📢 Submit your abstract by 14 March and be a part of AI4X!
📅 Dates: 8–11 July 2025
📍 Location: Singapore
🔗https://ai4x.cc/submission/

AI for Materials Science

Abhishek Singh (Indian Institute of Science): His work spans ML applications, 2D materials, thermoelectrics, catalysis, optical properties, topological materials, and defect analysis using density functional approaches.

Unconventional Computing

Wei Lu (University of Michigan): His research explores high-density memory based on two-terminal resistive devices (RRAM), memristors, in-memory computing, neuromorphic circuits, aggressively scaled nanowire transistors, and emerging electrical devices.

AI for Biology

Limsoon Wong (National University of Singapore): He currently works mostly on knowledge discovery technologies and their application to biomedicine. He has also done, in the earlier part of his career, significant research in database query language theory and finite model theory.

AI for Chemistry

Artem Oganov (Skolkovo Institute of Science and Technology): He works in the field of computational materials discovery, study of matter at high pressures, and development of novel computational methodologies for predicting the structure and properties of materials.

AI for Chemistry

Xavier Bresson (NUS): His research focuses on Graph Deep Learning, a framework that merges graph theory and neural networks to tackle complex data domains. He will introduce Graph ViT, a novel approach leveraging Visual Transformers (ViT).

Xujie Si (University of Toronto): He focuses on developing learning-based techniques to help programmers build better software with less effort, integrating logic programming with differentiable learning systems.
#AIforMathematics

@emilyrlines.bsky.social
Emily Lines (University of Cambridge): She will discuss the challenges of using DL for analyzing tree and forest data. Her goal is to improve the extraction of ecologically meaningful information to address questions ranging from fundamental ecology to applied conservation.

@limes-bonn.bsky.social
Jürgen Bajorath (University of Bonn): His research focuses on cheminformatics, ML, and the development of computational methods for drug discovery. He will introduce the concept of chemical language models (CLMs), their preferred architectures, and their challenges.

Ron Dror (Stanford University): An expert in high-performance computing, ML, image analysis, molecular simulation, structural biology, and drug design. He leads a research group that applies molecular simulation and machine learning to guide the development of better medicines.
#AIforBiology

Zhang Yang (National University of Singapore): His research interests include AI and deep neural network learning, protein folding and structure prediction, and protein design and engineering.
#AIforBiology

Alex Aliper (Insilico Medicine): He pioneered the application of AI in multi-omics data for drug discovery and drug repurposing, generative chemistry, and generative biology, putting an AI-designed drug into human clinical trials.
#AIforBiology

Mario Lanza (NUS): He focuses on improving electronic devices, integrated circuits, and silicon microchips using all kinds of novel nanomaterials, with especial emphasis on 2D-materials. He will discuss the status of memristor-based neuromorphic computation.

Fabio Sciarrino (University of Rome La Sapienza): In recent years his research activity has focused on the implementation of quantum information protocols via integrated photonic circuits. His talk will explore Adaptive Boson Sampling as a pathway to quantum ML.

Marin Soljacic (MIT): He explores unconventional computing through nanophotonics, leveraging the unique properties of artificially engineered materials to develop novel computing approaches using photons instead of electrons.

Dongling Deng (Tsinghua University): His main research interests are quantum AI and quantum technologies. In his talk, he will provide a concise introduction to the field of quantum AI advantage.