جست‌وجوی استاد و پژوهشگر

Jerry Trahanمشاهده پروفایل

استاد

• Theory of computation
• Parallel computation models
• Reconfigurable meshes
• +۳ مورد دیگر

Dr. Jerry Trahan is the Chevron Professor at the Division of Electrical & Computer Engineering within Louisiana State University's School of Electrical Engineering and Computer Science. His research focuses on foundational areas of computer science including parallel computation models, reconfigurable architectures, algorithm design, and reliability engineering. He holds a Ph.D. (1988) from the University of Illinois, Urbana-Champaign. Education: Ph.D. in Computer Science, University of Illinois at Urbana-Champaign (1988) Research Interests: Theory of computation Models of parallel computation Reconfigurable meshes and run-time reconfiguration Algorithm design and analysis with a focus on robotics and distributed systems Reliability in computing systems His recent work explores autonomous robot coordination, secure RFID protocols, and efficient grid-based algorithms. Over 30 years of contributions span reconfigurable computing, parallel architectures, and distributed systems reliability. Grants & Advising: No specific grants or advisee information is listed in the provided text. His research has been supported through university and industry partnerships.

Alin Stefanescuمشاهده پروفایل

استاد

• Software Engineering
• Cybersecurity
• Artificial Intelligence
• +۳ مورد دیگر

Alin Stefanescu is a Professor and Head of the Computer Science Department at the University of Bucharest , Romania. He is also a founding member of the Institute for Logic and Data Science (ILDS) . His research focuses on software engineering, cybersecurity, and artificial intelligence, with contributions to formal methods, model-based testing, and distributed systems. Education: PhD (2006) in Computer Science, University of Stuttgart Habilitation Thesis (2017) in Formal Methods for Software Testing, University of Bucharest MSc (2000), BSc (1998) in Computer Science, University of Bucharest Research Interests: Formal verification of distributed systems Model-based testing and software quality assurance AI-driven tools for cybersecurity and testing (e.g., RobustCheck, CyberGuardian) Blockchain applications in AI and identity management Reinforcement learning for fuzz testing and automation Recent Trends in Publications: Recent work emphasizes AI integration in testing frameworks, blockchain for secure AI systems, and adaptive cybersecurity tools. He has pioneered open-source tools like RiverFuzzRL and EBLT, addressing challenges in automated testing and vulnerability analysis. Awards: Best Paper Award at ICSOFT'23 (2023) 10-Year Most Influential Paper Award (2023, for 2013 work) Best Student Paper Award (2010) Grants & Labs: Active in EU-funded projects like DYNABIC (AI techniques) and MEASURE (metrics modeling). Leads the ILDS institute, focusing on logic and data science research.

Eli Upfalمشاهده پروفایل

استاد

• Algorithms
• Randomized Algorithms
• Probabilistic Analysis
• +۵ مورد دیگر

Eli Upfal is the Rush C. Hawkins Professor of Computer Science at Brown University, where he has been a faculty member since 1998 and served as department chair from 2002 to 2007. Prior to Brown, he held positions as a researcher and project manager at IBM Almaden Research Center and a professor at the Weizmann Institute of Science. He earned his undergraduate degree in mathematics and statistics and a doctorate in computer science from the Hebrew University in Jerusalem, Israel. Education: B.Sc./M.Sc. in Mathematics & Statistics, Ph.D. in Computer Science Previous Institutions: IBM Almaden Research Center, Weizmann Institute Upfal's research focuses on the design and analysis of algorithms, particularly randomized algorithms and probabilistic analysis. His work spans combinatorial and stochastic optimization, routing and communication networks, computational biology, and computational finance. He has also contributed to applying Rademacher Averages and VC-dimension to sampling-based algorithms for graph analysis and pattern mining. Recent publications emphasize algorithmic applications in graph theory, machine learning, and handling distribution drift in data analysis. His work includes practical implementations of theoretical concepts, such as Abra for betweenness centrality approximation and frameworks for secure data exploration like VizCertify and VizRec . Scientific Awards IEEE Fellow ACM Fellow IBM Outstanding Innovation Award IBM Research Division Award Upfal has advised PhD student Matteo Riondato and received funding from the National Science Foundation (NSF), Defense Advanced Research Projects Agency (DARPA), Office of Naval Research (ONR), and National Institute of Health (NIH). He co-authored the textbook Probability and Computing: Randomized Algorithms and Probabilistic Analysis with M. Mitzenmacher.

