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WIFIRE Commons Team

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James Ahrens, Ph.D.

Visualization Expert

Dr. James Ahrens is the Director of the Information Science and Technology Institute (ISTI) and a senior scientist at Los Alamos National Lab (LANL). He is also the Founder and Design Lead of ParaView, an open-source visualization tool designed to handle extremely large data. ParaView has been downloaded over two million times, and is in use at supercomputing and scientific centers worldwide. His primary research interests are visualization, computer graphics, and parallel systems.

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İlkay Altıntaş, Ph.D.

PI / Founding Director

Dr. İlkay Altıntaş is the Chief Data Science Officer and the Founding Director of the Workflows for Data Science (WorDS) Center of Excellence and WIFIRE Lab at the San Diego Supercomputer Center, UCSD. She has worked on different aspects of scientific workflows as a principal investigator and in other leadership roles across a wide range of cross-disciplinary projects. She is a co-initiator of and an active contributor to the open-source Kepler Scientific Workflow System.

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Yvonne Andres, Ph.D.

Broadening Participation Expert

Dr. Yvonne Andres is the President and CEO of the Global SchoolNet Foundation, Founder of the Global Schoolhouse and is the former Vice President of Internet Learning Programs and Partnerships at Lightspan, Inc. She was inducted into the Internet Hall of Fame in 2017 for her work and global social impact. An educator for nearly two decades, she has taught pre-school through university and is dedicated to demonstrating and documenting the power of "Internet style learning."

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Jessica Block

Convergence Expert

Jessica Block is the Associate Director for Operational Programs of the WIFIRE Lab at the San Diego Supercomputer Center, UCSD. Her work aims to mitigate disasters using emerging technologies including satellites, sensor networks, machine learning tools, and virtual reality. She has spent her career addressing fire, water, and geologic risks in the American West and Southeastern Australia. In 2019, she was appointed by Gov. Gavin Newsom to the California Wildfire Safety Advisory Board.

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Somya Sharma Chatterjee

Physics-Guided Machine Learning Expert

Somya Sharma Chatterjee is a Ph.D. student at the University of Minnesota-Twin Cities. She is working on applications of statistical machine learning to solve climate sciences problems. Under the supervision of Dr. Vipin Kumar and Dr. Snigdhansu Chatterjee, she is working on utilizing Bayesian spatio-temporal and physics-informed deep learning techniques to address estimation and inference challenges for uncertainty quantification.

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Weizhe Chen

Optimization Expert

Weizhe Chen is currently a first-year Ph.D. student in the Department of Computer Science at the University of Southern California (USC), where his advisor is Dr. Bistra Dilkina. His research interest lies in artificial intelligence, including machine learning, optimization, decision making, multi-agent systems, and computational sustainability. He is especially interested in machine learning with optimization objectives and optimization with machine learning surrogates.

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Laura Condon, Ph.D.

Moisture Expert

Dr. Laura Condon is an assistant professor in the Department of Hydrology and Atmospheric Sciences at Arizona University. She is interested in large-scale water sustainability and the dynamic behavior of managed hydrologic systems in the context of past development and future climate change. Her work combines physically based numerical modeling with observations and statistical techniques to evaluate large systems using rigorous quantitative methods.

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Daniel Crawl, Ph.D.

BurnPro 3D Development Lead

Dr. Daniel Crawl is the Associate Director for Products of the WIFIRE Lab at the San Diego Supercomputer Center, UCSD. He is one of the lead developers of the Kepler Scientific Workflow System and has advanced experience in working with applications of workflows in bioinformatics, geoinformatics, oceanography, and computational physics. He is the lead architect for the overall integration of many modules in Kepler including distributed data parallel (DDP) execution patterns.

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Raymond de Callafon, Ph.D.

Data Conditioning Expert

Dr. Raymond de Callafon is a professor with the Department of Mechanical and Aerospace Engineering (MAE), UCSD. His teaching and research cover many aspects of signal processing, estimation, experiment-based modeling, and adaptive control. Dr. de Callafon designs and analyzes experiment-based modeling techniques for control relevant identification of linear systems and extends these techniques to specific classes of (block) non-linear and linear parameter varying (LPV) systems.

