Ali Malik
I am a PhD student in Computer Science at Stanford University (starting in 2020) focusing on Machine Learning theory and education. My research interests are in probabilistic reasoning, foundations of machine learning, and building intelligent systems that help humans learn.
I completed my Bachelor's in Mathematics at Stanford University advised by Kannan Soundararajan. As an undergraduate, I did research with Stefano Ermon and Chris Piech. I also lectured a class on standard C++ programming!
I love teaching and thinking about problems that make my brain hurt. I keep a blog on the side where I write about random Maths, CS, and Philosophy related gems that come my way.
Blog
This blog is generally just my ramblings about random things. Whenever I encounter anything interesting or figure out a cool way to think about a problem, I write the results up here for personal venting and public education.
Teaching
Here are some links to the class websites of the courses I have taught at Stanford so far. If you have any questions or suggestions for improvements, please feel free to email me!
Papers and Projects
Generative Grading: Neural Approximate Parsing for Automated Student Feedback
A. Malik*, M. Wu*, V. Vasavada, J. Song, J. Mitchell, N. Goodman, C. Piech
Under review.
The Stanford Acuity Test: A Probabilistic Approach for Precise Visual Acuity Testing
C. Piech*, A. Malik*, L. Scott, R. Chang, C. Lin
Proceedings of the 34th AAAI Conference on Artificial Intelligence, New York, USA. 2020.
Calibrated Model-Based Deep Reinforcement Learning
A. Malik*, V. Kuleshov*, J. Song, D. Nemer, H. Seymour, S. Ermon
Proceedings of the 36th International Conference on Machine Learning, Long Beach, USA. 2019
Using Latent Variable Models to Observe Academic Pathways
N. Gruver, A. Malik, B. Capoor, C. Piech, M. Stevens, A. Paepcke
Proceedings of the 12th International Conference on Educational Data Mining, Montréal, Canada. 2019
BlueBook: Secure, Electronic Computer Science Exams
A. Malik, B. Capoor, C. Piech
A secure, reliable, cross-platform desktop application to administer computerised examination for large classes. Has been used to administer over 5000 exams in Stanford's introductory CS classes.
DeepGIFs
A. Malik, M. Troute, B. Capoor
Exploring the effectiveness of deep generative recurrent networks in the task of understanding and generating motion. In particular, we attempt to generate GIFs of realistic mechanical motion on a synthetic dataset from an initial seed frame.
Archive of Code
A. Malik
A compilation of various code snippets and programs I have written. Includes interesting data structures, algorithms, and interview problems.
WikiRacer
A. Malik
An assignment I wrote where students implement an algorithm that finds a link ladder between two given Wikipedia pages.