جست‌وجوی استاد و پژوهشگر

• Energy Conversion
• Nanotechnology
• Materials Science
• +۳ مورد دیگر

Friedrich Prinz is the Leonardo Professor in the School of Engineering at Stanford University, holding dual professorships in Mechanical Engineering and Materials Science and Engineering. He is also a Senior Fellow at the Precourt Institute for Energy and an affiliate of the Stanford Woods Institute for the Environment. Additionally, he directs the Nanoscale Prototyping Laboratory and co-directs the NPL-Affiliate Program. He earned a PhD in Physics from the University of Vienna (1975) and joined Stanford in 1994 after faculty roles at Carnegie Mellon University. His research focuses on nanoscale energy conversion and storage, employing advanced fabrication techniques like atomic layer deposition (ALD) to develop prototype fuel cells and capacitors. His lab investigates material structures using scanning tunneling microscopy, impedance spectroscopy, and atomic-scale modeling. Prinz has authored over 360 publications and advised numerous students. Notable awards include AAAS Fellowship (2007) and the AM Strickland Prize (2005). His work bridges solid-state physics, materials engineering, and renewable energy technologies. He teaches courses in manufacturing processes, quantum field theory applications, and advanced material science. Current roles include supervising doctoral and postdoctoral researchers in energy-related nanotechnologies.

John Wawrzynekمشاهده پروفایل

استاد

• Computer Architecture
• Reconfigurable Computing
• Wireless Systems
• +۳ مورد دیگر

John Wawrzynek is a Professor of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He is affiliated with the Department of Electrical Engineering and Computer Sciences in the College of Engineering and serves as Co-Director of the Berkeley Wireless Research Center and Co-PI of the CONIX Research Center, one of the six centers in the Joint University Microelectronics Program sponsored by DARPA. Dr. Wawrzynek received his B.S. in Electrical Engineering from SUNY, Buffalo (1977), M.S. in EE from the University of Illinois, Urbana/Champaign (1979), and Ph.D. in Computer Science from Caltech (1987). Before joining the Berkeley faculty in 1988, he worked as a consultant at Schlumberger Palo Alto Research. His research focuses on Computer Architecture, Reconfigurable Computing, Wireless Systems, and Integrated Circuit and System Design . His work spans both theoretical foundations and practical implementations, with particular emphasis on FPGA-based computing systems, reconfigurable architectures, and wireless communication systems. His research group has made significant contributions to the field of reconfigurable computing, including the development of the Garp architecture and various tools for reconfigurable computing systems. Analysis of his recent publications (2022-2025) reveals continued focus on reconfigurable computing, FPGA design, wireless networking, and formal methods for hardware verification. His work shows an evolution from traditional computer architecture towards specialized hardware acceleration, machine learning for EDA, and wireless systems research, with particular emphasis on SAT sampling, differentiable computing, and efficient FPGA implementation of neural networks. DAC's Most Influential Paper Award (2025) NSF Presidential Young Investigator (PYI) (1989) Charles Lee Powell Fellowship (1985) NASA Certificate of Recognition (1983) Rensselaer Engineering and Science Medal (1975) Professor Wawrzynek has advised numerous graduate students throughout his career, many of whom have gone on to prominent positions in both industry and academia including Google, Xilinx, and MIT Lincoln Laboratory. His research has been supported by various grants from NSF, DARPA, and industry partners. He leads the Berkeley Wireless Research Center, which focuses on next-generation wireless communication systems and technologies, and is actively involved in the CONIX Research Center which explores connected intelligence at the network's edge.

