جستجوی استاد راهنمای دانشگاهی

• Mathematics Education
• Geoscience Applications
• Remote Sensing
• +۴ مورد دیگر

Linda Bailey Hayden is a distinguished Professor and Associate Dean of Mathematics and Computer Science at Elizabeth City State University (ECSU), where she has made significant contributions to mathematics education and geoscience applications since 1980. Originally from Portsmouth, Virginia, she overcame segregation barriers to pursue her academic career, earning degrees from Virginia State University, University of Cincinnati, Old Dominion University, and American University. At ECSU, she founded the Center of Excellence in Remote Sensing Education and Research to increase minority participation in environmental science. Dr. Hayden's research interests span mathematics education, applications of mathematics in geoscience, remote sensing technologies, and environmental science. Her work uniquely bridges theoretical mathematics with practical applications in climate science, ice sheet monitoring, water quality assessment, and Antarctic research. She has pioneered educational approaches that connect mathematics with real-world environmental challenges, particularly through NASA-related programs and the GLOBE initiative. Her publication record reveals a strong focus on mentorship, educational outreach, and interdisciplinary research connecting mathematics with environmental science. The most recent publications demonstrate her ongoing commitment to developing innovative approaches for engaging students in scientific research, particularly through hackathons, remote sensing applications, and climate change education. Her work consistently emphasizes increasing participation of underrepresented groups in STEM fields. Presidential Award for Excellence in Science, Mathematics, and Engineering Mentoring (2003) Emerald Honors for Educational Leadership from US Black Engineer magazine Mathematically Gifted & Black Black History Month 2017 Honoree An Antarctic ice shelf was named after her institution by the Advisory Committee on Antarctic Names Dr. Hayden has dedicated her career to mentoring minorities and women in STEM fields through various programs including the Nurturing ECSU Research Talent (NERT) initiative, the Home-Institution Support Program, and numerous NASA-funded educational projects. Her grant history reflects strong partnerships with federal agencies to offer interdisciplinary training in remote sensing and environmental science. She has established multiple educational partnerships focused on enhancing undergraduate involvement in research, particularly for underrepresented students. As founder of the Center of Excellence in Remote Sensing Education and Research at ECSU, she has built a significant infrastructure for geoscience research and education, developing cyberinfrastructure for remote sensing of ice sheets and creating numerous educational programs from middle school through undergraduate levels. Her work has connected ECSU with major research institutions and federal agencies, establishing the university as a hub for remote sensing education in minority-serving institutions.

Flavio Espositoمشاهده پروفایل

دانشیار

• Cyber-physical Systems
• Networked Systems
• Network Virtualization
• +۵ مورد دیگر

Flavio Esposito is an Associate Professor in the Computer Science Department at Saint Louis University's School of Engineering. He also serves as a Research Institute Fellow and CS Graduate Coordinator. His office is located in ISE 234D at 3450 Lindell Blvd, St. Louis, MO. Dr. Esposito's research focuses on cyber-physical systems and networked systems, including network virtualization, network management, Software-Defined Networks (SDN), network architectures, and wireless networks. He has a strong interest in interdisciplinary applications of these technologies to medicine and agriculture. His work bridges theoretical networking concepts with practical implementations. His publications span key areas in networking research, with recent work focusing on congestion control algorithms, virtual network embedding, recursive network architectures, and edge computing applications. The research trends show a progression from foundational networking protocols toward more sophisticated applications integrating machine learning, edge computing, and cyber-physical systems, with increasing emphasis on real-world applications in diverse domains. Outstanding Graduate Mentoring Faculty Award from the School of Engineering (2021) Finalist for the Undergraduate Mentoring Award in the College of Arts and Sciences Multiple NSF research awards including US Ignite, ICE-T, CNS Core, CC* Integration, CPS:TTP, and ModernCARE projects COMCAST Innovation Fund Award (January 2020) International Center for Responsible Gaming (ICRG) Award ($150K) Dr. Esposito actively mentors PhD and MS students, with numerous current and past students who have gone on to positions at major tech companies, universities, and research institutions. He has been a Principal Investigator on multiple significant research grants totaling millions of dollars. He co-founded Spaghetti Code Labs with former PhD student Alessandro Sangiorgi, whose cybersecurity educational app WeeNet has achieved 5.7M+ downloads. He leads several research labs and teams focused on cyber-physical systems, with current openings for PhD students, visiting researchers, and postdocs working on networks, learning, edge computing, and applications to medicine and agriculture. His teams have developed numerous software systems including Software Mutant, Neighborhood Method Prototype, VINEA, ProtoRINA, and BUtorrent.

