Quantum Algorithms for Bio and Life Sciences

2024 IEEE International Conference on Quantum Computing and Engineering

Teague Tomesh will be a panelist at the 2024 IEEE International Conference on Quantum Computing and Engineering on the Quantum Algorithms for Bio and Life Sciences at Montréal, Québec, Canada. 

Date: Wed, Sep 18, 2024

Time: 10:00-16:30 Pacific Time (EDT) — UTC-4

Montréal, Québec, Canada

 - About this Workshop -

As the field of quantum computing rapidly advances, its potential applications in the realms of bioinformatics and life sciences are becoming increasingly important. This workshop aims to explore the recent breakthroughs and future prospects of quantum computing in addressing complex challenges in biotechnology, pharmaceuticals, healthcare, and related disciplines. By convening researchers from both industry and academia, the workshop seeks to facilitate the exchange of recent findings and collaborative discussions on effective pathways for applying these techniques to address real-world challenges in these domains.

The target audience includes experts in quantum algorithms interested in applying them to computational biology, drug discovery, and other human health applications, as well as biochemistry and other experts exploring quantum algorithms for their most computationally intensive problems. Most of the talks should be accessible to the general audience interested in prospects for practical application of quantum algorithms to bio and life sciences. The workshop will be structured to cater to participants with different levels of expertise in quantum computing and should be of interest to early career researchers and students curious about the applications of quantum computing for bio and life sciences.

Confirmed Speakers

• Teague Tomesh (Infleqtion), "On the potential for quantum advantage in feature selection applications for multimodal cancer data"

• Antonio Mezzacapo (IBM), "Chemistry Beyond Exact Solutions on a Quantum-centric Supercomputer"

• Jonathan Wurtz (QuEra), "Quantum solutions for binding affinities and protein NMR spectral inference"

• Rob Parrish (QC Ware) "Quantum Chemistry for Pharmacology: Progress and Challenges with Hybrid Quantum/Classical Methods"

• Sabrina Maniscalco, Stefan Knecht (Algorithmiq), TBA

• Alexey Galda (Moderna), "mRNA secondary structure prediction using utility-scale quantum computers"

• Anthony Smaldone (Yale), "Hybrid Quantum-Classical Neural Networks for Drug Discovery "