Roger Melko

Dr. Melko's research interests involve strongly-correlated many-body systems, with a focus on emergent phenomena, ground state phases, phase transitions, quantum criticality, and entanglement. He emphasizes computational methods as a theoretical technique, in particular the development of state-of-the-art algorithms for the study of strongly-interacting systems. Dr. Melko's work has employed computer simulations to explore the low-temperature physics of classical and quantum magnetic materials, cold atoms in optical lattices, bosonic fluids and quantum computers. He is particularly interested in microscopic models that display interesting quantum behavior in the bulk, such as superconducting, spin liquid, or topological phases. He is also interested in broader ideas in computational physics, the development of novel algorithms such as machine learning for simulating quantum mechanical systems on classical computers, and the relationship of these methods to the field of quantum information science.

• Entanglement in Condensed Matter Systems

• Unconventional Quantum Criticality

• Frustrated Quantum Magnets

• Supersolid and Superglass phases

• Quantum Monte Carlo

• Machine learning

• Condensed Matter

• Quantum Science

• 2005 PhD Physics, University of California, Santa Barbara, Santa Barbara, California, USA

• 2003 MA Physics, University of California, Santa Barbara, Santa Barbara, California, USA

• 2001 MSc Physics, University of Waterloo, Waterloo, Ontario, Canada

• 2000 BSc Physics, University of Waterloo, Waterloo, Ontario, Canad

• 2021 CAP/DCMMP Brockhouse Medal

• 2016, Herzberg Medal, Canadian Association of Physicists

• 2013, Canada Research Chair in Computational Quantum Many-Body Physics, Natural Sciences and Engineering

• 2012, Young Scientist Prize in Computational Physics, International Union of Pure and Applied Physics (IUPAP)

• 2010, Early Researcher Award, Ontario Ministry of Research and Innovation

• Faculty Affiliate, Vector Institute for Artificial Intelligence

• Affiliate, Institute for Quantum Computing

• Associate Faculty, Perimeter Institute for Theoretical Physics

• PHYS 449 - Machine Learning in Physics
  • Taught in 2021, 2025
• PHYS 490 - Special topics in Physics
  • Taught in 2020
• PHYS 705 - Statistical Physics 2
  • Taught in 2021, 2023, 2025
• PHYS 739 - Quantum Many Body Physics
  • Taught in 2022, 2024

* Only courses taught in the past 5 years are displayed.

• March 20, 2014: Pseudogap Theory Puts Physicists Closer to High Temperature Superconductors
• January 13, 2012: UW prof finds way to split virtual electron.