جست‌وجوی استاد و پژوهشگر

Xian Suمشاهده پروفایل

استادیار مهمان

• Distributed Machine Learning
• Coding Techniques for Straggler Tolerance
• Distributed Systems Optimization
• +۳ مورد دیگر

Xian Su is a Visiting Assistant Professor at the Knight Foundation School of Computing and Information Sciences, Florida International University. He holds a Ph.D. (2024) and M.Phil (2022) in Computer Science from the City University of New York, and a B.Sc. (2016) from Ocean University of China. His research focuses on distributed machine learning, particularly leveraging coding techniques to address straggler challenges in distributed systems. Education: Ph.D. in Computer Science, City University of New York (2024) M.Phil in Computer Science, City University of New York (2022) B.Sc. in Information Science and Engineering, Ocean University of China (2016) Research Interests: Distributed machine learning systems, straggler mitigation via coding theory, theoretical foundations of coded computing, and practical implementations of fault-tolerant algorithms. His work bridges theoretical advancements with real-world applications in distributed computing environments. Publications: Recent work emphasizes accelerating distributed machine learning through coded techniques, with contributions in coded matrix multiplication, gradient coding, and dynamic resource allocation strategies. Themes include improving computational efficiency and resilience in large-scale distributed systems.

Anima Boseمشاهده پروفایل

دانشیار

• Renewable Energy
• Fuel Cell Technology
• Energy Storage Materials
• +۳ مورد دیگر

Anima Bose is an Associate Professor in the Department of Mechanical Engineering Technology at the University of Houston’s Cullen College of Engineering. She leads the Sustainable Energy Conversion and Storage Lab, focusing on renewable energy technologies, particularly fuel cell innovation and energy storage materials. Her research addresses challenges in catalyst cost reduction, water management in fuel cells, and oxidation-resistant materials. She holds a Ph.D. in Analytical Chemistry (Materials Engineering) from Kent State University, along with multiple M.S. degrees in Solid State Physics and a B.Sc. (Honors) in Chemistry. Her professional experience includes roles as Associate Professor at the University of Houston (2011–present), Research Assistant Professor at Ohio University (2008–2011), and Associate Director of Fuel Cell Initiatives at Northern Illinois University (2003–2008). She has collaborated with institutions like Argonne National Laboratory and the Liquid Crystal Institute. Bose is affiliated with the Electrochemical Society and American Chemical Society. Research interests span proton exchange membrane fuel cells, energy storage systems, and superconducting materials. Her lab has pioneered advancements in nano-catalysts, hydrophobic membrane engineering, and hybrid vehicle power distribution. Key innovations include boron-carbon meso-spheres for enhanced conductivity and siloxane polymer-based MEAs to mitigate water flooding. Lab Director: Sustainable Energy Conversion and Storage Lab Membership: Texas Center for Superconductivity, Advanced Materials Center Publications: Over 50 articles in journals like Journal of Power Sources and Journal of the American Chemical Society

Todd Pittmanمشاهده پروفایل

استاد

• Quantum Information
• Quantum Optics
• Nonlinear Optics
• +۳ مورد دیگر

Todd Pittman is a Professor in the Department of Physics at the University of Maryland, Baltimore County (UMBC), affiliated with the College of Natural and Mathematical Sciences. Previously, he served as an experimental physicist at the Johns Hopkins University Applied Physics Laboratory. His research focuses on quantum information, quantum optics, and ultralow-power nonlinear optics, with emphasis on quantum computing using photonic qubits, entanglement generation, and novel nonlinear optical techniques. Education: Ph.D. Physics, UMBC (1996) M.S. Physics, UMBC (1992) B.S. Physics, Bucknell University (1990) Research Interests: Quantum computing with single-photon qubits (e.g., Linear Optics Quantum Computing) Quantum entanglement (parametric down-conversion, entangled photon holes) Ultralow-power nonlinear optics using tapered optical nanofibers and noble gas systems Recent work includes advancements in quantum memory systems, noiseless attenuation of quantum states, and experimental demonstrations of zero-photon subtraction techniques. Awards: No specific awards are explicitly mentioned in the provided texts. Advising & Grants: No advisees or grant details are listed, though his research likely involves significant funding given the experimental focus. Labs & Teams: Leads the Quantum Information Group laboratory at UMBC, specializing in experimental quantum optics and photonic systems.

