2026:
[Sep] Paper (workshop) Accepted: Backward-Consistent Diffusion Sampling for Sparsely Observed PDE Inverse Problems. NeurIPS 2026 STODY.
[Sep] Paper Accepted: A Principled Self-Referenced Early Stopping Approach for Deep Image Prior. NeurIPS 2026.
[Sep] Attended and gave a talk at a seminar in Allerton (UIUC) on "Diffusion Models for Inverse Problems".
[Aug] Paper Released: Parallelizable Gradient-Based Optimization For Multi-Objective MaxCut.
[Jul] Honored to have been selected to participate in NextProf Nexus 26 hosted by Georgia Tech and in partnership with UM and UC Berkeley.
[Jun] Attended the Midwest Machine Learning Symposium (MMLS26) at Purdue University.
[Jun] Paper Released: ForcingDAS: Unified and Robust Data Assimilation via Diffusion Forcing. (ICML26 FoGen Workshop, spotlight)
[May] Paper Accepted: DCDP: Decoupled Data Consistency via Diffusion Purification for Inverse Problems. ICCP 2026.
[May] Attended the 3rd Conference on Foundation Models & AI Agents for Science (SciFM26) at the University of Chicago.
[May] Paper Released: A Principled Self-Referenced Early Stopping Approach for Deep Image Prior.
[May] Paper Released: Dynamic MRI Reconstruction Via Dual Deep Priors and Low-Rank Plus Sparse Modeling.
[May] Honored to have been recognized as a Silver Reviewer at ICML 2026.
[May] PhD students, Gavin Kunesh (UM) and Ryan Devrea (UMN), join LANL Michigan SPARC as Summer interns, working with me and Jonah Miller.
[May] Paper Released: Mutation-Guided Differentiable Quadratic Combinatorial Optimization.
[Apr] Paper Accepted: Local Minima in Quadratic-Penalty Relaxations of Binary Linear Programs. ICML 2026.
[Mar] Paper Released: GaloisSAT: Differentiable Boolean Satisfiability Solving via Finite Field Algebra.
[Feb] Paper Accepted: Differentiable Quadratic Optimization with Semidefinite Programming Initializations: A Case Study on Maximum Independent Set. ISCO 2026.
[Feb] Gave a talk to UMN's CSE DSI ML seminar on "Differentiable Combinatorial Optimization at Scale", invited by Prof. Ju Sun.
[Feb] Gave a talk to LANL's Center of Non Linear Studies (CNLS) on "Differentiable Combinatorial Optimization at Scale".
[Jan] Paper Accepted: A Scalable Lift-and-Project Differentiable Approach For the Maximum Cut Problem. AISTATS 2026.
[Jan] Paper Accepted: Coarse Adversarial Training with Label Grouping for Robust Classification. ICASSP 2026.
[Jan] Joined Los Alamos National Lab (XCP Division) as a Research Scientist at LANL Michigan SPARC.
2025:
[Dec] Attended NeurIPS25 in San Diego, CA.
[Nov] Gave a talk to Prof. Yu Sun's group at JHU on "Input Adaptivity in Generative Imaging Models In Data Scarce Regimes".
[Nov] Paper Accepted: Robust Physics-based Deep MRI Reconstruction Via Diffusion Purification. IEEE TNNLS 2025.
[Oct] Gave a talk to Prof. Jia (Kevin) Liu's group at OSU on "Input Adaptivity in Generative Imaging Models In Data Scarce Regimes".
[Oct] Paper Accepted: On the Dataless Training of Neural Networks. AAAI 2026 - ETA Track.
[Oct] Paper Accepted: Tada-DIP: Input-adaptive Deep Image Prior for One-shot 3D Image Reconstruction. Asilomar 2025.
[Sep] Attended DARPA's TIAMAT program PI meeting at the University of Maryland College Park.
[Sep] Paper Accepted: UGoDIT: Unsupervised Group Deep Image Prior Via Transferable Weights. NeurIPS 2025.