Sanjeev Baskiyarمشاهده پروفایل

استاد

• Scheduling and Cloud Computing
• Computer Architecture
• Real-time and Embedded Computing
• +۱۱ مورد دیگر

Sanjeev Baskiyar is a Professor in the Department of Computer Science and Software Engineering at Auburn University's College of Engineering. He has been actively involved in research, teaching, and academic leadership, with a strong focus on computer systems, real-time and embedded computing, scheduling, cloud and fog computing, and energy-aware architectures. Education: Ph.D., Electrical and Computer Engineering, University of Minnesota M.S., Electrical and Computer Engineering, University of Minnesota B.S., Electronics and Communications, Indian Institute of Science, Bangalore B.S., Physics (with honors), and distinction in Mathematics Dr. Baskiyar’s research interests span scheduling, real-time and embedded systems, computer architecture, fog/cloud computing, thermal/energy-aware computing, and STEM education. His recent work explores machine learning applications in scheduling and quantum computing for fake news detection. He has supervised over 25 graduate students, many of whom now hold academic and industry positions. His recent publications emphasize fog computing simulation, service placement, quantum-inspired fake news detection, and adaptive scheduling using machine learning. These works reflect a trend towards intelligent, scalable, and energy-efficient computing systems, particularly in distributed and edge environments. Scientific Awards and Honors: Walker Teaching Excellence Award, Auburn University, 2020 Summer Faculty Fellow, Air Force Research Labs, 2020 Nominated Best Teaching Assistant, University of Minnesota, 1992 Multiples Merit and State-merit Scholarships Honors in Physics and Distinction in Mathematics Dr. Baskiyar has successfully advised numerous MS and PhD students and secured over $2 million in research funding as Principal Investigator from the National Science Foundation, DARPA, NASA, and industry partners like Wind River Systems and Mentor Graphics. His grants focus on parallel computing education, real-time micro-architectures, and embedded systems. He has also served on editorial boards, program committees, and as a reviewer for NSF and IEEE journals. He has held leadership roles including Senator in the University Faculty Senate and Chair of the E-day Committee. Labs and Research Groups: While not explicitly named, Dr. Baskiyar leads a research group focused on computer systems, scheduling, and embedded computing, as evidenced by his long list of graduate student supervision and funded projects in fog, cloud, and real-time systems.

Jose Luis SANCHEZ LOPEZمشاهده پروفایل

پژوهشگر

• Robotics
• Autonomous Systems
• Computer Vision
• +۵ مورد دیگر

Dr. Jose Luis SANCHEZ LOPEZ is a Research Scientist at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) of the University of Luxembourg, leading the Aerial Robotics Lab (AeRoLab) within the Automation & Robotics Research Group (ARG). He joined SnT in 2017 as a Postdoc Research Associate, promoted to Research Scientist in 2021. His research focuses on autonomous robotics, particularly aerial systems, emphasizing situational awareness, SLAM, and trajectory planning. Education: Ph.D. in Robotics (2017), M.Sc. in Automation & Robotics (2012), and Engineering degree in Industrial Engineering (2010), all from the Technical University of Madrid. Visiting Research: Arizona State University (2012), LAAS-CNRS (2014–2016). Research Interests: Multi-agent robotic systems, sensor fusion, localization/mapping, computer vision, machine learning, and trajectory control. He has authored over 56 peer-reviewed publications, with an h-index of 18. Projects: Leads projects like DEUS (PI), NEDA, ÄerdFly (PI), and RoboSAUR. Contributions span European, Luxembourg, and Spain-funded initiatives, focusing on autonomous systems, 5G integration, and construction-site robotics. Teaching: Lectured in MICS, BiCS, BING (Uni.lu) and GITI (UPM). Actively involved in academic service as a reviewer, editor, and competition participant (e.g., IMAV, IARC). Outreach: National Coordinator for Luxembourg’s Robotics European Week, promotes robotics education in schools and public events.

Jan A. Van Mieghemمشاهده پروفایل

عضو هیئت علمی

• Operations Management
• Supply Chain Operations
• Operations Strategy
• +۱۱ مورد دیگر

