Welcome!
This seminar series brings together researchers from TU Delft working on Graphs and Data.

The seminar takes place every month and comprises 2/3 talks:

• One long talk + Q&A (45min)
• One/two shorter talks + Q&A (targeting a specific topic/research) (20 min).

[ Register here ] to attend the next seminar and receive email updates about the seminar.

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Upcoming Talks

[December 5th, 2024] Network Science

Location: Building 28: Turing room 0.E420

Time: 10.30-12.00

Zoom: link

• Approximations for Kemeny’s Constant for Several Families of Graphs and Real-World Networks, Rob Kooij

• Network Reliability: Approximation, Upper Bounds, and Applications to Network Robustness, Xinhan Liu

• Diffusion Backbones of Temporal Higher-Order Networks, Shilun Zhang

[January 9th, 2025] Network Controllability

Location: EEMCS-36: LB 01.150 Lipkenszaal

• Controllability of Networks Under Sparsity Constraints, Geethu Joseph

• On the Optimality of Sparse Feedback Control Under Architecture-Dependent Communication Delays, Luca Ballotta

[February 13th, 2025] Networks and Crime Analysis

Location: Building 28: Turing room 0.E420

• Graph ML for Financial Crime Analysis, Kubilay Atasu

• Multigraph Neural Networks for Financial Transaction Graphs, Çağrı Bilgi

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Past Talks

[November 7th, 2024] Graph Neural Networks for Power Systems

• Opportunities & Challenges in Graph-Based Learning for Power System Application, Jochen Cremer
  [ Slides ]
• Graph Shift Operator for Power System Applications, Ola Arowolo
  [ Slides ]
• Enabling Large-Scale Coordination of Electric Vehicles Using Reinforcement Learning, Stavros Orfanoudakis
  [ Slides ]

[October 3rd, 2024] Graph Generation for Chemical Engineering

• Generative Artificial Intelligence for Chemical Process Engineering, Artur M. Schweidtmann
• Generative Artificial Intelligence for Control Structure Prediction, Lukas Schulze Balhorn
  [ Slides ]
• Process Design through Deep Reinforcement Learning and Graph Neural Networks, Qinghe Gao
  [ Slides ]

[July 11th, 2024] Special session - Learning with Graphs

• Online Learning of Nonlinear and Dynamic Graphs, Rohan Thekkemarickal Money
  [ Slides ] [ Recording ]

• Mixup for Augmenting Data in Myriad Scenarios, Madeline Navarro
  [ Slides ] [ Recording ]

• Exploiting the Structure of Two Graphs with Graph Neural Networks, Víctor Manuel Tenorio Gómez
  [ Slides ] [ Recording ]

[May 2nd, 2024] System Identification

• Identification of Networks of Dynamic Systems, Michel Verhaegen
  [ Slides ] [ Recording ]

[April 4th, 2024] PDEs and Graphs

• Graphs and Differential Equations in Machine Learning, Yves van Gennip
• Inferring Time-Varying Signals over Graphs via SPDEs, Mohammad Sabbaqi
  [ Slides ] [ Recording ]

[March 14th, 2024] Higher-Order Structures

• Geometry Processing: Discretization, Learning and Analysis, Klaus Hildebrandt

• Hodge-compositional Edge Gaussian Processes, Maosheng Yang
  [ Slides ] [ Recording ]

• DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds, Ruben Wiersma
  [ Slides ] [ Recording ]

[February 15th, 2024] Water Networks

• Towards Foundational (Meta)models of Water Distribution Networks with Graph Neural Networks, Riccardo Taormina
  [ Slides ] [ Recording ]

• Faster and Transferable Urban Drainage Simulations with Graph Neural Networks, Alexander Garzón
  [ Slides ] [ Recording ]

• Relating Complex Network Theory Metrics with Discolouration Activity in Water Distribution Systems, Greg Kyritsakas
  [ Slides ] [ Recording ]

[January 11th, 2024] Temporal and Higher-Order Networks

• Temporal Network Prediction and Interpretation, Huijuan Wang
  [ Slides ]

• Unrolling of Simplicial ElasticNet for Edge Flow Signal Reconstruction, Chengen Liu
  [ Slides ]

• Temporal-Topological Properties of Higher-Order Evolving Networks, Alberto Ceria
  [ Slides ]

[December 7th, 2023] Graph Signal Processing

• Graph Signal Processing: Introduction and Research at SPS, Geert Leus
  [ Slides ] [ Recording ]

• Learning (Time-Varying) Graphs from (Online) Data, Alberto Natali
  [ Slides ] [ Recording ]

• Uncovering Temporal Networks through Tensor-like Decompositions, Bishwadeep Das
  [ Slides ] [ Recording ]

[November 9th, 2023] Graph Neural Networks

• Explainable Graph Machine Learning : Challenges and Solutions, Megha Khosla
  [ Slides ] [ Recording ]

• Multi-label Node Classification On Graph-Structured Data, Tianqi Zhao
  [ Slides ] [ Recording ]

• Self-Attention Message Passing for Contrastive Few-Shot Image Classification, Ojas Shirekar
  [ Slides ] [ Recording ]

[October 5th, 2023] Network Representation and Inference

• Geometric Representations of Complementarity-Driven Networks, Maksim Kitsak
  [ Slides ] [ Recording ]

• Learning Graphs and Simplicial Complexes From Data, Andrei Buciulea Vlas
  [ Slides ] [ Recording ]

• System Identification for Temporal Networks, Sergey Shvydun
  [ Slides ] [ Recording ]

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Organizers

Elvin Isufi

Mohammad Sabbaqi

Andrea Cavallo

Alexander Garzón
(previous organizer)