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L. Turin Dickman

Live Fuels Expert

Turin Dickman is a staff scientist in the Earth and Environmental Sciences Division at Los Alamos National Lab (LANL). Her current research applies her expertise in plant ecophysiology to understand the live fuel moisture and structure dynamics that influence fire behavior and ecological fire effects. Her work is supporting the integration of live fuel moisture models into FIRETEC and providing field data to validate 3D fuel structure and moisture simulations.

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Bistra Dilkina, Ph.D.

Optimization Expert

Dr. Bistra Dilkina is the Co-Director of the University of Southern California (USC) Center for AI in Society (CAIS), a joint effort between the USC Viterbi School of Engineering and the USC Suzanne Dworak-Peck School of Social Work. She is one of the junior faculty leaders in the young field of computational sustainability and her research focuses on advancing the state of the art in combinatorial optimization techniques for solving real-world large-scale problems, particularly ones that arise in sustainability areas.

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Charles Erwin

Convergence Expert

Charles Erwin is a research project manager at UCSD’s Calit2/Qualcomm Institute and San Diego Supercomputer Center. He works closely with Drs. Larry Smarr, Thomas DeFanti, İlkay Altıntaş, and their respective teams on a number of cyberinfrastructure and personalized medicine projects. Additionally, Erwin develops web-based applications and designs custom wireless gestural interfaces to visualize and interact with biomedical longitudinal time-series data.

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Melissa Floca

Broadening Participation Lead

Melissa Floca is the Director of Strategic Partnerships at the Cyberinfrastructure and Convergence Research and Education (CICORE) Division of the San Diego Supercomputer Center, UCSD. She also serves as the Senior Advisor for Cross-Border Initiatives at the University of San Diego's Kroc Institute for Piece and Justice (IPJ), where she launched the Border Fellows Program to create a cross-border network of local scholars, practitioners, and policymakers focused on creating a peaceful U.S.-Mexico border region.

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James H. Furman

Convergence Advisory Board Chair

James H. Furman serves as a USFS liaison to the U.S. Department of Defense. He previously served as Chief of the Air Force Wildland Fire Center (AFWFC) and as Eglin Air Force Base's (Eglin AFB) Wildland Fire Program Manager. Eglin AFB's prescribed fire program tripled its productivity under his leadership, becoming a national leader with an average of approximately 125 prescribed fires and more than 100,000 acres/year over the last five years of his tenure there.

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Yolanda Gil, Ph.D.

Co-PI / Commons Framework Co-Lead

Dr. Yolanda Gil is the Senior Director for Major Strategic AI and Data Science Initiatives at USC's Information Sciences Institute (ISI). As principal scientist, they lead the Interactive Knowledge Capture research group, which is part of AI@ISI. Their research focuses on intelligent interfaces for knowledge capture, which is a central topic in our projects concerning knowledge-based planning and problem solving, semantic annotation, agent and software choreography, and information analysis and assessment of trust.

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Daniel Rosales Giron

Weather Expert

Daniel Rosales Giron is the Fire Modeling Program Lead at Tall Timbers Research Station. He co-developed the coupled fire-atmospheric model called QUIC-Fire. His research has focused on the application of fire behavior models to complex environments, looking at different scales and levels of detail of fuel representation and their effects on fire behavior. He also hopes to become an effective liaison between academia and fire managers, helping bridge the gap between science and application. 

 

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Attila Gyulassy, Ph.D.

Visualization Expert

Dr. Attila Gyulassy is a research computer scientist who works with Dr. Valerio Pascucci at the Scientific Computing and Imaging Institute, University of Utah. His work involves visualization, topological data analysis, and explainable AI. His principal research interests involve developing and applying techniques from computational topology to solve analysis problems in a variety of scientific domains. His research has also been focused on using the Morse-Smale complex to solve various analysis problems.

 

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J. Kevin Hiers

Co-PI / Fire Science Co-Lead

J. Kevin Hiers is an associate scientist at Tall Timbers Research Station where he leads wildland fire research and training applications. For more than 25 years, he has worked at the interface between management and science. His program applies research to support the safe and effective use of prescribed fire through research on interacting fire lines, fire-atmospheric feedback driving smoke transport, and mechanistic understanding of fire effects. He is one of the co-founders of the Prescribed Fire Science Consortium.

