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

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

Time: 10:30-12:00

Location: EEMCS-36: LB 01.170 Timmanzaal

Join on Zoom: link

• Opportunities & challenges in graph-based learning for power system application, Jochen Cremer
• Graph Shift Operator for Power System Applications, Ola Arowolo
• Enabling Large-Scale Coordination of Electric Vehicles Using Reinforcement Learning, Stavros Orfanoudakis

[December 5th, 2024]

Location: Building 28: Turing room 0.E420

• Approximations for Kemeny’s constant for several families of graphs and real-world networks, Rob Kooij

[January 9th, 2025]

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

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Past Talks

[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
• 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)