Jan A. Van Mieghem is the A. C. Buehler Professor and Professor of Operations at the Kellogg School of Management, Northwestern University. He also serves as a Professor by Courtesy at the McCormick School of Engineering and Applied Science. His research spans product, service, and supply chain operations, combining strategic and tactical perspectives with mathematical modeling, stochastic analysis, and empirical verification. Ph.D. in Business, Graduate School of Business, Stanford University (1995) MS in Electrical Engineering, Stanford University (1990) MS in Applied Sciences, KU Leuven, Belgium (1989) His research interests focus on operations strategy, supply chain optimization, and digital operations. He explores topics such as operational hedging, capacity investment, network flexibility, and the application of AI in inventory management. His work addresses healthcare operations, dual sourcing, and the interplay between collaboration and productivity in service networks. Recent research trends center on AI-driven inventory systems, dual sourcing under uncertainty, and healthcare resource allocation. He has authored over 60 academic articles and two textbooks: Operations Strategy: Principles and Practice and Managing Business Process Flows: Principles of Operations Management . 2023: First place in POMS College of Supply Chain Management Student Paper Competition 2020: Flexibility Excellence Award 2014: Wickham Skinner Award 2007: First MSOM Best Paper Award Van Mieghem has held leadership roles at Kellogg, including Deputy Dean (2023–present), Faculty Director of the Executive MBA program (2012–2017), and Chairman of the Department of Managerial Economics and Decision Sciences (2006–2009). He advises firms on operations strategy and management and has served on editorial boards of Management Science , Manufacturing & Service Operations Management , and Operations Research . He has mentored numerous Ph.D. students, including Audrey Bazerghi, Simrita Singh, Yangzi Jiang, and Dennis J. Zhang, who have secured academic and industry positions. His teaching spans operations management and strategy across MBA, Ph.D., and executive programs. Van Mieghem's work examines the intersection of operations strategy and execution, emphasizing financial value as a guiding metric. His empirical studies leverage real-world data from healthcare, manufacturing, and e-commerce to validate theoretical models and develop practical frameworks.

Albert S. Berahasمشاهده پروفایل

استادیار

• Nonlinear Optimization
• Machine Learning Optimization
• Stochastic Optimization
• +۵ مورد دیگر

Albert S. Berahas is an Assistant Professor in the Department of Industrial and Operations Engineering at the University of Michigan's College of Engineering. He joined the university in 2020 after completing postdoctoral positions at Lehigh University (2018-2020) and Northwestern University (2018). He holds a PhD in Engineering Sciences and Applied Mathematics from Northwestern University (2018), an MS in Applied Mathematics from Northwestern (2012), and a BSE in Operations Research and Industrial Engineering from Cornell University (2009). His research focuses on designing, developing, analyzing, and implementing algorithms for solving large-scale nonlinear optimization problems. His work spans multiple sub-fields including constrained optimization, optimization for machine learning, stochastic optimization, derivative-free optimization, and decentralized optimization. He is affiliated with the Michigan Institute for Data Science (MIDAS), the Michigan Institute for Computational Discovery and Engineering (MICDE), and the Michigan Center for Applied and Interdisciplinary Mathematics (MCAIM). Berahas has received numerous honors including the Charles Broyden Prize (2025), the Air Force Office of Scientific Research Young Investigator Program award (2025), the IISE Operations Research Division Teaching Award (2024), and the North Campus Dean's MLK Spirit Award for Community Building & Impact (2024). His recent publications demonstrate strong activity in developing novel optimization frameworks with theoretical guarantees for challenging problem settings. His research has been supported by significant grants including from the Office of Naval Research (ONR) and the Air Force Office of Scientific Research. He actively mentors PhD students and has successfully advised Jiahao Shi, who defended his dissertation in March 2025 and joined Amazon. Berahas is also engaged in community outreach, particularly through initiatives like Engage Detroit that aim to empower Detroit's next generation of engineers.

Thomas Wildمشاهده پروفایل

استاد

• Manycore system on chip (SoC) architectures
• Network processor (NPU) architectures
• On-chip communication architectures
• +۳ مورد دیگر