• Energy Conversion Systems
• Distributed Energy Resources (DER)
• Battery Storage Systems
• +۴ مورد دیگر

Nicolae Lucian Mihet is a **Full Professor in Energy Technology** at **Østfold University College, Norway**, affiliated with the Faculty of Information Technology, Engineering and Economics. His academic journey includes roles as Associate Professor (2008–2016) at Politehnica University of Timisoara, Romania, and Research Scientist at Danish Technical University (DTU) and Aalborg University in Denmark. He holds a PhD in Electrical Engineering from Politehnica University of Timisoara. **Research Interests**: Focuses on energy conversion systems, distributed energy resources (DER), smart grids, battery storage systems (BSS), and power electronics. His work emphasizes modeling, simulation, and control of renewable energy systems, including wind turbines, photovoltaics, and EV integration. **Publications**: Authored over 200 papers, 12 books, and guest-edited 5 special issues in journals like *IEEE Transactions* and *Energies*. Key contributions include wind turbine modeling (2004 IEEE award-winning paper), smart grid technologies, and wireless EV charging systems. **Awards**: 2021 Best Researcher Award at Østfold University College; 2005 IEEE IAS Transactions Second Prize Paper Award. **Grants & Projects**: Led 25+ projects, including 6 EEA/ Norway Grants. Coordinates the Master’s Program in Green Energy Technology and manages the *Intelligent Control of Energy Conversion and Storage Systems* lab. Supervised over 100 students and co-advised 3 PhDs. **Collaborations**: Partners with universities in Denmark, Germany, Italy, and Canada. Industry collaborations include ABB, Danfoss, and DONG Energy.

Ivan Bjerre Damgårdمشاهده پروفایل

استاد

• Cryptography
• Secure Communication
• Multi-Party Computation (MPC)
• +۳ مورد دیگر

Professor Ivan Bjerre Damgård is affiliated with the Department of Computer Science at Aarhus University, where he holds a full academic rank of Professor. His primary research focus lies in cryptography, secure communication, and privacy-preserving technologies. Key areas include multi-party computation (MPC), homomorphic encryption, and differential privacy. He has contributed to foundational work on secure protocols for dynamic networks, threshold cryptosystems, and resilient distributed systems. His recent publications (2023–2024) emphasize advancements in MPC protocols with optimized communication and round complexity, secure computation in unstable networks, and privacy-preserving techniques. Notable work includes 'Phoenix' (2023) addressing network instability and 'Broadcast-Optimal MPC' frameworks minimizing setup requirements. Professional activities include organizing conferences like TCC 2009 and ICALP 2008, as well as delivering lectures on cryptography and IT security. No scientific awards are explicitly listed in the provided information. His research collaborates extensively with global institutions, reflected in co-authored papers with researchers like Agarwal, Braun, and Ciampi. Ongoing work appears to prioritize practical implementations of theoretical cryptographic constructs in real-world distributed environments.

• Communications
• Networking
• Signal & Image Processing
• +۵ مورد دیگر

Mung Chiang is the Roscoe H. George Distinguished Professor of Electrical and Computer Engineering and President of Purdue University . He holds a PhD from Stanford University (2003) in Electrical Engineering, following earlier degrees from the same institution. His research focuses on optimizing networks and systems, including federated learning, edge computing, and 6G technologies. He leads projects on fog networking, smart data pricing, and social learning networks. Key research areas include network optimization , edge AI inference , and cooperative federated learning . Recent work addresses challenges in dynamic client management, hybrid terrestrial-satellite networks, and energy-efficient D2D systems. His publications emphasize practical solutions for heterogeneous environments and wireless network dynamics. Dr. Chiang has contributed to systems like Coded Edge Computing and Model Predictive Control (MPC) frameworks. He explores the interplay between connectivity and machine learning, with applications in autonomous vehicles and IoT. His work spans theoretical advancements and real-world implementations, including protocols for wireless system discovery and control. Current research trends include 6G innovations, resilient cyberphysical systems, and adaptive learning frameworks for dynamic networks.

