Google Scholar page

DBLP author page

papers

Ayesha Bajwa*, Ruchir Rastogi*, Pooja Kathail*, Richard W. Shuai, and Nilah Ioannidis. Characterizing uncertainty in genomic sequence-to-activity models. Proceedings of the 18th Machine Learning in Computational Biology meeting, 2024.

Bertie Ancona, Ayesha Bajwa, Nancy A. Lynch, and Frederik Mallmann-Trenn. How to Color a French Flag--Biologically Inspired Algorithms for Scale-Invariant Patterning. LATIN: Latin American Symposium on Theoretical Informatics 2020, São Paulo, Brazil.

Ayesha Bajwa, Ana Bell, Erik Hemberg, and Una-May O'Reilly. Analyzing Student Code Trajectories in an Introductory Programming MOOC. IEEE Learning With MOOCs 2019, Milwaukee, WI, USA.

Winner of the Best Student Paper Award
Jitesh Maiyuran, Ayesha Bajwa, Ana Bell, Erik Hemberg, and Una-May O'Reilly. How Student Background and Topic Impact the Doer Effect in Computational Thinking MOOCs. IEEE Learning With MOOCs 2019, Milwaukee, WI, USA.

Sagar Biswas, Ayesha Bajwa, Erik Hemberg, Nancy Law, and Una-May O'Reilly. Categorizing Resources and Learners for a Finer-Grained Analysis of MOOC Viewing & Doing. IEEE Learning With MOOCs 2019, Milwaukee, WI, USA.

Bertie Ancona, Ayesha Bajwa, Nancy A. Lynch, and Frederik Mallmann-Trenn. How to Color a French Flag--Biologically Inspired Algorithms for Scale-Invariant Patterning. SIROCCO: International Colloquium on Structural Information and Communication Complexity 2019, L'Aquila, Italy. (Brief Announcement Track)

Leilani H. Gilpin, David Bau, Ben Z. Yuan, Ayesha Bajwa, Michael Specter, and Lalana Kagal. Explaining Explanations: An Overview of Interpretability of Machine Learning. IEEE International Conference on Data Science and Advanced Analytics 2018, Turin, Italy.

workshops

Bertie Ancona, Ayesha Bajwa, Nancy A. Lynch, and Frederik Mallmann-Trenn. How to Color a French Flag--Biologically Inspired Algorithms for Scale-Invariant Patterning. 7th Workshop on Biological Distributed Algorithms at PODC 2019, Toronto, Canada.

posters

Ayesha Bajwa, Ana Bell, Erik Hemberg, and Una-May O'Reilly. Student Code Trajectories in an Introductory Programming MOOC. Learning at Scale 2019, Chicago IL, USA. (Work-In-Progress Track)

Smriti Pramanick, Ayesha Bajwa, Jessica Werk. The Distribution of Oxygen in the Magellanic Clouds. American Astronomical Society 2014, Washington DC, USA.

other

My 2019 MIT MEng thesis on student learning in MOOCs.

Post on bias in ML systems, adapted from my essay for an Ethics and Governance of AI class (Spring 2018).