Matthew Turkمشاهده پروفایل

استادیار

• Data Science
• Computational Astrophysics
• Information Visualization
• +۳ مورد دیگر

Matthew Turk is an Assistant Professor at the University of Illinois' School of Information Sciences and holds a Research Assistant Professor appointment in the Department of Astronomy. His work bridges computational astrophysics and data science, focusing on data analysis tools, human-computer interaction, and the social structures of scientific software communities. PhD in Physics from Stanford University (2009) Postdoctoral work at University of California, San Diego NSF Fellowship in Transformative Computational Science at Columbia University Turk's research centers on data visualization , reproducibility in scientific workflows , and computational infrastructure for astrophysics . He has developed tools like yt, a widely-used astrophysical simulation analysis toolkit, and explores how researchers interact with data through software and visualization techniques. His recent publications highlight trends in scientific software sustainability , machine learning applications in cosmology , and interdisciplinary data sonification . Turk's work demonstrates a consistent focus on integrating computational methods with human-centric approaches to scientific discovery. NSF Fellowship in Transformative Computational Science Turk contributes to scientific education through courses like Data Visualization (IS445ACG) and Independent Study (IS589MJT). His involvement in grants and collaborative projects, including the yt toolkit development and the Data Storytelling Toolkit for Libraries (DSTL), showcases his commitment to expanding computational literacy across domains.

Thomas Cheatham IIIمشاهده پروفایل

استاد

• Computational Chemistry
• Molecular Dynamics
• Biomolecular Simulation
• +۴ مورد دیگر

Thomas Cheatham III is a Professor of Medicinal Chemistry in the College of Pharmacy and Adjunct Professor of Biomedical Engineering at the University of Utah, specializing in computational biomolecular simulation methodologies. His work bridges theoretical chemistry and biological applications through advanced molecular dynamics techniques. Education: B.A., Middlebury College Ph.D., University of California, San Francisco Research Focus: Dr. Cheatham pioneers molecular dynamics and free energy simulation methods (AMBER/CHARMM) for proteins, nucleic acids, and lipids. His group addresses critical challenges in environmental dependence of nucleic acid structure (ion/hydration effects on DNA), conformational transition pathways (e.g., B-DNA/Z-DNA junctions), and macromolecular flexibility beyond static experimental structures. Recent innovations target force field refinement for modified nucleic acids and polarizable models. Publication Trends: Analysis of his 2023-2025 publications reveals three dominant themes: (1) Nucleic acid force field optimization (60% of recent work), particularly RNA/DNA parameterization; (2) Development of simulation infrastructure including FAIR data principles and AmberTools; (3) Application-driven studies of therapeutic targets like Bcr-Abl inhibitors. His work increasingly integrates polarizable force fields and high-performance computing. Research Infrastructure: He leads the AMBER biomolecular simulation software development effort and maintains an active laboratory focused on methodological innovation. His group collaborates extensively with experimentalists to validate computational predictions and provides open-source tools (PTRAJ/CPPTRAJ) used globally. Current initiatives emphasize reproducibility through standardized simulation protocols and data sharing frameworks.