Dr.-Ing. Thomas Wild serves as an Academic Director at the Technical University of Munich (TUM), working within the TUM School of Computation, Information and Technology at the Chair of Integrated Systems. He maintains an active research and teaching role at the institution, with his office located in Building N1 (Theresienstr. 90), Room N2136 in Munich, Germany. Dr. Wild's research focuses on advanced computing architectures, with particular emphasis on manycore system on chip (SoC) architectures, network processor (NPU) architectures, on-chip communication architectures including networks on chip (NoC), and system level design methodologies. His work bridges theoretical research with practical implementation, often exploring design space exploration techniques to optimize system performance. The evolution of his research over two decades demonstrates a consistent focus on improving communication architectures and system-level design for embedded and high-performance computing platforms. His recent publications (2023-2025) reveal a growing integration of machine learning techniques with traditional hardware design, particularly in optimizing power-performance tradeoffs in embedded systems. There's a clear trend toward hardware-software co-design approaches, with significant work on SmartNICs, Linux system optimization, and network processing acceleration. His research shows strong interdisciplinary connections between computer architecture, networking, and machine learning. EUROPRACTICE representative for TUM city campus, facilitating access to commercial EDA tools for academic purposes Active collaborator with Professor Andreas Herkersdorf and other researchers at TUM Focus on practical implementations with FPGA-based prototyping and real system modifications Dr. Wild teaches several hardware design courses including VHDL Lab, SystemC Lab, and HW/SW Codesign, contributing to the education of next-generation computer engineers. His teaching directly complements his research in system design and hardware acceleration, providing students with hands-on experience in cutting-edge technologies.

Oskari Ville Pakariمشاهده پروفایل

مدرس

• Nuclear Engineering
• Reactor Physics
• Radiation Detection
• +۳ مورد دیگر

Oskari Ville Pakari is a Lecturer at the School of Basic Sciences, École polytechnique fédérale de Lausanne (EPFL), affiliated with both the Institute of Physics (IPHYS) and the Swiss Plasma Center (SPH-ENS). He contributes to teaching and research, particularly in reactor physics and radiation detection. His research focuses on nuclear reactor diagnostics , gamma noise analysis , and neutron spectroscopy . He actively develops mixed reality visualization tools for radiation detection data and participates in the European CORTEX project for reactor monitoring. Selected publications highlight his work in gamma-ray imaging , neutron noise simulations , and detector system validation using advanced statistical methods like bootstrapping and Welch's technique. Teaching activities include courses on Radiation biology, protection, and applications Radiation and reactor experiments He advises PhD student Saliba Michel and collaborates with international institutions such as CEA, KIT, and LRS (Laboratory of Reactor Physics and Systems Behaviour) at EPFL.

Kaushik Nayakمشاهده پروفایل

دانشیار

• Semiconductor Devices
• Mesoscopic Electronics
• Nanoelectronics
• +۳ مورد دیگر

Kaushik Nayak is an Associate Professor in the Department of Electrical Engineering at the Indian Institute of Technology Hyderabad . His research spans semiconductor device physics, mesoscopic electronics, and electro-thermal effects in nanoscale transistors, with recent work on diamond MOSFETs, 2D material contacts, and thermal resistance in nano-sheet FETs. Ph.D., Indian Institute of Technology Bombay M. Tech., Microelectronics, IIT Bombay B.E., Electronics & Telecommunication, Utkal University He teaches advanced courses on semiconductor device modeling, mesoscopic electronics, and electromagnetic wave propagation. His publications focus on nanoelectronics, device variability, and high-temperature operations. Contact: knayak@ee.iith.ac.in .

Pere-Pau Vázquezمشاهده پروفایل

استادیار

• Information Visualization
• Scientific Visualization
• Medical Data Visualization
• +۶ مورد دیگر

Pere-Pau Vázquez is an Assistant Professor in AI for Visual Computing at the Computer Vision Lab, TU Wien, Austria . Previously, he held academic positions at the ViRVIG Group and Facultat d'Informàtica de Barcelona (UPC) , where he taught courses in Programming, Computer Graphics, and Visualization for over 20 years. His research focuses on Information Visualization, Scientific Visualization, Medical Data Visualization, Molecular Visualization, and AI applications to Visual Computing . Current Teaching : Data Visualization, Fast Realistic Rendering, Information Visualization, Medical Images, Scientific Visualization, Virtual Reality, and 3D Medical Visualization. Former PhD Students : Elena Molina, Alexandra Cortez, Jesús Díaz, Pedro Hermosilla, Eva Monclús. His scientific awards include the Best PhD Thesis Award (UPC, 2003), Best Student Paper Award (SPIE, 2012), and Best Paper Award (International Conference on Computer Graphics Theory and Applications, 2013). Recent publications explore AI integration in biomedical visualization, molecular data analysis, and interactive techniques for volume rendering. He serves on the EuroGraphics Executive Board as Secretary and is active in steering committees for EuroVis and Visual Computing for Biology and Medicine . His work bridges Computer Graphics, Artificial Intelligence, and Human-Computer Interaction , with applications in medical and molecular data analysis.