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Deborah Khider, Ph.D.

Model Repository Manager

Dr. Deborah Khider is a data scientist at USC's Information Sciences Institute (ISI). Her domain of research lies at the intersection of geoscience and artificial intelligence; applications of her research can be found in the fields of paleoclimatology, data science, machine learning, and scientific workflows. She is particularly interested in using AI to advance the field of paleoclimatology, via the development of tools to annotate and retrieve data, workflows for analysis, and machine learning techniques for predictions.

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Michael Kleeman

Business Development Expert

Michael Kleeman is a senior fellow at UCSD, associated with the School of Global Policy & Strategy and the San Diego Supercomputer Center, where he works on critical infrastructure resilience, cloud computing policy and cross border research coordination. Kleeman leads the strategy and scenario planning effort at the American Red Cross, where he supports the SVP for Disaster and has worked with the Offices of Emergency Services and Homeland Security in California on disaster preparedness and response.

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Vipin Kumar, Ph.D.

Physics-Guided Machine Learning Expert

Dr. Vipin Kumar is a regents professor at the University of Minnesota, where he holds the William Norris Endowed Chair in the Department of Computer Science and Engineering. His research spans data mining, high-performance computing, and climate applications, and has resulted in the development of the following: the concept of isoefficiency metric for evaluating the scalability of parallel algorithms, and software for sparse matrix factorization (PSPASES) and graph partitioning (METIS, ParMetis, hMetis).

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Samuel Leventhal

Visualization Expert

Samuel Leventhal is a Ph.D. candidate studying computer science at the University of Utah within the Scientific Computing and Imaging Institute under Dr. Valerio Pascucci and a research collaborator with Lawrence Livermore National Laboratory. His research interests include the interpretability of artificial intelligence and the application and/or development of topologically informed machine learning models, as well as the theoretical foundation and capabilities of quantum computing from a categorical or functional perspective.

 

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Rodman Linn, Ph.D.

Co-PI / Fire Science Co-Lead

Dr. Rodman Linn is the Associate Director for Fire Science of the WIFIRE Lab at the San Diego Supercomputer Center, UCSD, and a senior scientist in the Earth and Environmental Sciences Division at Los Alamos National Lab (LANL). For over two decades, he has served as principal investigator for a process-based coupled fire/atmosphere model, FIRETEC. He leads LANL efforts to use next-generation process-based wildfire models for the study of fundamental wildfire behavior and the evaluation of prescribed fire tactics.

 

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David Marvin, Ph.D.

Boutique Fuels Expert

Dr. David Marvin is the Co-Founder & CEO of Salo Sciences, Inc. He is an expert in conservation policy and forest carbon mapping, and previously worked at the Carnegie Institution for Science’s Department of Global Ecology and The Nature Conservancy (TNC). At TNC, he led a comprehensive report that evaluated the potential for natural climate solutions to increase carbon sequestration and offset the state’s emissions, which is now used to guide California’s policies reducing emissions from natural and working lands.

 

 

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Dr. Aaron Maxwell is an assistant professor of geography in the Department of Geology and Geography at West Virginia University. Prior to teaching, he served as a remote sensing analyst at the Natural Resource Analysis Center (NRAC) at West Virginia University, where he worked on mapping and geospatial modeling tasks related to natural resource management. His research interests include land cover mapping, machine learning, LiDAR, image analysis, geomorphology, and landscape change.

 

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Mai Nguyen, Ph.D.

AI Innovations Co-Lead

Dr. Mai Nguyen is the Associate Director for AI of the WIFIRE Lab and the Lead for Data Analytics at the San Diego Supercomputer Center, UCSD. Her research centers on applying artificial intelligence, deep/machine learning, and data science techniques to interdisciplinary problems. She has worked in many domains, including remote sensing, spacecraft autonomy, satellite image processing, medical image analysis, knowledge extraction from text, and object detection and data analysis for wildfire mitigation.

 

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Russell A. Parsons, Ph.D.