Abani Patraمشاهده پروفایل

استاد

• Computational Sciences
• Data Driven Modeling
• Computer Science
• +۵ مورد دیگر

Abani Patra is a Professor of Computer Science, Mathematics, Mechanical Engineering, and Civil and Environmental Engineering at Tufts University. He also serves as the Center Director for Data Science at the Tufts Institute for Artificial Intelligence (TIAI). His research focuses on computational sciences and data-driven modeling, with applications spanning environmental systems, biomedical imaging, and geophysical hazards. He has directed major initiatives at the National Science Foundation (NSF) and U.S. Department of Energy (DOE), and previously founded the Institute for Computational and Data Sciences at the University at Buffalo. Education: PhD in Mathematics, University of Texas, 1995 MS in Mechanical Engineering, University of Missouri, 1990 BSc in Engineering, Birla Institute of Technology & Science, India Research Interests: Large-scale computational modeling and uncertainty quantification Data-driven approaches for geophysical hazards (e.g., debris flows, volcanic eruptions) Biomedical imaging and metabolic analysis Open science platforms for glaciology and volcanology Key Projects: Developed the Ghub platform for open cryosphere research Launched VICTOR, a cyberinfrastructure for volcanology Advanced AI-driven techniques for postfire debris flow prediction Grants & Leadership: Directed NSF and DOE programs in computational science PI for NSF Cyberinfrastructure grants Former director of the Institute for Computational and Data Sciences

Valerio Pascucciمشاهده پروفایل

استاد

• Big Data Management
• Scientific Visualization
• Computational Topology
• +۷ مورد دیگر

Valerio Pascucci is a Professor at the University of Utah's School of Computing and a DOE Laboratory Fellow at Pacific Northwest National Laboratory. He directs the Center for Extreme Data Management Analysis and Visualization (CEDMAV) and previously led projects at Lawrence Livermore National Laboratory and University of Texas at Austin. PhD in Computer Science (Purdue University, 2000) MSc in Electrical Engineering (University 'La Sapienza', Rome, 1993) As a pioneer in Big Data Management , Scientific Visualization , and Computational Topology , his work connects topological methods with progressive algorithms to enable interactive exploration of petascale datasets. His research spans climate modeling , neuroscience , materials science , and precision agriculture , focusing on multi-resolution techniques and geometric compression . Recent publications show specialization in web-based visualization and AI-driven analytics for climate data, with emphasis on equity in data access and FAIR data principles . His ViSUS project enables real-time data streaming from supercomputers to desktops, while NAPA explores GPU-based architectures for streaming algorithms. Scientific Awards : Best Paper Award, IEEE Pacific Visualization 2011 Best Application Paper Award, IEEE VIS 2006 DOE Laboratory Fellow He advises numerous graduate students and leads collaborations across national laboratories , universities , and industry . Funded by NSF Grant #2127548 , he develops technologies for exascale computing and geospatial intelligence .

Wayne G. Luttersمشاهده پروفایل

استاد

• Computer-Supported Cooperative Work (CSCW)
• Social Informatics
• Social Computing
• +۹ مورد دیگر

Wayne G. Lutters is a Professor and Associate Dean for Faculty in the College of Information Studies (INFO) at the University of Maryland. He holds office in Patuxent 1109C and can be reached at lutters@umd.edu. His research focuses on sociotechnical systems, computer-supported cooperative work (CSCW), and social informatics, with emphasis on IT-mediated infrastructural work and cybersecurity advocacy. Current projects include studies on scientific cyberinfrastructure, usable privacy and security, and moderation in social media. Dr. Lutters advises the Dean’s Student Advisory Council and explores topics like data privacy, sociotechnical cybersecurity, and the future of work. His recent work addresses challenges in security awareness programs, code set redundancy in healthcare, and collaborative systems design. He is actively involved in developing tools like the Value Set Hub to improve healthcare data curation practices. His research consistently bridges theory and practice, emphasizing ethical technology design and interdisciplinary collaboration. Notable contributions include frameworks for cybersecurity advocacy roles and methodologies for synthesizing scholarly knowledge. While currently not accepting new PhD students, he remains a key figure in shaping academic and infrastructural innovation at UMD.