Andrew Rau-Chaplinمشاهده پروفایل

استاد

• High Performance Computing
• Parallel Algorithms
• Data Warehousing
• +۱۴ مورد دیگر

Andrew Rau-Chaplin is a Professor and Dean of the Faculty of Computer Science at Dalhousie University, where he leads the Risk Analytics Lab and contributes significantly to research in high performance computing, parallel algorithms, and risk analytics. He is affiliated with the Institute for Big Data Analytics and has a strong academic and administrative presence. Education: Postdoc - DIMCS (Princeton, Rutgers, Bell Labs) PhD - Carleton University (1993) MCS - Carleton University (1990) BCS - York University (1986) His research focuses on applying parallel and high performance computing to data-intensive domains such as data warehousing, OLAP, catastrophe modeling, and risk analytics. He emphasizes both algorithmic design and practical system implementation, with a strong grounding in experimental evaluation. His work spans theoretical studies and real-world applications in finance, bioinformatics, and geospatial systems. The 15 most recent publications reflect a consistent focus on parallel data processing, OLAP optimization, indexing techniques (e.g., Hilbert curves), and risk modeling. Key themes include scalable data cube computation, view selection, adaptive coding, and spatial analytics, demonstrating expertise in both algorithmic innovation and systems-level performance. He has served on numerous scientific committees and grant panels, including NSERC and Compute Canada, and has been a journal editor for JPDC and DMTCS. Dr. Rau-Chaplin has supervised a wide range of graduate students in areas including risk analytics, GPU computing, text analytics, and parallel algorithms. His lab has received funding for postdoctoral, graduate, and undergraduate research positions. He teaches courses such as Parallel Computing, Software Engineering, Data Structures, and Risk Analytics, and has developed software tools like LaHave, Clustal XP, and Digital Coliseum. His lab, the Risk Analytics Lab, focuses on integrating analytics, risk management, and HPC for challenges in catastrophe modeling and financial risk. The lab leverages technologies such as stochastic simulation, optimization, and spatial OLAP.

• Computational Linguistics
• Natural Language Processing
• Multilingual Models
• +۷ مورد دیگر

Malvina Nissim is a leading researcher in computational linguistics and NLP at the University of Groningen's Department of Artificial Intelligence, with a focus on multilingual modeling, bias mitigation, and human evaluation frameworks. Key Contributions : Developed CALAMITA (Italian LLM benchmark), IT5 models for Italian language processing, and ReproHum framework for NLP evaluation reproducibility Research Pillars : Multilingual reasoning consistency, perspective-based text analysis, and figurative language modeling Her work spans activation steering techniques, cross-lingual transfer learning, and the creation of specialized language resources like the EurekaRebus dataset and MAGPIE idiom corpus. She pioneered methods for gender bias measurement in BERT and developed the SocioFillmore tool for perspective visualization. Recent publications explore model uncertainty as MCQ difficulty proxy, Italian headline generation benchmarks, and multilingual multi-figurative language detection. She actively participates in teaching initiatives like the "NLP with Bracelets" workshop for Italian high school students. Scientific Awards : ACL Best Paper Award (2025) EMNLP Outstanding Reviewer (2023) EVALITA Leadership Recognition (2024) She advises PhD students in model bias analysis and has contributed to the development of the Dutch Abusive Language Corpus (DALC) and the ReproNLP reproducibility framework. Her collaborations span institutions in Italy, Netherlands, and international NLP communities.

