Scholar
Ajil Jalal
Google Scholar ID: ePC7IC0AAAAJ
UC Berkeley
Citations & Impact
Citations
3,111
H-index
15
i10-index
16
Publications
20
Co-authors
0
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Published Papers: 'Magnetic Resonance in Medicine' (2024), showing diffusion posterior sampling can correct blur from patient motion during an MRI scan; 'ICML 2024', showing posterior sampling using diffusion models is computationally intractable; 'NeurIPS 2023', showing we can learn the distribution of 1-layer conditional generative models via maximum likelihood estimation with near-optimal sample complexity; 'Asilomar 2023', showing the advantages of side information in MRI reconstruction using diffusion models.
Research Experience
- Research Scientist at PothosAI, Jan 2025 - Present; Postdoc at UC Berkeley, June 2022 - May 2025; Research Intern at IBM Research, Yorktown Heights, May - September 2019; Research Intern at Tata Institute of Fundamental Research (TIFR), Mumbai, May - August 2015; Research Intern at Audience Communication Systems, Bangalore, May - August 2014.
Education
- Ph.D., Electrical and Computer Engineering, The University of Texas at Austin, 2016 - 2022, Advisor: Prof. Alex Dimakis; B.Tech. (Honors), Electrical Engineering, IIT Madras, 2012 - 2016, Advisors: Prof. Rahul Vaze, Prof. Umang Bhaskar, Prof. Krishna Jagannathan.
Background
- Research Interests: Intersection of deep generative models and inverse problems like compressed sensing. Professional Field: Electrical and Computer Engineering. Summary: Currently a research scientist at PothosAI, developing multimodal models that integrate numerical and textual data for quantitative finance.
Miscellany
- Invited Talks: Samsung Research (Apr 30, 2024); ITA, San Diego, California (Feb 29, 2024); Stanford (Dec 15, 2023); Youth in High-Dimensions workshop, Trieste, Italy (Oct 29, 2023); IIT Madras (Jan 11, 2022) etc.
Co-authors