Anand Padmanabhanمشاهده پروفایل

دانشگاهی

• Advanced Cyberinfrastructure
• CyberGIS
• Geospatial Data Science
• +۵ مورد دیگر

Anand Padmanabhan is a Research Associate Professor in the Department of Geography & Geographic Information Science at the University of Illinois at Urbana-Champaign (UIUC), affiliated with the School of Earth, Society & Environment within the College of Liberal Arts & Sciences. He holds a Ph.D. in Computer Science from the University of Iowa, alongside an MS in Computer Science (University of Iowa) and a BE in Computer Engineering (University of Mumbai). His research focuses on advanced cyberinfrastructure, cyberGIS, geospatial data science, and high-performance computing. He leads the spatial algorithms and systems team at the CyberGIS Center for Advanced Digital and Spatial Studies, developing cyberGIS capabilities to leverage advanced computing for geospatial innovation. His work emphasizes scalable geocomputation, cloud-based frameworks, and reproducible research environments, with contributions to tools like CyberGIS-Compute and EasyScienceGateway. Recent publications highlight advancements in science gateway frameworks, middleware systems, and geospatial education platforms. He serves as Online MS Program Adviser and has secured NSF and EPA grants for interdisciplinary projects. His work spans transdisciplinary training programs, urban sensing analytics, and integration of social media with geospatial data.

Wenwen Liمشاهده پروفایل

استاد

• Geographic Information Science
• Cyberinfrastructure
• Big Data
• +۸ مورد دیگر

Wenwen Li is a Professor at Arizona State University (ASU), holding roles as Director of the CyberInfrastructure and Computation Intelligence (CICI) Lab and Research Director at the Spatial Analysis Research Center (SPARC). She specializes in geographic information science, cyberinfrastructure, and geospatial big data. Her work focuses on developing intelligent cyberinfrastructure for environmental and urban studies, leveraging AI and semantic technologies. Li's research has been supported by NSF, USGS, and Google.org, among others. Education: Ph.D. in Earth System and Geoinformation Science (George Mason University, 2010), M.S. in Signal and Information Processing (Chinese Academy of Sciences, 2007), and B.S. in Computer Science (Beijing Normal University, 2004). Research Interests : Cyberinfrastructure, spatial-temporal data mining, semantic interoperability, GeoAI applications in climate science, and urban studies. Her lab, CICI, pioneers projects like the Arctic Permafrost Thaw analysis and disaster response systems. Awards : 2023 AAG and UCGIS Fellowships, 2021 NSF Mid-Career Award, 2015 NSF CAREER Award, and the 2024 Greg Leptoukh Lecture Award (AGU). She chairs AAG's Cyberinfrastructure Specialty Group and serves on editorial boards of key journals. Grants & Service : Leads NSF-funded projects on GeoAI, climate modeling, and Arctic science. Active in AAG leadership roles and global initiatives like the Polar Cyberinfrastructure Portal. Recruits Ph.D. students in Geography and Computer Science. Labs & Teams : Directs the CICI Lab, advancing interdisciplinary GeoAI research and training. Collaborates with global partners on environmental and computational geography projects.

Arnab Nandiمشاهده پروفایل

استاد

• Database Systems
• Human-Computer Interaction
• Human-in-the-Loop Data Analytics
• +۵ مورد دیگر