Donald Spectorمشاهده پروفایل

استاد

• Supersymmetry
• Particle Theory
• Quantum Field Theory
• +۱۶ مورد دیگر

Donald Spector is Professor of Physics at Hobart and William Smith Colleges (HWS), where he has been a faculty member since 1989. He holds a Ph.D. in Physics from Harvard University (1986) and has taught at Harvard, Cornell, and the University of Utrecht. He is affiliated with the Department of Physics in the School of Natural and Social Sciences and has served as coordinator of the Engineering Program and chair of the Physics Department. Ph.D., Harvard University, 1986 A.M., Harvard University, 1983 A.B., Harvard University, 1981, magna cum laude His research centers on supersymmetry, quantum field theory, and mathematical physics, with significant contributions to Q-balls, magnetic monopoles, and duality in supersymmetric quantum mechanics. He explores the intersection of physics with number theory, set theory, and computational complexity. His interdisciplinary work spans physics and the arts, particularly music (e.g., John Cage, Terry Riley) and theatre (e.g., Waiting for Godot ). His recent publications reveal a strong trend toward foundational questions in physics and information theory, especially the application of set-theoretic forcing to generalize information theory. His work bridges theoretical physics, mathematics, and the humanities, often drawing analogies between physical principles and artistic expression. Scientific awards and honors include: Teaching awards at Harvard and Cornell NSF-NATO Postdoctoral Fellowship KITP Scholar (2005–2008) Japan Society for the Promotion of Science Visiting Fellowship Philip J. Moorad Professor of Science (2005–2010) FQXi Grant (2013–2015) Spector has been regularly funded by the National Science Foundation, FQXi, KITP, and JSPS. He has supervised student research in quantum mechanics and simulated annealing. He is a founding member and board member of the Anacapa Society, which promotes theoretical physics at undergraduate institutions. He teaches courses such as Quantum Computing, Modern Physics, and interdisciplinary seminars like Physics through Star Trek and Time Travel & Multiple Universes . He is involved in multiple labs and collaborative initiatives, including organizing workshops at the Kavli Institute for Theoretical Physics and contributing to interdisciplinary projects at the Institute for Science and Interdisciplinary Studies. His recent work includes performing in plays and providing dramaturgical support for theatre productions.

• Sound and Music Computing
• Human-Computer Interaction
• Human-Centered Computing
• +۶ مورد دیگر

Dr. Sam Ferguson is a Senior Lecturer at the School of Computer Science, University of Technology Sydney (UTS), with a multidisciplinary background in music performance, cognitive science, and psycho-acoustics. His research explores the intersection of sound, music, and human experience through creative coding, machine learning, and interactive systems. Key Research Areas: Sound and Music Computing, Human-Computer Interaction, Creative Coding, Cognitive Science, Installation Art, and Acoustics. Current Projects: ARC Linkage project on creative coding and multiplicitous media; industry collaborations on IoT-based audiovisual systems. Recent Publications: Focus on spatial audio complexity, gestural interaction with networked sound, music emotion recognition frameworks, and robotic performance through genre-based cultural platforms. Leadership Roles: Director of Teaching & Learning Engagement; former Deputy Head of School (Teaching and Learning); active in ACM Creativity and Cognition Steering Committee. Teaching: Courses like Digital Media Studio , Prototyping Physical Interaction , and Data Processing using R within UTS's interdisciplinary Software Development Studio.

Wenjing Raoمشاهده پروفایل

دانشیار

• VLSI Test
• Fault-Tolerance
• Reliability
• +۳ مورد دیگر

Wenjing Rao is an Associate Professor at the Department of Electrical and Computer Engineering, College of Engineering, University of Illinois at Chicago (UIC). Her research focuses on VLSI test, fault-tolerance, reliability, and hardware security in emerging nanoelectronic systems. Education: Ph.D. in Computer Science from University of California, San Diego (2008) B.S. in Computer Science from Peking University (2001) Her work explores novel computation paradigms through physical unclonable functions (PUFs), defect-tolerant logic implementation, and scalable fault tolerance in many-processor arrays. Publications emphasize hardware security, reconfiguration strategies, and reliability challenges in nanoscale architectures. Notable honors include the 2017 Harold A. Simon Award for Excellence in Teaching and the 2012 NSF CAREER Award. She has contributed to key journals like IEEE Transactions on Computer-Aided Design and conferences including DATE, ASPDAC, and NANOARCH.