Kevin Tomsovicمشاهده پروفایل

استاد

• Power Systems Engineering
• Renewable Energy Integration
• Smart Grid Technologies
• +۶ مورد دیگر

Kevin Tomsovic is the Chancellor's Professor in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville, and Director of the CURENT Engineering Research Center. His expertise spans smart grids, power systems optimization, and cyber-physical resilience. He holds a PhD from the University of Washington (1987) and prior roles at Washington State University. Research focuses on renewable integration, microgrid scheduling, and grid security, with notable contributions to IEEE standards. Awards include IEEE Fellow status. Education: PhD/M.S. Electrical Engineering, University of Washington (1987/1984); B.S. Electrical Engineering, Michigan Tech (1982). Research interests include: - Intelligent systems for power distribution design - Electricity market analysis and stability control - Cybersecurity for grid infrastructure - Resilience quantification in energy systems Publications highlight advancements in grid emulation platforms, adversarial ML defenses, and microgrid optimization. His work is supported by NSF/DOE grants (e.g., NSF EEC-1041877). CURENT testbed facilities enable real-time grid control validation. Awards: IEEE Fellow (20XX). Grants & Collaborations: Lead CURENT NSF ERC; industry partnerships include power utilities and tech firms. Active in developing standards for grid resilience metrics. Labs/Teams: CURENT Engineering Research Center, UT Power Systems Lab.

Michael A. Benderمشاهده پروفایل

استاد

• Algorithms
• Data Structures
• Cache and I/O-Efficient Computing
• +۷ مورد دیگر

Michael A. Bender is the John L. Hennessy Chaired Professor of Computer Science at Stony Brook University. His work spans both theoretical and applied domains in algorithms, data structures, and storage systems. He co-founded Tokutek, Inc., a database company acquired by Percona in 2015, and has held visiting positions at MIT and King's College London. Education: PhD in Computer Science from Harvard University (1998), DEA and Magistère in Computer Science from École Normale Supérieure de Lyon (1993), BA in Applied Mathematics from Harvard (1992). His research focuses on cache-oblivious algorithms , I/O-efficient computing , parallel systems , and scheduling . His work addresses scalability in large-scale data management and computational geometry, with applications in bioinformatics and robotics. The 15 most recent publications highlight advancements in list labeling , hash table design , graph algorithms , and memory optimization . These papers reflect his commitment to solving practical problems with rigorous algorithmic approaches. Awards include: PODS Best Paper Award (2024) ASPLOS Distinguished Paper Award (2023) USENIX FAST Best Paper Award (2016) Chancellor's Award for Excellence in Teaching (2015) R&D 100 Award (2006) He has led the Stony Brook Computer Science Honors Program and advised graduate students in algorithmic research. His grants portfolio includes 39 funded projects, emphasizing algorithm engineering and systems optimization.

Ralph Detersمشاهده پروفایل

استاد

• Multi-Agent Systems
• Scalability & Dependability of Distributed Systems
• Mobile & Ubiquitous Computing
• +۴ مورد دیگر

Ralph Deters is a Professor in the Department of Computer Science at the University of Saskatchewan , where he co-leads the MADMUC (Multi-Agent Distributed Mobile and Ubiquitous Computing) Lab . He has taught courses including CMPT 298, CMPT 350, CMPT 436, CMPT 842, and CMPT 898, and served as co-coordinator for CMPT 400/CMPT 405. Education Ph.D. in Computer Science, Federal Armed Forces University Munich (1998) MS (Diploma) in Computer Science, Technical University Berlin (1992) BS in Computer Science, Technical University Berlin (1988) Research Interests focus on multi-agent systems , scalable distributed systems , mobile/ubiquitous computing , and privacy-preserving technologies . Current lab projects include: Middleware infrastructures for decentralized systems (cloud/fog/mobile) Social software for sustainable user collaboration Decentralized trust-based data storage Persuasive technologies for health, physical activity, and learning Ethical AI and dark patterns in UI design Blockchain applications in IoT and access control Publications highlight trends in digital twins , blockchain integration , synthetic data for privacy , and machine learning for social impact , with recent work spanning health analytics, agricultural AI, and smart city applications. Lab Impact : The MADMUC Lab, established in 2000 with a $895,687 CFI grant, has graduated 120 researchers (17 PhD, 103 MSc), including two Vanier Scholars. The lab emphasizes awards, scholarships, and interdisciplinary collaboration with 152 total alumni.

