Ayesha Bajwa

Publication Activity (10 Years)

Years Active: 2018-2023
Publications (10 Years): 10

Top Topics

Machine Learning

Introductory Programming

Massive Open Online Courses

Scale Invariance

Top Venues

Publications

Ayesha Bajwa, Ruchir Rastogi, Pooja Kathail, Richard W. Shuai, Nilah Ioannidis
Characterizing uncertainty in predictions of genomic sequence-to-activity models. MLCB (2023)
Bertie Ancona, Ayesha Bajwa, Nancy A. Lynch, Frederik Mallmann-Trenn
How to Color a French Flag - Biologically Inspired Algorithms for Scale-Invariant Patterning. LATIN (2020)
Erik Hemberg, Sagar Biswas, Ayesha Bajwa, Nancy Law, Una-May O'Reilly
Categorizing Resources and Learners for a Finer-Grained Analysis of MOOC Viewing & Doing. LWMOOCS (2019)
Ayesha Bajwa, Erik Hemberg, Ana Bell, Una-May O'Reilly
Student Code Trajectories in an Introductory Programming MOOC. L@S (2019)
Bertie Ancona, Ayesha Bajwa, Nancy A. Lynch, Frederik Mallmann-Trenn
How to Color a French Flag - Biologically Inspired Algorithms for Scale-Invariant Patterning. SIROCCO (2019)
Alberto Ancona, Ayesha Bajwa, Nancy A. Lynch, Frederik Mallmann-Trenn
How to Color a French Flag-Biologically Inspired Algorithms for Scale-Invariant Patterning. CoRR (2019)
Jitesh Maiyuran, Ayesha Bajwa, Ana Bell, Erik Hemberg, Una-May O'Reilly
How Student Background and Topic Impact the Doer Effect in Computational Thinking MOOCs. LWMOOCS (2019)
Ayesha Bajwa, Ana Bell, Erik Hemberg, Una-May O'Reilly
Analyzing Student Code Trajectories in an Introductory Programming MOOC. LWMOOCS (2019)
Leilani H. Gilpin, David Bau, Ben Z. Yuan, Ayesha Bajwa, Michael A. Specter, Lalana Kagal
Explaining Explanations: An Overview of Interpretability of Machine Learning. DSAA (2018)
Leilani H. Gilpin, David Bau, Ben Z. Yuan, Ayesha Bajwa, Michael A. Specter, Lalana Kagal
Explaining Explanations: An Approach to Evaluating Interpretability of Machine Learning. CoRR (2018)