[Sep] Paper Accepted: Understanding Untrained Deep Models for Inverse Problems: Algorithms and Theory. IEEE SPM (Issue on The Mathematics of Deep Learning) 2025.
[Sep] Paper Accepted: NERD: Network-Regularized Diffusion Sampling For 3D Computed Tomography. CAMSAP 2025.
[Aug] Honored to have received the Alumni Outstanding Research Award at the CMSE Department 10th anniversary workshop at MSU.
[Jul] Paper Accepted: Robust MRI Reconstruction by Smoothed Unrolling (SMUG). JSTSP 2025.
[Jul] Attended ICML25 in Vancouver, Canada.
[Jun] Gave a talk to the XCP Division at Los Alamos National Lab (hosted by Dr. Juston Moore) on "Input Adaptivity in Generative Imaging Models Across Data Regimes".
[May] Paper Released: UGoDIT: Unsupervised Group Deep Image Prior Via Transferable Weights.
[May] Paper Released: A Dataless Reinforcement Learning Approach to Rounding Hyperplane Optimization for Max-Cut.
[May] Paper Accepted: SITCOM: Step-wise Triple-Consistent Diffusion Sampling For Inverse Problems. ICML 2025.
[May] Paper Accepted: Differentiable Quadratic Optimization for the Maximum Independent Set Problem. ICML 2025.
[Apr] Gave a talk to the OPTML group at MSU (hosted by Prof. Sijia Liu) on "Differentiable Quadratic Combinatorial Optimization".
[Apr] Gave a talk to the NuSCI group at SRI International (hosted by Dr. Susmit Jha) on "Differentiable Quadratic Combinatorial Optimization".
[Mar] Attended CPAL2025 at Stanford University.
[Mar] Attended DARPA's TIAMAT program PI meeting at UC Berkeley.
[Feb] Paper Released: Understanding Untrained Deep Models for Inverse Problems: Algorithms and Theory.
[Jan] Honored to have been selected for the CPAL25 Rising Stars Award.
[Jan] Joined DARPA I2O as a Tech SETA, working with Alvaro Velasquez.
2024:
[Dec] Paper Accepted: Sequential Diffusion-Guided Deep Image Prior For Medical Image Reconstruction. ICASSP 2025.
[Dec] Attended NeurIPS24 in Vancouver, Canada.
[Oct] Attended SIAM MDS in Atlanta, Georgia.
[Oct] Paper Accepted: Structure-Preserving Network Compression Via Low-Rank Induced Training Through Linear Layers Composition. TMLR 2024.
[Oct] Paper Released: Unrolled Diffusion Guided Deep Image Prior For Medical Image Reconstruction.
[Oct] Paper Released: SITCOM: Step-wise Triple-Consistent Diffusion Sampling for Inverse Problems.
[Oct] Paper Released: Dataless Quadratic Neural Networks for the Maximum Independent Set Problem.
[Sep] Paper Accepted: Image Reconstruction Via Autoencoding Sequential Deep Image Prior. NeurIPS 2024.
[Aug] Attended a Computational Imaging workshop at IMSI in the University of Chicago.
[Jun] Paper Accepted: Controller synthesis for linear temporal logic and steady-state specifications. JAAMAS 2024.
[May] Attended ICASSP24 in Seoul, South Korea
[May] Gave a talk to Prof. Jong Chul Ye's group at KAIST on "Robust Physics-based Deep MRI Reconstruction Via Diffusion Purification".
[Mar] Paper Released: Decoupled Data Consistency with Diffusion Purification for Image Restoration.
[Feb] Paper Accepted: Improving Training Efficiency of Diffusion Models via Multi-Stage Framework and Tailored Multi-Decoder Architecture . CVPR 2024.
[Jan] Gave a tutorial on "Deep Learning for Inverse Imaging Problems" at CPAL in Hong Kong.
[Jan] Paper Accepted: Diffusion-Based Adversarial Purification for Robust Deep MRI Reconstruction. ICASSP 2024.
[Jan] Paper Accepted: Exploring The Predictive Capabilities of AlphaFold Using Adversarial Protein Sequences. IEEE TAI 2024.