Björn Schemberaمشاهده پروفایل

پژوهشگر

• Research Data Management
• Metadata
• Semantics
• +۴ مورد دیگر

Björn Schembera is a Researcher at the Institute of Applied Analysis and Numerical Simulation (IANS) at the University of Stuttgart, focusing on Research Data Management (RDM), metadata standards, and ontologies. He holds a Dr.-Ing. (Engineering Doctorate) and a Diplom-Informatik (Computer Science) degree, with interdisciplinary training in philosophy. His current work centers on FAIR principles, knowledge graphs, and dark data in computational and mathematical sciences, particularly within the MaRDI (Mathematical Research Data Initiative) project under NFDI funding. Education and Professional Background: After completing his doctoral studies on dark data in simulations at HLRS (2011–2022), he joined IANS in 2022. His research bridges technical RDM challenges with societal implications of information technology. Research Interests: Schembera’s work emphasizes metadata models (e.g., EngMeta), ontology development for mathematics and engineering, and ethical aspects of data stewardship. He contributes to projects like bwDataArchive and NFDI4Cat, addressing interoperability and standardization in research data infrastructures. Teaching: He leads the course 'Schlüsselqualifikation Forschungsdatenmanagement' since 2023/24, promoting open science and RDM practices. Key Achievements: His 2023 Best Paper Award (MTSR Conference) recognizes contributions to metadata and semantic research. Over 50 publications span journals like Energies, IEEE Transactions, and conference proceedings on metadata, ontologies, and simulation workflows. Projects: He collaborates on MaRDI (mathematical data infrastructure), NFDI4Cat (catalysis sciences), and bwDataArchive (long-term storage).

Steven C. DeCaluweمشاهده پروفایل

دانشیار

• Clean Energy Systems
• Electrochemistry
• Interfacial Processes
• +۵ مورد دیگر

Steven C. DeCaluwe is an Associate Professor in the Department of Mechanical Engineering at Colorado School of Mines, where he combines experimental and computational approaches to study clean energy systems. His research focuses on electrochemistry and interfacial processes in batteries (Li-ion, Li-O 2 , Li-sulfur) and fuel cells. He also serves as Director of Graduate Studies and chairs the university's Diversity, Inclusion, and Access Committee. PhD in Mechanical Engineering (University of Maryland, 2009) NRC Postdoctoral Fellowship at NIST (2009-2012) BS in Elementary Education and Mathematics (Vanderbilt University, 2000) DeCaluwe's work bridges advanced diagnostics (neutron scattering, operando XPS) with multiscale simulations to improve energy storage technologies. His research spans solid-electrolyte interphase formation , electrochemical degradation mechanisms , and materials optimization for sustainable energy . He advocates for open science practices and integrates conservation biology principles into engineering design. His recent publications demonstrate expertise in battery modeling, phase segregation in electrodes, and sustainability-driven materials selection. Key themes include parameter uncertainty quantification , interface stability , and multi-modal characterization of energy storage systems. NRC Postdoctoral Fellowship Associate Editor, ASME Journal of Electrochemical Energy Conversion and Storage Chair, Mechanical Engineering Diversity Committee Director, Rocky Mountain Environmental XPS Facility DeCaluwe actively mentors students through the CORES Research Group , emphasizing inclusive learning environments and growth mindsets. His service extends to organizing neutron scattering conferences and managing shared instrumentation facilities.

