Lab Partnering Service Discovery
Use the LPS faceted search filters, or search by keywords, to narrow your results.
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"
Ben Brown is a statistical scientist in the Environmental Genomics and Systems Biology division within Berkeley Lab’s Biosciences Area. He specializes in the development of novel machine algorithms, usually for the biological and environmental sciences at Berkeley Lab. His group develops “third-wave” learning algorithms that combine the interpretability and reliability of classical statistics with the predictive performance of deep learning. They specialize in designing learning paradigms for complex, high-dimensional systems that enable accurate uncertainty quantification, model discovery, feature selection, and inference. Dr. Brown's expertise include statistics, machine learning, deep learning, and artificial intelligence.
COVID-19-related research: "Using Machine Learning to Estimate COVID-19's Seasonal Cycle". Other principal investigators include: Eoin Brodie, Nicola Falco, Dan Feldman, Zhao Hao, Chaincy Kuo, Joshua Ladau, and Haruko Wainwright.
Eleanor A. Blakely, is a Lawrence Berkeley National Laboratory (LBNL) Senior Staff Biophysicist with 45 y of professional experience in molecular, cellular and animal radiobiological research directed at studying the basic mechanisms of radiation responses, with an emphasis on charged particle radiation effects. She is also a Clinical Professor of Radiation Medicine (nontenured) at Loma Linda University, School of Medicine, Loma Linda, California. Dr. Blakely earned a PhD in Physiology from the University of Illinois at Champaign-Urbana as a U.S. Atomic Energy Commission Special Fellow in Radiation Science and Protection.
Her professional activities have included service on advisory panels for several hospitals, universities, and numerous federal agencies including the U.S. Department of Energy (DOE), the National Institutes of Health (NIH), and the National Aeronautics and Space Administration (NASA); on Editorial Boards for several journals: Space Power, Radiation Research, Journal of Radiation Research, and NPJ Microgravity; Appointed Member, Diagnostic Radiology Study Section-Division of Research Grants, NIH; Advisory Committee Member, International Atomic Energy Agency; Scientific Director, NASA Space Research Summer School; and Elected Officer of the Radiation Research Society: Biology Councilor and Secretary-Treasurer.
In 2000 she was elected to NCRP, and has served on Scientific Committee (SC) 75 that produced NCRP Report No. 132, Radiation Protection Guidance for Activities in Low-Earth Orbit; and SC 1-7 that produced NCRP Report No. 153, Information Needed to Make Radiation Protection Recommendations for Space Missions Beyond Low-Earth Orbit. She has received several awards including the Robert Emerson Graduate Teaching Award, School of Life Sciences, University of Illinois, the Lawrence Berkeley Laboratory Outstanding Performance Award, the DOE Office of Science Outstanding Mentor Award, the Lawrence Berkeley Laboratory Technology Transfer Award, and an RD100 award from Research and Development Magazine.
She leads the Data Science Engagement Group at the National Energy Research Scientific Computing Center (NERSC) at Berkeley National Lab. A native of the U.K., her career spans research in particle physics, cosmology, and computing on both sides of the Atlantic. She obtained her Ph.D. at Edinburgh University, and worked at Imperial College London and SLAC National Accelerator Laboratory before joining NERSC. Her group leads the support of supercomputing for experimental science, and her work focuses on data-intensive computing and research. This includes using high-performance computing (HPC) to scale up machine-learning algorithms that can tackle new, larger scientific problems; and leveraging artificial intelligence to gain insight from cosmological data.
Mike's research interests are in mathematical modeling of environmental systems and quality, uncertainty analysis, value-of-information decision analysis, water-energy integrated assessment, and sensor-data fusion. Mike has a PhD in Civil and Environmental Engineering and an MS degree in Engineering and Public Policy from Carnegie Mellon University. He also has MS and BS degrees in Mechanical Engineering from UCLA. Mike is a California-licensed Professional Engineer (Civil), and has worked at an environmental engineering firm where he conducted environmental health risk assessments. He is Leader of the Sustainable Energy Systems Group and former Leader of the Airflow and Pollutant Transport Group (Indoor Environment Dept.). Mike has been at LBNL since 1998.
COVID-19-related research: "New Research Launched on Airborne Virus Transmission in Buildings"
Michael Connolly is a Principal Scientific Engineering Associate at the Molecular Foundry at Lawrence Berkeley National Laboratory and an organic chemist with 20+ years of expertise in combinatorial and automated synthesis methods and nanomaterial discovery. His research focus is the development of combinatorial discovery technologies and new biopolymer nanomaterials. He has developed a class of bio-inspired polymer called ‘peptoids’ that have found utility in drug discovery, drug delivery, diagnostics, and materials science. Key contributions included the development of new synthetic methods, new sequencing, and characterization methods for peptoids.
Additional information available at this link.
COVID-19-related research: "Scientists Aim Gene-Targeting Breakthrough against COVID-19" (cellular delivery system/anti-viral agent)
Dani Ushizima PhD, is a Staff Scientist at Lawrence Berkeley National Laboratory, a Data Scientist at UC Berkeley and an Affiliate Faculty at UC San Francisco. More than a decade at LBNL, her research in image analysis and pattern recognition has impacted a broad array of scientific investigation that depends on experimental data, particularly images. In 2015, Ushizima received the U.S. Department of Energy Early Career award to focus on pattern recognition applied to diverse scientific domains, such as structural analysis of materials science samples. She is also recipient of the Science without Borders Researcher award (CNPq/Brazil) for her work on machine learning applied to cytology, as part of an initiative focused on public healthcare. She has also led the Image Processing team for the Center for Advanced Mathematics for Energy Related Applications (CAMERA). Recently, she's been investigating lung scans for COVID-19 screening as part of initiatives related to the National Virtual Biotechnology Laboratory (NVBL).
COVID-19-related research: "Can CT Scans Be Used to Quickly and Accurately Diagnose COVID-19?"
Dr. Turqueti is currently a Research Engineer at Lawrence Berkeley National Laboratory (LBNL). He received his PhD in Electrical Engineering from the Illinois Institute of Technology.
Author or co-author of over 100 publications, his research interests are in the areas of electronics and signal processing for harsh environments especially those operating at high levels of radiation, cryogenic temperatures, or high magnetic fields. He works on projects funded by the Department of Energy (DOE) office of science, and by the Defense Threat Reduction Agency (DTRA).
Previously he worked at Fermi National Accelerator Laboratory (Fermilab) whereas an engineer he developed and researched electronics and signal processing algorithms for the CDF and D0 experiments. Dr.Turqueti lead at Fermilab the integration efforts for the US-CMS forward pixel detector.
In the private sector, Dr.Turqueti served as vice-president of technology at Creative Electron Inc, where he was the principal investigator and technical manager for several radiation detection projects for the Department of Homeland Security (DHS), Defense Advanced Research Projects Agency (DARPA) and DOE.
His professional activities included serving on a variety of advisory panels, conference committees, and as a reviewer for DOE Small Business Innovation Research (SBIR), and several journals, including IEEE Transactions on Nuclear Science and IEEE Transactions on Applied Superconductivity.