Fuel Modeling Expert

Dr. Russell A. Parsons is a research ecologist with the Fire, Fuels and Smoke research program at the USFS Rocky Mountain Research Station, Fire Sciences Lab in Missoula, MT. His research spans multiple time and space scales, ranging from landscape fire and vegetation simulation modeling to highly detailed 3D fuel and physics-based fire modeling. A key theme of his current work is the development of 3D data to improve our capacity to plan and implement fuel treatments.

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Valerio Pascucci, Ph.D.

Visualization Expert

Dr. Valerio Pascucci is the Founding Director of the Center for Extreme Data Management Analysis and Visualization (CEDMAV) of the University of Utah. He is also a faculty of the Scientific Computing and Imaging Institute, a professor of the School of Computing, University of Utah, and a laboratory fellow of PNNL. His research interests include Big Data management and analytics, progressive multi-resolution techniques in scientific visualization, and discrete topology.

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Rohan Patil

Physics-Guided Machine Learning Expert

Rohan Patil is a master's student studying computer science and specializing in artificial intelligence at UCSD, where he is a part of Dr. Rose Yu's Spatiotemporal Machine Learning Research Group. His research interests include exploring deep learning techniques for modeling dynamical systems, and reducing the computational footprint of deep learning models. During his undergraduate career, he worked on gravitational wave detection and modeling the spread of COVID-19.

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Michael Pazzani, Ph.D.

AI Innovations Co-Lead

Dr. Michael Pazzani is a distinguished scientist at the Halıcıoğlu Data Science Institute at UCSD. He conducts research in machine learning, explainable AI (a topic in which he currently runs a DARPA-sponsored project), personalization, internet search, and recommendation systems. His scholarship is in areas including causal inference and Bayesian statistics. Prior to joining UCSD, Dr. Pazzani was the Vice Chancellor for Research and Economic Development at UCR.

 

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Ismael Perez

Staff Researcher

Ismael Perez is a computational and data science research specialist with the Workflows for Data Science (WorDS) Center of Excellence and WIFIRE Lab at the San Diego Supercomputer Center, UCSD. He is currently developing cyberinfrastructure that links distributed computing with edge computing under the project Sage: A Software Defined Sensor Network. His research interests are edge computing, distributed computing, parallel computing, and composable systems.

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Varun Ratnakar

Model Commons Expert

Varun Ratnakar is the Director of Karya Ltd., London and a research consultant for USC's Information Sciences Institute (ISI). As a consultant with ISI, he has worked on workflow composition for the Model Integration through Knowledge-Rich Data and Process Composition project, also known as MINT. He has worked in various AI research projects pertaining to knowledge representation, knowledge acquisition, knowledge graphs and semantic workflows.

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Rukmini Ravi

Project Coordinator

Rukmini Ravi serves as the Project Coordinator of the WIFIRE Lab and as a project policy analyst at the San Diego Supercomputer Center, UCSD. She assists in establishing partnerships between the WIFIRE Lab and the greater fire science and AI communities, and in communicating technical data and fire science concepts to multidisciplinary audiences. Rukmini also assists in the development of the SDSC Workflows for Data Science (WorDS) Center of Excellence and WIFIRE Lab websites.

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David Robinson

Fire Dynamics Expert

David Robinson is a Ph.D. student at Florida State University, studying computational fire dynamics. David also works as a graduate research assistant at Los Alamos National Lab (LANL), under the guidance of Dr. Rodman Linn. His research at LANL has focused on the incorporation of topography into the wind solver and fire routines of the QUIC-Fire model. David's research interests include scientific visualization and the development of fast-running algorithms for use in operational models.

 

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Daniel Roten, Ph. D.

Data Scientist

Dr. Daniel Roten is a computational data scientist at the San Diego Supercomputer Center, UCSD where he works on multiple research projects at the intersection of natural hazards and data-intensive computing. Previously, he was a computational seismologist at San Diego State University and co-developed the AWP-ODC wave propagation code with SDSC's High-performance Geocomputing Lab (HPGeoC). He also has experience in the use of deep learning for the prediction of earthquake shaking.

 

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David Saah, Ph.D.