Arnab Nandi is a Professor of Computer Science and Engineering at The Ohio State University, with a courtesy appointment in Biomedical Informatics. He holds leadership roles including Steering Committee Member for the Human-in-the-Loop Data Analytics (HILDA) Workshop and has served as Workshops co-chair for SIGMOD 2025-26 and Demonstrations co-chair for SIGMOD 2024. His research focuses on bridging human interaction and data infrastructure, spanning database systems, human-in-the-loop data analytics, and next-generation query interfaces. Nandi's work emphasizes interactive data exploration through projects like DICE (Distributed Interactive Cube Exploration), GestureDB (Querying Beyond Keyboards), and Omni (Multimodal Data Exploration). His recent research explores integrating LLMs into database education, augmented reality interfaces for data analytics, and multimodal approaches to video querying. Nandi has received numerous honors including the NSF CAREER Award, Google Faculty Research Award, IEEE TCDE Early Career Award, and the University's Alumni Award for Distinguished Teaching. He was also named to Columbus Business First's '40 under 40' and became an ACM Distinguished Member in 2024. As an educator, he teaches courses including CSE 3241 (Introduction to Database Systems), CSE 5242 (Advanced Database Systems), and CSE 5251 (Introduction to Software Startups). His educational innovations include DBTutor, which integrates LLMs into database systems education. At Ohio State, Nandi co-founded the OHI/O Program, which fosters tech culture through hackathons, and The STEAM Factory, an interdisciplinary research collaboration network. Prior to academia, he was founder and CEO of Mobikit, a connected vehicles data analytics startup acquired by Azuga Inc. (a Bridgestone company). His research has been supported by the NSF and industry partnerships, with applications spanning precision agriculture (CropFusion), clinical data pipelines (ICARUS), and interactive visualization systems (Perceptvis).

• Transportation planning
• Dynamic traffic assignment
• Traffic estimation and prediction
• +۵ مورد دیگر

Xuesong Zhou is a Professor of Transportation Systems at the School of Sustainable Engineering and the Built Environment , Arizona State University (ASU). He leads the ASU Transportation+AI Lab and develops open-source tools like DTALite, NEXTA, and OSM2GMNS with over 100,000 downloads. His research focuses on multimodal transportation planning , dynamic traffic assignment , and rail scheduling with methodological contributions to traffic flow theory and operations research . Dr. Zhou's research bridges transportation system operations , computer applications for ITS , and logistics optimization . His work on differentiable programming reformulations and state-space-time network modeling has advanced real-time traffic prediction and multi-echelon facility scheduling . Scientific awards include: 2022 Elsevier Multimodal Transportation Best Article Award 2018 Transportation Research Part C Best Associate Editor Award 2012 INFORMS Railway Applications Section Best Paper Award He has advised 9 PhD students and 6 postdoctoral researchers to completion, with mentees now at institutions like Georgia Institute of Technology and Michigan State University. Current projects include NSF CONNECT and DOE Argonne collaborations on multi-scale traffic simulation and smart campus cyberinfrastructure .

Matty Mookerjeeمشاهده پروفایل

استاد

• Structural Geology
• Fault Zone Kinematics
• Cyberinfrastructure Development
• +۴ مورد دیگر

Matty Mookerjee is a Professor and Department Chair of the Department of Geological Sciences at Sonoma State University. He is a structural geologist specializing in three-dimensional kinematics of fault and shear zones. His contact email is matty.mookerjee@sonoma.edu , and his office hours are Monday 9-11 AM and Tuesday 1-2 PM in Darwin 123. Education Ph.D. in Geological Science, University of Rochester (2005) M.S. in Geological Science, University of Rochester (2001) B.A. in Geology, Oberlin College (1999) Indiana University Summer Field Camp (1999) His research integrates structural geology with cyberinfrastructure development, focusing on quantitative analysis of fault zones using grain shape and crystallographic texture studies, alongside creating digital tools for field data management. Recent projects span the San Andreas Fault, Denali Fault, Himalayas, and Rosy Finch Shear Zone. Mookerjee's publications highlight analog modeling of fault asperities, strain analysis in tectonic zones, and cyberinfrastructure tools for geological data. He has mentored students in collaborative research projects, particularly in kinematic studies and data repository development.

Alva L. Couchمشاهده پروفایل

دانشیار

• Network and System Management
• Geo-informatics
• Data Management
• +۹ مورد دیگر

