LLM

The Role of Humans in Scientific Discovery in the Age of LLMs — Beyond Asking: Turning LLMs into Research Collaborators

Sir Bashir M. Al-Hashimi, Vice President, Research & Innovation, King’s College London (KCL); Distinguished Professor, Department of Engineering, Faculty of Natural, Mathematical & Engineering Sciences, King’s College London (KCL)

Apr 8, 12:00 - 14:15

B9 R2325

AI artificial intelligence LLM scientific research scientific knowledge Assistive Technology

Rather than offering definitive conclusions, this talk seeks to stimulate dialogue, question assumptions, and inspire new forms of collective thinking about the future of scientific research and doctoral training in an AI-driven world.

Yanda Meng

Assistant Professor, Bioengineering

artificial intelligence medical image analysis machine learning LLM Large Language Models

Yanda Meng designs AI models to improve medical imaging and clinical decision-making.

KAUST advances scalable AI through global collaboration

1 min read · Wed, Nov 12 2025

machine learning LLM Federated learning Distributed algorithms

KAUST brings global experts together to advance scalable AI and tackle the challenges of training large models.

From the Ball-Proximal (Broximal) Point Method to Efficient Training of LLMs

Peter Richtarik, Professor, Computer Science

Sep 16, 16:00 - 17:00

B1 L3 R3119

AI machine learning optimization algorithms LLM

This talk introduces the Ball-Proximal Point Method, a new foundational algorithm for non-smooth optimization with surprisingly fast convergence, and Gluon, a new theoretical framework that closes the gap between theory and practice for modern LMO-based deep learning optimizers.

Ahmar Husain

Visiting Student, Computer, Electrical and Mathematical Sciences and Engineering

Cyber Security Malware Analysis LLM

From the Ball-Proximal (Broximal) Point Method to Efficient Training of LLMs

Peter Richtarik, Professor, Computer Science

Sep 4, 12:00 - 13:00

B9 L2 R2325

AI machine learning optimization algorithms LLM

This talk introduces the Ball-Proximal Point Method, a new foundational algorithm for non-smooth optimization with surprisingly fast convergence, and Gluon, a new theoretical framework that closes the gap between theory and practice for modern LMO-based deep learning optimizers.

Muhammad Samiullah

Intern, Cyber Security and Resilience Technology

cybersecurity ML FPGA LLM

Cyber Security, FPGA security, AI/ML security