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I am fifth year Ph.D. candidate at the ECE department at Rice University, advised by Santiago Segarra. My research develops algorithms to solve inverse problems, currently focused on image inverse problems. In particular, I have worked on designing fast and scalable algorithms that incorporate diffusion models as prior distributions. Also, I have worked on graphon estimation using implicit neural representations, zero-shot stitching, and algorithm unfolding and its application to Particle filters.
I am fifth year Ph.D. candidate at the ECE department at Rice University, advised by Santiago Segarra. My research develops algorithms to solve inverse problems, currently focused on image inverse problems. In particular, I have worked on designing fast and scalable algorithms that incorporate diffusion models as prior distributions. Also, I have worked on graphon estimation using implicit neural representations, zero-shot stitching, and algorithm unfolding and its application to Particle filters.
I recently completed a summer research internship at the Center of Computational Neuroscience at Flatiron Institute, Flatiron Institute (New York), where I worked with Prof. Eero Simoncelli and Florentin Guth. In summer 2024, I was a research intern at InterDigital (Los Altos, CA), collaborating with Akshay Malhotra and Shahab Hamidi-Rad.
I recently completed a summer research internship at the Center of Computational Neuroscience at Flatiron Institute, Flatiron Institute (New York), where I worked with Prof. Eero Simoncelli and Florentin Guth. In summer 2024, I was a research intern at InterDigital (Los Altos, CA), collaborating with Akshay Malhotra and Shahab Hamidi-Rad.
News
News
September 2025 Paper accepted at NeurIPS: NPGL Graph Guided Diffusion: Unified Guidance for Conditional Graph Generation
May 2025 Started intership in Flatiron Insitute, working at Computational Vision group
March 2025 Attended Khipu AI in Santiago, Chile
Jan 2025 Paper accepted at AISTATS 2025 Scalable Implicit Graphon Learning
Jan 2025 Paper accepted at ICLR 2025 Repulsive Latent Score Distillation for Solving Inverse Problems
Nov 2024 I am honored to receive the Ken Kennedy – HPE Cray Graduate Fellowship
Oct 2024 Paper accepted at NeurIPS: 2ndUniReps workshop Topology Preserving Regularization for Independent Training of Inter-operable Models
Oct 2024 New preprint Scalable Implicit Graphon Learning
May 2024 Started internship in InterDigital, Los Altos, CA
May 2024 New preprint Repulsive Latent Score Distillation for Solving Inverse Problems
Jan 2024 Paper Solving linear inverse problems with Higher-order Annealed Langevin dynamics accepted at IEEE transactions on Signal Processing
Nov 2023 Successful Master defense, entitled Annealed Langevin dynamics for MIMO communications
Nov 2023 Preprint of Joint channel estimation and data detection in massive MIMO systems based on diffusion models
Oct 2023 Paper Unsupervised Learning of sampling distributions for Particle filters accepted at IEEE transactions on Signal Processing
May 2023 Preprint of Solving linear inverse problems with Higher-order Annealed Langevin dynamics
Feb 2023 Paper accepted at ICASSP 2023 Accelerated massive MIMO detector based on annealed underdamped Langevin dynamics
Oct 2022 Paper Annealed Langevin Dynamics for Massive MIMO Detection accepted at IEEE transactions on Wireless Communications
May 2022 Two papers accepted at EUSIPCO 2022.
January 2022 One paper accepted to ICASSP 2022.
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