I am a fourth-year PhD student at MIT CSAIL advised by Sam Hopkins. My research interests are in algorithm design, particularly from the lens of convex programming. Before starting my PhD I earned my BS in Computer Science from CMU, where I worked with Pravesh Kothari.

If you'd like to chat you can reach me at paanders@mit.edu.


news


research

My research interests are in designing efficient algorithms for problems in areas such as worst case approximation and robust statistics. I'm particularly interested in the power of semidefinite programming and the sum-of-squares hierarchy.

publications

Certifiable Near-Optimality: A Simple Framework for Unifying Search and Refutation for (Semi)random CSPs
with Peter Manohar and Jeff Xu.
Preprint
A Simple Algorithm for Best Separable State
with Samuel B. Hopkins and Amit Rajaraman.
Preprint
Faster MAX-CUT on Bounded Threshold Rank Graphs
with Samuel B. Hopkins, Amit Rajaraman, and David Steurer.
Preprint
Entrywise Low-Rank Approximation and Matrix p→q Norms via Global Correlation Rounding
with Ainesh Bakshi and Samuel B. Hopkins.
SODA 2027
Dimension Reduction via Sum-of-Squares and Improved Clustering Algorithms for Non-Spherical Mixtures
with Mitali Bafna, Rares Buhai, Pravesh Kothari, and David Steurer.
COLT 2026
Additive Approximation Schemes for Low-Dimensional Embeddings
with Ainesh Bakshi and Samuel B. Hopkins.
SODA 2026
Sample-Optimal Private Regression in Polynomial Time
with Ainesh Bakshi, Mahbod Majid, and Stefan Tiegel.
STOC 2025

teaching

I am honored to receive the 2023 Alan J. Perlis Undergraduate Student Teaching Award for my work as an undergraduate teaching assistant at CMU.


misc

  • In my free time, I enjoy going fast 8(th) in my Teamfight Tactics games.
  • I'm also a beginner photographer and enjoy various other arts and crafts.
  • I'm a big fan of matcha, you can read more about my thoughts on matcha here.
  • Website template is due to Rebecca Lin.