• Artificial Intelligence
• Geospatial Data Science
• Knowledge Graphs
• +۵ مورد دیگر

Professor Manolis Koubarakis is a faculty member at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. His research focuses on geospatial data science, knowledge graphs, entity resolution, and AI applications in Earth observation. He leads projects like ExtremeEarth and Plato, advancing semantic data cube systems and geospatial question answering engines. His work bridges AI and geospatial technologies, with contributions to frameworks like pyJedAI and Strabo 2 for managing big geospatial data. Research Interests include: Geospatial Question Answering Systems Entity Resolution and Entity Linking Ontology-Based Data Access (OBDA) Knowledge Graph Construction and Applications Earth Observation Data Analytics AI for Geoinformatics Notable Projects: ExtremeEarth: Combines Copernicus satellite data with machine learning for environmental analytics. Plato: Semantic data cube system enabling advanced querying of multidimensional datasets. GeoQA2: A geospatial question answering engine evaluated on large benchmarks. JedAI Family: Tools for scalable entity resolution in structured/semi-structured data. His publications span 20+ years, with recent emphasis on: AI-driven Earth observation systems Geospatial RDF benchmarking 3D geospatial interlinking Large language models for legal and health content delivery

Claudia Rawnمشاهده پروفایل

استاد پژوهشی

• Neutron and X-ray diffraction
• Ceramic synthesis
• Structure-property relations
• +۶ مورد دیگر

Claudia Rawn is a Research Professor and Joint Faculty Member in the Department of Materials Science and Engineering at the University of Tennessee, Knoxville (UTK), affiliated with the Tickle College of Engineering. She is also a Senior Research Staff Member at Oak Ridge National Laboratory (ORNL). Her research focuses on neutron and X-ray diffraction techniques, ceramic synthesis, crystal structure analysis, and thermophysical properties of materials, with notable contributions to gas hydrates, biomaterials, and phase transition studies. Education: PhD in Materials Science and Engineering, University of Arizona (1995) MSc in Chemistry, George Mason University (1991) BSc in Materials Engineering, Virginia Tech (1986) Research Interests: Dr. Rawn’s work integrates experimental and computational methods to explore material behavior. Key areas include: Neutron/X-ray diffraction for in-situ structural analysis Phase transitions in ceramics and metallic alloys Biomimetic synthesis of nanomaterials (e.g., hydroxyapatite composites) Gas hydrate formation/decomposition mechanisms Thermal expansion and microstructural evolution in additively manufactured materials Awards: 2019, 2013, 2012 MSE Excellence in Service Award 2017 TCE Outstanding Faculty Advisor 2006 UTK Outstanding Young Researcher (Materials Science) ASM International Fellow Advising & Grants: Advises graduate students in materials science and collaborates on projects funded by DOE, NASA, and NSF. Leads educational outreach through the UT Materials Advantage Chapter and co-organizes ASM’s annual Materials Camp for K-12 students. Labs & Collaborations: Active in ORNL’s Materials Science and Technology Division, focusing on neutron scattering and advanced characterization. Serves on editorial boards for crystallography journals and professional committees.

Pavan Poudelمشاهده پروفایل

استادیار

• Parallel and Distributing Computing Algorithms
• Robotics
• Internet of Things
• +۳ مورد دیگر

Dr. Pavan Poudel is an Assistant Professor of Computer Science at the University of Houston-Clear Lake (UHCL), part of the College of Science and Engineering. He joined UHCL in Fall 2024 after working as a Research Engineer in the software industry and completing a postdoctoral research position at Augusta University's Department of Computer and Cyber Sciences. He holds a Ph.D. in Computer Science from Kent State University (2021) and a Bachelor's in Computer Engineering from Tribhuvan University, Nepal. His research focuses on Parallel and Distributed Computing, Robotics, and Fault-Tolerance, with expertise in optimizing scheduling algorithms and designing scalable systems for distributed environments. Dr. Poudel's research includes transactional memory systems, distributed robotics algorithms (e.g., gathering, scattering, and coverage), and fault-tolerant solutions for real-time applications like medical and disaster response. His work bridges theoretical computer science with practical applications, emphasizing efficiency and scalability. He has published extensively in venues like Theoretical Computer Science (TCS) and Information, addressing topics such as time-optimal robot navigation and adaptive versioning in transactional memory. His academic awards include the Best Presentation Award at Kent State’s Graduate Research Symposium (2021) and scholarships like the John Sechrist and Hine Scholarships (2019–2020). He teaches courses such as Computer Organization and Assembly Language and Computer Game Programming. His publications demonstrate a strong focus on distributed systems, robotics algorithms, and concurrency control, reflecting his commitment to advancing scalable and reliable computing solutions.

