Scholar
Falaah Arif Khan
Google Scholar ID: 53O3iRgAAAAJ
New York University
Citations & Impact
Citations
204
H-index
7
i10-index
5
Publications
20
Co-authors
3
list available
Publications
Resume (English only)
Academic Achievements
- 2024: Awarded the Apple Scholars in AIML PhD Fellowship.
- March 2023: Paper on 'effect of automated data cleaning on model fairness' accepted to IEEE ICDE'23 Special Track.
- October 2022: Work on 'Fairness as Equal Opportunity' accepted for oral presentation at ACM EAAMO'22.
- September 2022: 'Interactive Introduction to Causal Inference' accepted to VISxAI Workshop at IEEE VIS.
- August 2022: Paper on 'Stability Auditing of Personality Prediction AI' accepted to the Fairness and Bias Special Edition of Data Mining and Knowledge Discovery Journal.
- April 2021: Invited talk 'It's funny because it's true: confronting ML catechisms' at ICLR 2021’s 'Rethinking ML Papers' Workshop.
- April 2021: 'Fairness and Friends' accepted as an exhibit at ICLR 2021’s 'Rethinking ML Papers' Workshop.
- March 2021: Presented 'Fairness and Friends' tutorial at ACM FAccT 2021 with Julia Stoyanovich and Eleni Manis.
Research Experience
- Summer 2024: Interned with Apple MLR in the San Francisco Bay Area.
- Summer 2023: Co-facilitated the third offering of the public education course 'We Are AI' for NYU librarians and non-academic staff.
- Summer 2022: Co-organized a 6-week summer research program with Ukrainian Catholic University under #ScienceForUkraine via R/AI.
- May–June 2021: Launched the public-facing comic series 'We are AI' to accompany a public education course of the same name.
- December 2020: Facilitated the MAIEI x RAIN-Africa workshop 'Perspectives on the future of Responsible AI in Africa'.
- November 2020: Facilitated the 'Privacy in AI' Workshop by MAIEI and the AI4Good Lab.
Background
- Engineer/Scientist by training and an Artist by nature.
- Broadly interested in how technology shapes and is shaped by society.
- Currently a fourth-year PhD student at NYU's Center for Data Science.
- Supported by the Apple Scholars in AIML PhD fellowship.
- Conducts fundamental interdisciplinary research on AI fairness and AI safety.
- Creates scientific comics and artwork to make AI research accessible to both technical and non-technical audiences.
