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Professor of Chemistry, received his B.S. in 1997 from Pennsylvania State University, where he worked in the group of Prof. Ayusman Sen on palladium-catalyzed co- and terpolymerizations. He earned his Ph.D. from the University of California, Berkeley in 2003 under the guidance of Prof. T. Don Tilley, primarily focused on the development of new catalytic C–H bond functionalizations. Following postdoctoral work at the Swiss Federal Institute of Technology (ETH Zürich) with Antonio Togni investigating catalytic asymmetric hydroamination and hydrophosphination, Aaron joined the chemistry faculty at Iowa State University in 2005. He was promoted to associate professor in 2011, and to professor in 2016.
Dr. David Stracuzzi is a Principal Member of Technical Staff at Sandia National Laboratories and has been studying machine learning and artificial intelligence for 20 years. He currently leads several projects that apply data-driven modeling and uncertainty analysis methods to tasks related to remote sensing data, pattern-of-life data, geophysical data, and data related to physics-based simulations. Prior to joining Sandia in 2010, Dr. Stracuzzi was a member of the research faculty at Arizona State University working on computational cognitive architectures for developing intelligent agents.
Tim Draelos has been at Sandia for over 32 years and received his Ph.D. at UNM in 1998, focusing on constructive neural networks. He has spent the last ten years conducting deep learning R&D, including work on seismic signal detection, phase identification, and event discrimination. He chaired special sessions on Machine Learning in Seismology at the 2016 and 2017 Seismological Society of America annual meetings and 2017 American Geophysical Union fall meeting. He has taught classes on machine and deep learning and was the founder and general chair of the 1st three Sandia Machine Learning and Deep Learning Workshops, starting in 2017. He has published papers in the Bulletin of the Seismological Society of America, Seismological Research Letters, and various machine learning conferences.
Susan Clark has been a scientist at Sandia National Laboratories since 2013 where she has worked on a variety of quantum information-related projects on different platforms, including trapped ions and gate-defined quantum dots in silicon. She is currently the PI of the DOE-funded Quantum Scientific Computing Open User Testbed (QSCOUT) at Sandia, a project which aims to build, maintain, and provide access to quantum hardware based on trapped ions to scientists around the world. Prior to joining Sandia, she did her postdoctoral work at the Joint Quantum Institute at University of Maryland with Chris Monroe. There, she researched quantum networking with trapped ions via photons and robust two-qubit gates via phonons. Prior to her postdoctoral work, she graduated with a PhD and Masters in Applied Physics from Stanford University in 2010. At Stanford, under the direction of Professor Yoshi Yamamoto, she studied and characterized a variety of optical solid-state qubits including electron spins of silicon donors in bulk GaAs and single fluorine donors in ZnSe.
Assistant Scientist, Nanoscience
- First-principles modeling of charge and energy transport in nanoscale materials.
- Optoelectronic properties of nanomaterials and heterogeneous interfaces
- Development of novel methods for the computation of electron and exciton dynamics
- Wave-like charge and energy transport in mesoscale devices
- Current- and bias-driven structural evolution
Staff scientist at the Center for Nanoscale Materials
He has developed a research program exploring materials discovery, synthesis, characterization, and processing. We are leading the discovery of new low-dimensional materials, the exploration of novel synthesis and characterization, and tailoring material properties.
Tuan Ho is a Senior Member of the Technical Staff in the Geochemistry Department at Sandia National Laboratories. He earned his Bachelor of Engineering from Ho Chi Minh City University of Technology, Vietnam and his PhD from University College London, UK. His research interests include molecular interaction/properties in natural/engineering nanoporous materials related to subsurface applications: shale gas production, nuclear waste disposal, carbon dioxide capture and geological storage.
Research focuses on experimental study of hybrid quantum systems involving magnon spintronics, integrated photonics, and nanomechanics, aiming at developing high-fidelity quantum transducers for distributed quantum networks. Such interdisciplinary research not only studies the quantum coherent phenomena of individual quantum information carriers but also seeks enhancement of their coherent interactions. Research interests also include developing integrated photonic sensors for biochemical sensing with high sensitivity and specificity, as well as wireless sensor networks in extreme conditions such as in subterranean environments.
Thomas Schenkel is a physicist and senior scientist at Lawrence Berkeley National Laboratory, where he is the interim Director of the Accelerator Technology and Applied Physics Division (http://atap.lbl.gov/). Thomas received his Ph.D. in physics from the Goethe University in Frankfurt. Following time as a postdoc at Lawrence Livermore National Laboratory, he joined Berkeley Lab. His research interests include novel accelerator concepts, materials far from equilibrium, exploration of fusion processes, and spin qubit architectures. Thomas also teaches a graduate course on particle accelerators at UC Berkeley.
Thomas worked on variations of time-of-flight mass spectrometry to characterize the environment of bio-molecules as a postdoc. This theme has now come up in the current Covid-19 crisis with new ideas for mass spectrometry and imaging of viruses in droplets.
COVID-19-related research: "Laser, Biosciences Researchers Combine Efforts to Study Viruses in Droplets"
Areas of expertise: accelerators, fusion, lasers, quantum, spin qubits
Title: Associate Professor of Physics ad Astronomy, Tufts University/Senior Scientist, Computer Science Initiative
Expertise: Quantum Computing
In 2015 Love joined the Physics Department at Tufts University as an Associate Professor with Tenure. In 2018 he joined Brookhaven National Lab’s Computational Science Initiative as a Senior Scientist in a dual appointment held concurrently with his Tufts appointment. He serves as the Chair of the Scientific Advisory Board of Zapata Computing, Inc., a Boston-based quantum software startup. He is a member of FQXi.
In quantum information science Love has worked broadly on quantum simulation, including work on quantum simulation of quantum chemistry and high energy physics and on quantum lattice-gas and quantum cellular automata models. Love has also worked on adiabatic quantum computing, the theory of entanglement, on semiclassical descriptions of quantum information including wigner functions for qubits and qudits, and on efficient simulation of subtheories of quantum mechanics that lack contextuality.