392232 Advanced Artificial Intelligence in Biomedicine

Schönhuth/Schlüter

Winter 2025

Thu 12-14 in Y-1-202 (S) and Thu 10-12 in U2-200 (Ü)

Contact

Prof. Dr. Alexander Schönhuth: aschoen@cebitec.uni-bielefeld.de
Johannes Schlüter: j.schlueter@uni-bielefeld.de

Structure

Individual presentations (S): present contents of chosen scientific paper for 30 minutes, followed by 15 minutes for discussion
Technical report (S): 10-12 pages long
Paper journal (Ü): collection of summaries of at least half of the presentations; each summary should be at least 300 words

Papers

Please, see on Google Drive. The file is password protected.
If there is any problem with accessing a paper, write an email to Luna Pianesi.

Introduction

introduction-161025.pdf

How to present

howtopresent.pdf

How to write reports

howtowritereports.pdf

Timetable seminar sessions

Date	Topic
16.10.2025	Introduction, How to present
23.10.2025	-
30.10.2025	-
06.11.2025	-
13.11.2025	-
20.11.2025	How to write reports, Presentations start Presentation: Gregor Foitzik. “Protein Structure Generation Via Folding Diffusion”
27.11.2025	Presentation: Sanket Veerkar. “Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models for Protein Structures” Presentation: Özay Öztürk. “Mamba: Linear-time Sequence Modelling with Selective State Spaces”
04.12.2025	Presentation: Karthikeya Barla. “Quantum Mixed-State Self-Attention Network” Presentation: Christopher Gerz. “Protein Docking Model Evaluation by Graph Neural Networks”
11.12.2025	Presentation: Jonas Ginster. “Machine learning and AI-based approaches for bioactive ligand discovery and GPCR-ligand recognition” Presentation: Dustin Schulz. “Using GNN property predictors as molecule generators”
18.12.2025	Presentation: Dana Meyer. “Multiscale transformers and multi-attention mechanism networks for pathological nuclei segmentation” Presentation: Felix Duldinger. “Context-aware geometric deep learning for protein sequence design”
25.12.2025	Holidays
01.01.2026	Holidays
08.01.2026	Presentation: Lokesh Mangamuri. “Combining Graph Attention and Recurrent Neural Networks in a Variational Autoencoder for Molecular Representation Learning and Drug Design” Presentation: Genna Strathmann. “MEGANet: Multi-scale Edge-Guided Attention Network for Weak Boundary Polyp Segmentation”
15.01.2026	Presentation: Anjali Anjali. “Biomedical literature mining: graph kernel-based learning for gene–gene interaction extraction” Presentation: Mathis Wülpern. “Hypergraph Factorization for Multi-tissue Gene Expression Imputation”
22.01.2026	Presentation: Abdulrahman Alzahabi. “DrugDAGT: a Dual-Attention Graph Transformer for Drug-Drug Interaction Prediction” Presentation: Abu Emran Emon. “Graph-to-Sequence Retrosynthesis”
29.01.2026	Presentation: Jefferson Vormann. “gRNAde: Geometric Deep Learning for 3D RNA Inverse Design” Presentation: Michael Bucks. “Molecule Edit Graph Attention Network: Modelling Chemical Reactions as Sequences of Graph Edits”
05.02.2026	Presentation: Aya Benzine. “Contextual AI Models for Single-cell Protein Biology” Presentation: Ergys Kosita. “Prospective De Novo Drug Design with Deep Interactome Learning”
12.02.2026	Presentation: Kareem Elbanna. “TAnet: A New Temporal Attention Network for EEG-based Auditory Spatial Attention Decoding with a Short Decision Window” Presentation: Khaled Saber. “EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction” Presentation: Shambavi Arcot Velumani. “On the Scalability of GNNs for Molecular Graphs”