Skip Navigation

Research Distinguished Lecture Series

Skip Side Navigation

Research Distinguished Lecture Series

The Office of the Vice President for Research and Partnerships is pleased to announce the OU Research Distinguished Lecture Series. The University of Oklahoma will welcome two to three highly distinguished speakers each semester who are preeminent in their field of expertise who will speak to OU faculty and students about prominent global issues. Speakers will be selected who embody the spirit of innovation, boldness, and interdisciplinarity that characterize the OU research enterprise. Their lectures will focus on contemporary research and innovation topics within the fields of Natural Sciences, Engineering, Technology, the Humanities and Social Sciences, and the Fine Arts. These lectures will be accessible to an advanced yet non-specialist audience.

In order to launch the Research Distinguished Lecture Series (RDLS), I am soliciting input from Deans and their faculty across the campus for names of potential speakers whom the OVPRP could invite for the fall and spring semesters of the current academic year. Please provide your input to Melany Dickens-Ray (mdickens@ou.edu) no later than November 15, 2019 for the fall semester and no later than December 15, 2019 for the spring semester.

To launch the series, we have invited Distinguished Professor Vladimir Shalaev of Purdue University to be the first OU RDLS speaker. 

Plasmonic Metamaterials Meet Quantum

Featuring Vladimir M. Shalaev


Tuesday  November 19, 2019  10:30 A.M.

Fred Jones Jr. Museum of Art  |  Mary Eddy & Fred Jones Auditorium
Open to the public


Dr. Shalaev will review the current state of Quantum Technology, its promise for the future, and recent developments and novel applications for space-time-frequency metasurfaces. He will outline hybrid, plasmonic-photonic meta-structures for quantum information systems and discuss a new unorthodox approach for high-speed quantum photonics operating at THz rates. The use of plasmonics and machine learning to optimize light-matter coupling and speed up quantum processes so that they outpace quantum decoherence and losses at room temperature will be discussed.


Dr. Shalaev received his PhD in Physics at the Krasnoyarsk University in Russia. He specializes in nanophotonics, plasmonics, optical metamaterials, and quantum photonics. He has received several awards for his research in the field of nanophotonics and metamaterials, including the APS Frank Isakson Prize for Optical Effects in Solids, the Max Born Award of the Optical Society of America for his pioneering contributions to the field of optical metamaterials, the Willis E. Lamb Award for Laser Science and Quantum Optics, IEEE Photonics Society William Streifer Scientific Achievement Award, Rolf Landauer medal of the ETOPIM (Electrical, Transport and Optical Properties of Inhomogeneous Media) International Association, the UNESCO Medal for the development of nanosciences and nanotechnologies, and the OSA and SPIE Goodman Book Writing Award. H-index 98. He is a Fellow of the IEEE, APS, SPIE, MRS, and OSA. 

Vlad Shaleav

Vladimir M. Shaleav

Research Lecture Seminar Series

Machine-Learning-Assisted Photonics: From Optimized Design to Quantum Measurements

Featuring Alexandra Boltasseva


Monday  November 18, 2019  3:30 P.M.

Nielsen Hall | Room 170
Open to the public


Emerging photonic concepts such as optical metamaterials, metasurfaces, novel lasers, single-photon sources and other quantum photonic devices together with novel optical material platforms promise to bring revolutionary advances to information processing and storage, communication systems, energy conversion, imaging, sensing, and quantum information technology. In pursuit of the next generation of photonic technologies, machine learning approaches have emerged as a powerful tool to discover unconventional optical designs and even uncover new optical phenomena. In this talk, various photonic design approaches as well as emerging material platforms will be discussed, showcasing machine-learning-assisted topology optimization for efficient thermophotovoltaic metasurface designs as well as machine-learning enabled quantum optical measurements. The next steps on merging photonic optimization with artificial-intelligence-assisted algorithms and materials properties for designing advanced photonic components will be outlined.


Alexandra Boltasseva is a Professor at the School of Electrical and Computer Engineering at Purdue University. She received her PhD in electrical engineering at Technical University of Denmark, DTU in 2004. Boltasseva specializes in nanophotonics, nanofabrication, optical materials, plasmonics, and metamaterials. She was a 2018 Blavatnik National Award for Young Scientists Finalist and received the 2013 Institute of Electrical and Electronics Engineers (IEEE) Photonics Society Young Investigator Award, 2013 Materials Research Society (MRS) Outstanding Young Investigator Award, the MIT Technology Review Top Young Innovator (TR35) Award, the Young Researcher Award in Advanced Optical Technologies from the University of Erlangen-Nuremberg, Germany, and the Young Elite Researcher Award from the Danish Council for Independent Research. She is a Fellow of the Optical Society of America (OSA) and a Fellow of SPIE. She served on the MRS Board of Directors and is Editor-in-Chief for OSA’s Optical Materials Express.

Alexandra Boltasseva


Visual Analytics and Trusted Information for Effective Decision Making

Featuring David Ebert


Wednesday November 20, 2019  10:30 A.M.

Devon Hall  | Room 120
Open to the public


Information, not just data, is key to today’s global challenges. To solve these challenges requires advancing big data analytics as well as new analysis and decision-making environments that enable reliable decisions from trustable, understandable information that goes beyond current approaches to machine learning and artificial intelligence.

These environments are successful when they effectively couple human decision making with advanced, guided spatial analytics in human-computer collaborative discourse and decision making (HCCD). Our HCCD approach builds upon visual analytics, natural scale templates, traceable information, human-guided analytics, and explainable and interactive machine learning, focusing on empowering the decision-maker through interactive visual analytic environments where non-digital human expertise and experience can be combined with state-of-the-art and transparent analytical techniques. 

When we combine this approach with real-world application-driven research, not only does the pace of scientific innovation accelerate, but impactful change occurs. I’ll describe how we have applied these techniques to challenges in sustainability, security, resiliency, public safety, and disaster management.


David Ebert is the Silicon Valley Professor of Electrical and Computer Engineering at Purdue University, a Fellow of the IEEE, director of the Center for Education and Research in Information Assurance and Security (CERIAS), and director of the Visual Analytics for Command Control and Interoperability Center (VACCINE), the Visualization Science team of the Department of Homeland Security’s Command Control and Interoperability Emeritus Center of Excellence.

Ebert performs research in visual analytics, human-computer teaming, advanced predictive analytics, volume rendering, illustrative visualization, and procedural abstraction of complex, massive data. He is the recipient of the 2017 IEEE Computer Society vgTC Technical Achievement Award for seminal contributions in visual analytics. He has been very active in the visualization community, serving as Editor in Chief of IEEE Transactions on Visualization and Computer Graphics, serving as IEEE Computer Society Vice President and the IEEE Computer Society’s VP of Publications, and successfully managing a large program of external funding to develop more effective methods for visually communicating information.

David Ebert