• Cyber Physical Systems
• Risk/Reliability Analysis
• Deep Learning
• +۳ مورد دیگر

Dr. Saptarshi Sengupta is an Assistant Professor in the Department of Computer Science at San José State University (SJSU), leading the Machine Intelligence and Complex Systems (MICoSys) Lab. He advises the ACM student club at SJSU and holds a 'Alien of Extraordinary Ability' visa (Einstein Visa) from USCIS. His work focuses on resilient cyber-physical systems, risk analysis, and deep learning applications in healthcare and industrial systems. Education: Ph.D. in Electrical Engineering, Vanderbilt University M.S. in Electrical Engineering, Vanderbilt University B.Tech. in Electronics & Communication Engineering, West Bengal University of Technology Research Interests: Cyber-Physical Systems Security Healthcare AI for Cancer and Chronic Disease Prediction Battery Prognostics and Energy Systems Machine Learning for Complex Systems Analysis Key Achievements: Dr. T.M.A. Pai Gold Medal Award for Healthcare AI contributions Recipient of multiple best paper awards at international conferences Author of over 30 peer-reviewed publications Labs & Teams: Leads the MICoSys Lab, developing AI solutions for healthcare diagnostics, industrial prognostics, and smart infrastructure systems. Collaborations include interdisciplinary projects with biomedical and engineering domains.

Eduardo Martinez-Cesenaمشاهده پروفایل

مدرس

• Power Systems Economics
• Renewable Energy Integration
• Smart Grid Technologies
• +۳ مورد دیگر

Dr. Eduardo Martinez-Cesena is a Lecturer in Multi-energy Systems at the University of Manchester's Department of Electrical and Electronic Engineering. His research focuses on power systems economics, renewable energy integration, and smart grid solutions. He has contributed to European projects including ATTEST and FutureDAMS, specializing in economic assessment of electricity systems. Research outputs analyze energy scheduling frameworks and demand response optimization, with recent work exploring education pathways for low-carbon technology adoption. Publications demonstrate consistent focus on improving energy system resilience through computational optimization methods. Professional recognition includes the 2015 Orange Data for Development Prize for energy solutions in Senegal. Current roles include doctoral program leadership and research impact coordination within the faculty.

Jovica Milanovicمشاهده پروفایل

استاد

• Power System Dynamics
• Power Quality
• Probabilistic Modeling
• +۴ مورد دیگر

Jovica Milanovic is a Professor in the School of Electrical and Electronic Engineering at the University of Manchester, where he leads the Electrical Energy and Power Systems research group. He holds a Dipl.Ing. and MSc in Electrical Engineering from the University of Belgrade, a PhD from the University of Newcastle, and a DSc from the University of Manchester. With over 600 publications, his research focuses on probabilistic modeling of power systems, renewable integration, and power quality. Research Expertise: Probabilistic assessment of uncertain power systems Machine learning applications for grid stability Demand side management in low-carbon networks Global power quality monitoring frameworks Awards & Leadership: FIEEE, FIET, and IEEE PES Distinguished Lecturer Editor-in-Chief of IEEE Transactions on Power Systems Chair of multiple international conferences including PowerTech 2017 Recipient of the Verriest Medal for contributions to power systems

Giovanni Sansaviniمشاهده پروفایل

دانشیار

• Renewable Energy Systems
• Energy Infrastructure Resilience
• Power Systems Optimization
• +۳ مورد دیگر

Prof. Giovanni Sansavini is an Associate Professor in the Department of Mechanical and Process Engineering at ETH Zürich. His research focuses on energy systems resilience, renewable energy integration, and sustainable infrastructure design. He leads projects related to grid optimization, energy policy, and risk engineering, with a particular emphasis on decarbonization strategies for Switzerland and Europe. His work bridges theoretical modeling and practical implementation, addressing challenges such as power transmission equity, distributed energy resource management, and hydrogen storage integration. Recent projects include developing data-driven frameworks for grid reliability assessment and analyzing the socio-technical impacts of energy transitions. Prof. Sansavini collaborates with industry and policymakers to ensure research informs actionable solutions. His publications highlight interdisciplinary approaches to energy system design, emphasizing the trilemma of affordability, sustainability, and security.