Addressing today’s most pressing technological and scientific challenges—from developing new therapeutics and biotechnologies to creating greener chemical processes—requires the ability to accurately model matter at large atomistic scales and with high speed. However, current simulation techniques can be prohibitively slow, imprecise, or computationally too costly, resulting in heavy reliance on physical experiments that are time-consuming, expensive, and subject to inherent limitations.
In response, we present a pioneering digital chemistry framework that integrates many-GPU high-performance computing, computational quantum chemistry, and machine learning, delivering unprecedented accuracy and scalability in chemical discovery—particularly for drug design. By leveraging novel algorithms and software optimizations, we overcome the steep computational barriers that have historically limited quantum chemistry at large molecular scales. Recognized with the 2024 Gordon Bell Prize, our approach enables the first quantum-level simulations of complex bioscale molecular systems with accuracy nearing that of physical experiments.
Through exascale supercomputing, agentic AI workflows, and machine learning models trained on quantum-accurate data, we streamline end-to-end simulation and design processes. These intelligent workflows reduce reliance on laboratory experiments, providing a fully automatable, cost-effective, adaptive, and accurate solution for investigating complex molecular phenomena.
The result is a powerful platform that accelerates chemical discovery, enhances molecular design, and redefines in silico research opportunities across chemistry, biology, and related fields.
Biography:
Prof. Giuseppe M. J. Barca is a leading expert in high-performance computing (HPC), artificial intelligence (AI), and digital chemistry, recognized for pioneering scalable algorithms that have redefined the limits of molecular modelling and in silico drug discovery. His research integrates HPC, AI, and quantum chemistry to accelerate chemical R&D, enabling predictive simulations with accuracy close to physical experiments.
From 2018 to 2023, Barca led Australia’s only contribution to the U.S. Department of Energy’s Exascale Computing Project, collaborating with Georgia Tech, Argonne, Oak Ridge, and Ames National Laboratories as well as NVIDIA, Intel, AMD, and Cray. Between 2020 and 2024, his team set four world records in quantum chemical modelling, culminating in the 2024 ACM Gordon Bell Prize for enabling the first quantum-accurate simulations of biomolecular systems and the first-ever exaflop-scale computation in double precision. In 2025, he received the WATOC Dirac Medal, the highest international recognition in theoretical and computational chemistry for researchers under 40.
In 2023, Barca co-founded QDX Technologies, a deep-tech company with operations in Singapore, Melbourne, and Canberra, where he serves as Head of Research. Alongside this role, he leads academic teams at the Australian National University, focusing on high-performance computing, and at the Monash Institute of Pharmaceutical Sciences, advancing AI- and quantum-driven drug discovery.