I am a mathematics PhD student at Purdue University being advised by Plamen Stefanov. My research concerns inverse problems and imaging using tools such as microlocal analysis. I focus on applications like medical CT and optical imaging.
Before graduate school, I spent some years working in industry as an engineer. I studied electrical engineering with a focus on signal processing as an undergraduate at Penn State University.
Email: sheikh4@purdue.edu
Office: Mathematical Sciences Building 1045 (take the elevator to the 9th floor and then dare to take the stairs to the 10th…)
Updated: Jan 2025
Research interests
Applications of Microlocal Analysis to Inverse Problems
Computational Imaging and Statistical Inverse Problems
Signal and Image Processing
Projects and Publications
[Semiclassical Sampling of Helical CT] We are applying semiclassical sampling ideas to helical fan-beam CT.
[Coherent Optical Imaging through Atmospheric Turbulence] We are developing algorithms for estimating phase-errors due to atmospheric turbulence from digital holography data. Sponsored by the Air Force Research Lab.
Tools used: non-convex optimization, Bayesian modeling, expectation-maximization algorithm, Markov random field, Fourier optics
Relevant Publications:
Ali G. Sheikh, Casey J. Pellizzari, Sherman J. Kisner, Gregery T. Buzzard, Charles A. Bouman, “Dynamic DH-MBIR for Phase-Error Estimation from Streaming Digital-Holography Data”, 2023 57th Asilomar Conference on Signals, Systems, and Computers
Ali G. Sheikh, Casey J. Pellizzari, Sherman J. Kisner, Gregery T. Buzzard, and Charles A. Bouman "Dynamic DH-MBIR for low-latency wavefront estimation in the presence of atmospheric boiling", SPIE Unconventional Imaging, Sensing, and Adaptive Optics 2023
UPCOMING Conferences
Seminars Talks
“Motivating Microlocal Analysis by Way of the Region-of-Interest Problem”, Fall 2024, Graduate Student Colloquium, Purdue University
“A Taste of Statistical Inverse Problems and the Expectation-Maximization (EM) Algorithm", Fall 2023, Graduate Student Analysis Seminar, Purdue University
Conference tALKS
IEEE Asilomar Conference on Signals, Systems, and Computers - Oct 29-Nov 1 2023, Pacific Grove, CA (I gave a talk in the computational imaging session)
SPIE Optics + Photonics: Unconventional Imaging, Sensing, and Adaptive Optics - Aug 20-24 2023, San Diego, CA (It was a fun conference where I got to hear from a lot of optics and physics people. I presented a talk titled “Dynamic DH-MBIR for real-time low latency wavefront estimation”.)
Conferences Attended
Geometric Inverse Problems and Inverse Problems for Elliptic Equations Summer School - Aug 19-22 2024, Santa Cruz, CA
Workshop on Mathematical Trends in Medical Imaging - Aug 7-10 2023, Chicago, IL (This was my first in-person inverse problems conference! Lots of fun!)
Tomography Across the Scales - Oct 10-Dec 3 2022, Linz, Austria (attended virtually…so many great talks!)
Global Harmonic Analysis
Conference in honor of Steve Zelditch - Sep 8-11 2022, OnlineSpecial Session on Mathematical Methods for Inverse Problems at AMS Spring Central Sectional Meeting - Mar 26-27 2022, West Lafayette, IN (attended virtually)
Computational Imaging XX - Jan 18-22 2022, Online
Seminars
These are some of the seminars I regularly attend.
CCAM Seminar (Purdue Math)
Computational Imaging Seminar (Purdue ECE)
International Zoom Inverse Problems Seminar (UC Irvine Math)
Graduate Student Analysis Seminar (Purdue Math)
Spectral and Scattering Theory Seminar (Purdue Math)
Inverse Problems resources
Books and online resources that I regularly use, in alphabetical order.
Computational Imaging by Charles Bouman
Introduction to Inverse Problems by Guillaume Bal
Linear and Nonlinear Inverse Problems with Practical Applications by Jennifer Mueller and Samuli Siltanen
The Mathematics of Computerized Tomography by Frank Natterer
Microlocal Analysis and Integral Geometry by Plamen Stefanov and Gunther Uhlmann
Pseudodifferential Operators by Michael Taylor
Statistical and Computational Inverse Problems by Jari Kaipio and Erkki Somersalo
TALKS i HAVE ENJOYED
Accessible to a general, non-math audience.
Articles, essays, and Podcasts i HAVE ENJOYED
Terrence Tao on “good” math (episode of the podcast Joy of Why that expands on his essay)
tEACHING AT PURdue
Spring 2025: RA with Prof Stefanov
Fall 2024: TA for Calc 3 (MA 261)
Spring 2024: TA for Calc 2 (MA 162)
Summer 2022 - Fall 2024: RA with Prof Buzzard and Prof Bouman
Spring 2022: Grader for Linear Algebra (MA 353)
Hobbies
Playing basketball and tennis
Watching NBA games and the hilarious show Inside the NBA
Learning about sociology, psychology, economics and politics
Visiting coffee shops with friends
Professional Memberships
IEEE Signal Processing Society
Society of Industrial and Applied Mathematics (SIAM)
American Mathematical Society (AMS)