ALEJANDRO PARADA-MAYORGA

News

  • The ASP Lab welcomes Dipayan Bhadra, who will start his Ph.D. studies in the Fall of 2026.
  • Our work was featured at CU Denver news https://ucdengineeringnews.com/2026/03/25/understanding-the-mathematics-behind-modern-ai/
  • ASP Lab Receives Seed Grant for Multigraph Signal Processing Research. We are excited to announce that the ASP Lab has been awarded seed grant funding for our proposal “Optimal Sampling and Signal Reconstruction on Multigraphs”! This support will fuel new advances in sampling theory and signal reconstruction on complex network structures, with applications in power systems, transportation, and beyond. University of Colorado Denver, March 2026.
  • A new preprint is out: “RKHS Representation of Algebraic Convolutional Filters with Integral Operators” [link]
  • We are presenting two papers at ICASSP 2026 in Barcelona on May 4 to 8, 2026. Presentations on “Sampling and uniqueness sets in graphon signal processing” and “Convolutional Filtering with RKHS Algebras”. 
  • Invited talk, “Sampling and Uniqueness Sets in Graphon Signal Processing.” American Mathematical Society Western Sectional – Boise, March 7/8, 2026.
  • Our work “DiffKillR: Killing and Recreating Diffeomorphisms for Cell Annotation in Dense Microscopy Images” will be presented at IEEE International Workshop on Machine Learning for Signal Processing (MLSP) 2025 August 31-September 3, Istanbul/Turkey
  • Our paper “Sampling and Uniqueness Sets in Graphon Signal Processing” has been accepted for publication in IEEE Transactions on Signal Processing.
  • Our paper “Convolutional Filtering with RKHS Algebras” has been accepted for publication in IEEE Transactions on Signal Processing.
  • Our IEEE-TSP paper “Lie Group Algebra Convolutional Filters” has been accepted for presentation at ICASSP-2025.
  • Our paper “DiffKillR: Killing and Recreating Diffeomorphisms for Cell Annotation in Dense Microscopy Images” has been accepted for presentation at ICASSP-2025.
  • A new preprint is out: “Convolutional Filtering with RKHS Algebras”[link]
  • I am attending the 2024 Mathematical and Scientific Foundations of Deep Learning Annual Meeting, Simons Foundation, Flatiron Institute, NY. September 26-27
  • Invited talk, Codes and Expansions (CodEx) Seminar – theory and applications of harmonic analysis, combinatorics, and algebra, September 2024, “Algebraic Neural Networks: Stability to Deformations” [link]
  • Invited talk, Department of Mathematical and Statistical Sciences, University of Colorado (Denver), September 2024, “Algebraic Neural Networks: Stability to Deformations”
  • I started as a Tenure Track Assistant professor at the University of Colorado (Denver), August 2024
  • Invited talk, ECE Department, University of Colorado (Denver), April 2024, “Algebraic Neural Networks: Stability to Deformations”
  • Our paper, “Lie Group Algebra Convolutional Filters”, has been accepted for publication in IEEE Transactions on Signal Processing [link]
  • A new preprint is out: “Sampling and Uniqueness Sets in Graphon Signal Processing” [link]
  • Our IEEE-TSP published paper “Graphon Pooling for Reducing Dimensionality of Signals and Convolutional Operators on Graphs” has been accepted for presentation at ICASSP 2024
  • Our IEEE-TSP published paper “Convolutional Filters and Neural Networks With Noncommutative Algebras” has been accepted for presentation at ICASSP 2024
  • Our paper ” Non Commutative Convolutional Signal Models in Neural Networks: Stability to Small Deformations” has been accepted for ICASSP 2024
  • Our paper “Stability of Aggregation Graph Neural Networks” has been accepted for publication in IEEE Transactions on Signal and Information Processing over Networks [link]
  • Poster presentation at the Fall Fourier Talks 2023, “The Algebraic Structure of Convolutional Machine Learning”, Norbert Wiener center, University of Maryland
  • Invited talk, Algebra Seminar in the Math Department, Temple University, October 2023, “Algebraic Neural Networks: Stability to Deformations”
  • Our paper “Graphon Pooling for Reducing Dimensionality of Signals and Convolutional Operators on Graphs” has been accepted in IEEE Transactions in Signal Proccessing [link]
  • Invited talk, SUMRY (summer math research program), Yale University, June 2023, “Algebraic Neural Networks: Stability to Deformations”
  • Our paper “Convolutional Filtering and Neural Networks with Non Commutative Algebras” has been accepted in IEEE Transactions in Signal Processing [link]
  • Poster presentation at the GSP workshop 2023, “Learning with Multigraph Convolutional Filters”, University of Oxford.
  • Poster presentation at ICASSP 2023, “Learning with Multigraph Convolutional Filters”
  • New paper is out: “Lie Group Algebra Convolutional Filters” [link]
  • I am a co-instructor in the GNNs course at ICASSP-2023 organized by Professor Alejandro Ribeiro
  • Invited talk, CIS department seminar at University of Delaware, 2023, “Algebraic Neural Networks: Stability to Deformations”.
  • Invited talk, CMSE department seminar at Michigan State University, 2023, “Algebraic Neural Networks: Stability to Deformations”, 2023.
  • Our paper “Convolutional Learning on Multigraphs” has been accepted in IEEE Transactions in Signal Processing [link]
  • Invited talk, ESE department seminar at University of Washington in St. Louis, 2023, “Algebraic Neural Networks: Stability to Deformations”.
  • New preprint is out: “Convolutional Learning on Multigraphs” [link]
  • New preprint is out: “Graphon Pooling for Reducing Dimensionality of Signals and Convolutional Operators on Graphs” [link] 
  • New preprint is out: “Stability of Aggregation Graph Neural Networks” [link]
  • Invited talk, ECE department seminar at University of Southern California, 2022, “Algebraic Neural Networks: Stability to Deformations”
  • Invited talk, ECE department seminar at Michigan state university, 2022, “Algebraic Neural Networks: Stability to Deformations”
  • Talk at the THEORINET Retreat 2021, “Algebraic Neural Networks”
  • New preprint is out: “Convolutional Filtering and Neural Networks with Non Commutative Algebras” [link]
  • Talk (delivered by professor Alejandro Ribeiro). Seminar “Physics meets Machine Learning” at CERN (2021) [video]
  • Presentation at ICASSP 2021, “Stability of Algebraic Neural Networks to Small Perturbations” [video]
  • Presentation at EUSIPCO 2020, “Graphon Pooling in Graph Neural Networks” [video]