Ignition Patterns Expert

Dr. David Saah is the Managing Principal of the Spatial Informatics Group, LLC and the Director of the Geospatial Analysis Lab at the University of San Francisco. He has expertise in a number of areas, including landscape ecology, hydrology, geomorphology, ecosystem modeling, natural hazard modeling, remote sensing, GIS and geospatial analysis. His research uses integrated geospatial science for multi–scale mapping, monitoring and modeling of environmental spatial heterogeneity.

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Eshwar Prasad Sivaramakrishnan

Optimization Expert

Eshwar Prasad Sivaramakrishnan is a master's student at the University of Southern California (USC) Viterbi School of Engineering, specializing in artificial intelligence. He is conducting research in the domain of optimization, under the guidance of Dr. Bistra Dilkina and Ph.D. student Weizhe Chen. His contributions to research projects include prototyping, and the building and testing of multi-objective optimization algorithms and evolutionary algorithms for risk mitigation.

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Nicholas Skowronski, Ph.D.

Fire Ecology Expert

Dr. Nicholas Skowronski is a research forester with the U.S. Forest Service and an adjunct assistant professor with the Department of Geology and Geography at West Virginia University. His current research focuses on the analysis of the structural characteristics of forest canopies and how this relates to carbon and water cycles. He develops methods for using LiDAR and other remote sensing techniques for wildfire mitigation and studies how forest functionality changes after disturbance.

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Li Tan

Data Conditioning Expert

Li Tan is a Ph.D. candidate in mechanical engineering at UCSD. He works with Prof. Raymond de Callafon on data conditioning and data assimilation for wildfire modeling. He has also served as a teaching assistant in courses covering domains such as signals and systems, as well as parametric identification, in the Department of Mechanical and Aerospace Engineering (MAE), UCSD. He has co-authored papers on wildfire wind condition estimation and recursively updating wildfire perimeters by using ensemble Kalman filtering.

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Berk Ustun, Ph.D.

Interpretability Expert

Dr. Berk Ustun is a visiting faculty researcher at Google AI and an incoming assistant professor at the Halıcıoğlu Data Science Institute (HDSI), UCSD. He previously served as a researcher at the Center for Research on Computation and Society at Harvard. His research lies at the intersection of machine learning, optimization, and human-centered design. He develops methods to promote the adoption and responsible use of machine learning in medicine and criminal justice.

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Ben Weintraub, Ph.D.

AI Gateway Expert

Dr. Ben Weintraub is a data scientist with the Workflows for Data Science (WorDS) Center of Excellence and WIFIRE Lab at the San Diego Supercomputer Center, UCSD. He has experience working with big data and applying machine learning techniques to address fundamental challenges in domains ranging from materials chemistry to medicine. He is currently involved with the development of workflows which help support analysis of data from wearable sensors.

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Lucas Wells, Ph.D.

AI Integration Expert

Dr. Lucas Wells is the Founder and CEO of Holtz Forestry, LLC, a company specializing in algorithm design, mathematical optimization, artificial intelligence and remote sensing, with the goal of integrating new technologies into the natural resource industry. He currently lives in Missoula, MT, where he manages a team of engineers who are currently developing new tools for modeling wildland fire fuels and designing AI-based workflows for large-scale forest inventory.

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Rose Yu, Ph.D.

Physics-Guided Machine Learning Expert

Dr. Rose Yu is an assistant professor with the Department of Computer Science and Engineering (CSE), UCSD. She was a postdoctoral fellow at the California Institute of Technology (Caltech). Her research focuses on advancing machine learning techniques for large-scale spatiotemporal data analysis, with applications in sustainability and health. A particular emphasis of her research is on physics-guided AI which aims to integrate first-principles with data-driven models.

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Ilya Zaslavsky, Ph.D.

Commons Framework Co-Lead

Dr. Ilya Zaslavsky is the Director of the Spatial Information Systems Lab at the San Diego Supercomputer Center, UCSD. His research focuses on distributed information management systems, spatial and temporal data integration, geographic information systems, spatial data science, and online visual data analysis. He has been leading design and technical development in several large cyberinfrastructure projects supported by NSF, NIH, and other federal agencies and private foundations.