Sabre Kais

Sabre Kais is a Distinguished Professor of Chemistry and Professor of Chemical Physics at Purdue University, with courtesy appointments in Computer Science and Physics. He joined Purdue in 1994 as an Assistant Professor and became a full professor in 2002. His research focuses on quantum information, quantum computing for complex systems, and quantum machine learning applications in chemistry and materials science. He holds leadership roles such as Research Director of the theory group at Qatar Environment and Energy Research Institute and External Research Professor at the Santa Fe Institute.

Education: BS, MS, and PhD in Chemical Physics from the Hebrew University (1983–1989), followed by a postdoc at Harvard University (1989–1994).

Research Interests: Quantum algorithms for quantum chemistry, entanglement in chemical reactions, quantum machine learning for drug discovery, and quantum simulation of spin liquids. His work bridges quantum information science with practical applications in chemistry and physics. Notable contributions include quantum annealing for factorization, entanglement-based chemical reaction analysis, and quantum computing with polar molecules.

Publications: Over 230 peer-reviewed articles, including influential works on quantum machine learning for electronic structure calculations and quantum simulation of avian compass dynamics. Recent focus areas include quantum algorithms for many-body systems and quantum state tomography techniques.

Awards: NSF Career Award (1997), Guggenheim Fellowship (2005), APS Fellow (2007), and the Herbert Newby McCoy Award (2019). His work has been recognized for advancing quantum technologies in chemistry.

Labs/Teams: Leads research groups at Purdue and QEERI, collaborating on projects like quantum information for quantum chemistry and quantum computing applications in energy research.