Harvard Mathematics Department. Retrieved 2019-10-10.
  10. ^ "The Harvard Crimson – Writer Profile". The Harvard Crimson. Retrieved 2019-10-09.
  11. ^ "Breast Cancer Screening, Incidence, and Mortality Across US Counties". JAMA Internal Medicine. Retrieved 2019-10-09.
  12. ^ "Long-Distance Spin-Spin Coupling via Floating Gates". Physical Review X. Retrieved 2019-10-09.
  13. ^ "Top 100 Articles – 2015". Altmetric. Retrieved 2019-10-10.
  14. ^ "Another Problem with Being an Overweight Women? Breast Cancer Tumors Are Likely to Be Larger yet Harder to Detect". Newsweek. Retrieved 2019-10-10.
  15. ^ "Even More Evidence That Mammograms Have Been Oversold". FiveThirtyEight. Retrieved 2019-10-10.
  16. ^ "New Studies for an Old Story: Mammography Screening Isn't Saving Lives". The Huffington Post. Retrieved 2019-10-10.
  17. ^ "Why Women Shouldn't Cower To Concerns About Overdiagnosis Of Breast Cancer". Forbes. Retrieved 2019-10-10.
  18. ^ "Health Buzz: Study Concludes Mammograms Lead to Overdiagnosis". US News. Retrieved 2019-10-10.
  19. ^ "More Mammograms May Not Always Mean Fewer Cancer Deaths". NPR. Retrieved 2019-10-10.
  20. ^ "Mammograms Have a Magical Reputation. but They Don't Save as Many Lives as You Think". The Washington Post. Retrieved 2019-10-10.
  21. ^ "Detecting More Small Cancers in Screening Mammography Suggests Overdiagnosis". Science News. Retrieved 2019-10-10.
  22. ^ "Breast Cancer and Mammograms: Study Suggests 'Widespread Overdiagnosis'". The Washington Post. Retrieved 2019-10-10.
  23. ^ "EconCS Group – People". EconCS Group. Retrieved 2019-10-09.
  24. ^ "Cambridge Scholars". Harvard Magazine. Retrieved 2019-10-10.
  25. ^ "The Harvard-Cambridge Scholarships – Former Scholars". The Harvard-Cambridge Scholarships. Retrieved 2019-10-09.
  26. ^ "Jon Kleinberg – Home Page". Cornell University. Retrieved 2019-10-10.
  27. ^ "AI, Policy, and Practice". AI, Policy, and Practice. Retrieved 2019-10-09.
  28. ^ "Center for the Study of Inequality". Center for the Study of Inequality. Retrieved 2019-10-09.
  29. ^ "Rediet Abebe". Facebook Research. Retrieved 2019-10-09.
  30. ^ "Generation Google Scholarship – Build your future with Google". buildyourfuture.withgoogle.com. Retrieved 2019-10-09.
  31. ^ Can Algorithms Reduce Inequality? | Rediet Abebe | TEDxLosGatos, retrieved 2019-10-09
  32. ^ a b "ACD Working Group on Artificial Intelligence". NIH Advisory Committee to the Director. Retrieved 2019-10-09.
  33. ^ "Rediet Abebe". Berkman Klein Center. 2019-08-16. Retrieved 2019-10-09.
  34. ^ "Meet the Innovators Under 35 – MIT Technology Review". MIT Technology Review Events. Retrieved 2019-10-09.
  35. ^ a b "2019 Diversity & Inclusion Distinguished Award Winners : Graduate School". gradschool.cornell.edu. Retrieved 2019-10-09.
  36. ^ Forbes (2019-02-22). "Rediet Abebe, Co-Founder of Black in AI, talks about the need for more diversity in AI job roles, and why she founded her own organization". @forbes. Retrieved 2019-10-09.
  37. ^ "Rediet Abebe". Berkman Klein Center. 2019-08-16. Retrieved 2019-10-09.
  38. ^ "Bloomberg – Are you a robot?". www.bloomberg.com. Retrieved 2019-10-09.