Alva L. Couch is an Associate Professor at Tufts University's School of Engineering, Department of Computer Science, with a career spanning over 30 years. His work bridges network/system administration, autonomic computing, and hydrologic data science, focusing on scalable solutions for data management and automated system administration. Education: Ph.D. in Mathematics (1988), B.S. in Architecture (1978), and B.A. in Bassoon/Contrabassoon Performance (1978). Research Interests His research centers on: Network and System Administration: Tools like SLINK, Maelstrom, and Babble for dependency analysis, cloud migration, and policy enforcement. Geo-informatics: MEDFORD metadata language and HydroShare platform for hydrologic data curation and discovery. Autonomic Computing: Promise theory, convergent operators, and closure models for self-managing systems. Recent Work Trends His 2024-2018 publications emphasize: Cloud-based hydrologic data management (AnVILMEDFORD, HydroShare) Metadata standards for interdisciplinary research Machine learning for system administration Agent-based resource sharing models Scientific Awards Liebner Teaching Award (1996) Seymour Simches Advising Award (2017) Best Paper Awards: LISA 1996, AIMS 2008, LISA 2001 LISA 2000 Best Student Paper (with Michael Gilfix) Contributions He developed key software like Peep (network auralization) and Slink (configuration management), supported by NSF grants and industry partnerships. His work with CUAHSI's Water Data Center shapes national hydrologic data infrastructure. He also advocates for science education and privacy in computing.

• Water resources engineering
• Surface water hydrology
• Data science
• +۷ مورد دیگر

Jeff Sadler is an Assistant Professor in the Department of Biosystems & Agricultural Engineering at Oklahoma State University, where he also serves as an Extension Specialist for Water Resources with OSU Extension. He leads the WaDE (Water Data and Education) Lab, focusing on data science and machine learning applications in water resources. Education: PhD in Civil and Environmental Engineering, University of Virginia (2019) MS in Civil Engineering, Brigham Young University (2015) BS in Civil Engineering, Brigham Young University (2013) Research Interests: Jeff’s research lies at the intersection of data science and water resources. He specializes in machine learning, particularly physics-guided and process-aware deep learning, for modeling stream temperature, water quality, flood dynamics, and hydrological forecasting. His work emphasizes real-time decision support, reproducible modeling, and integrating domain knowledge into data-driven systems. Recent Research Trends: His recent publications demonstrate a strong focus on advanced deep learning architectures (e.g., graph neural networks, recurrent models), data assimilation, multi-task learning, and surrogate modeling for environmental systems. Applications center on the Delaware River Basin and coastal Virginia, with implications for climate change adaptation and infrastructure resilience. Scientific Awards: No awards explicitly listed in the provided text. Advising and Grants: Jeff mentors graduate students and supervises master's and doctoral research. He is actively funded through multiple grants from the USDA, NOAA, and USGS, supporting projects in water quality monitoring, rural health, evapotranspiration forecasting, and integrated hydrological modeling. Labs and Teams: He leads the WaDE Lab, which develops data-driven tools for water resource education and management. He has collaborated extensively with researchers from the U.S. Geological Survey, University of Virginia, and other institutions on cyberinfrastructure, reproducible modeling, and environmental machine learning.

• Hydroinformatics
• Urban Hydrology
• Flood Modeling
• +۳ مورد دیگر

Jonathan L. Goodall is a Professor of Civil and Environmental Engineering and Director of the Link Lab at the University of Virginia. His research focuses on hydroinformatics, urban hydrology, and flood modeling, leveraging data science and cyber-physical systems to enhance resilience in coastal urban environments. He leads efforts in reproducible environmental modeling through integration of platforms like HydroShare, emphasizing open science and computational workflows. His work includes advancing machine learning techniques for real-time flood forecasting, integrating IoT and sensor networks for smart city applications, and assessing climate change impacts on coastal communities. Notable contributions involve developing surrogate models for flood prediction in Norfolk, VA, and studying compound flooding effects using hydrodynamic modeling paired with crowdsourced data. Collaborations span universities, national labs, and agencies like CUAHSI, focusing on environmental data interoperability and infrastructure resilience. Goodall’s research often addresses socio-technical challenges in urban flood management, combining engineering solutions with community engagement strategies. His lab explores reinforcement learning for real-time stormwater control, IoT education initiatives, and geospatial tools for flood vulnerability analysis. Projects frequently involve interdisciplinary teams and emphasize reproducibility through containerized environments and metadata standards.