Sharon Fergusonمشاهده پروفایل

استادیار

• Computer-Supported Cooperative Work
• Human-Computer Interaction
• Future of Work
• +۵ مورد دیگر

Sharon Ferguson is an Assistant Professor in the Management Sciences Department at the University of Waterloo and a faculty affiliate at the Schwartz Reisman Institute for Technology and Society. Her research focuses on understanding and improving teamwork through digital trace data analysis, particularly in Human-AI collaboration and virtual environments. She holds a PhD in Mechanical and Industrial Engineering from the University of Toronto (2024), where she also earned a BASc in Industrial Engineering (2020). Her work has been recognized with awards such as the 2023 Teaching Assistant Award and the Reviewer's Favourite Award at the International Conference on Engineering Design. Ferguson has led projects on Human-AI decision-making, student retention in AI, and the impact of remote work on engineering teams. She previously interned at Slack’s Future of Work team and served as President of the Graduate Society of Women Engineers. Education: PhD in Mechanical and Industrial Engineering (2024), University of Toronto BASc in Industrial Engineering (2020), University of Toronto Research Interests: Computer-Supported Cooperative Work Human-Computer Interaction Human-AI Collaboration Virtual Collaboration Engineering Design Processes Diversity and Inclusion in STEM Publications Trends: Her recent work emphasizes leveraging digital communication data to study team dynamics, with a focus on psychological safety, gendered language patterns, and the impact of AI on decision-making. She frequently publishes in top venues like CHI and CSCW, addressing hybrid work challenges and innovation in distributed teams. Awards and Grants: NSERC Canada Graduate Scholarship Microsoft AI & The New Future of Work Grant (2024) Human-AI Interaction Fellowship Ethics of AI Fellowship Technology and Society Fellowship Advising & Labs: Currently recruiting graduate students at the University of Waterloo. Active in the Ready Lab (University of Toronto) and COoKIE Group, focusing on algorithmic solutions for shared understanding in teams. She also leads projects on student social belonging and conflict analysis in hybrid design teams.

• Control Systems
• Robotics
• Optimization Algorithms
• +۳ مورد دیگر

Prof. Iman Shames is a Professor of Mechatronics at the Australian National University (ANU), affiliated with the School of Engineering and the CIICADA Lab. Previously, he held roles at the University of Melbourne (Associate Professor, 2014–2020; Senior Lecturer/McKenzie Fellow, 2012–2014) and was a postdoctoral researcher at KTH Royal Institute of Technology, Stockholm. He earned a B.Sc. in Electrical Engineering from Shiraz University (2006) and a Ph.D. in Engineering from ANU (2011). His research focuses on control systems, robotics, optimization, and multi-agent systems. Notable projects include developing adversary-robust positioning systems and advancing decentralized optimization algorithms. He has supervised research students and leads initiatives in real-time control and grid security through ANU collaborations. Key Projects: Adversity/Adversary-Robust Adaptive Positioning Systems, Phase Retrieval Algorithms, Hybrid Dynamical Systems Modeling Awards: None explicitly listed for Prof. Shames Labs/Teams: CIICADA Lab (ANU), Collaboration with QUT Centre for Robotics

• Distributed Computing
• Algorithms
• Fault-Tolerance
• +۴ مورد دیگر

Soma Chaudhuri is an Associate Professor of Computer Science at Iowa State University. She earned her B.S. in Mathematics and Computer Science from MIT (1984), and M.S. and Ph.D. in Computer Science and Engineering from the University of Washington (1987, 1990) under Professor Richard E. Ladner. Her research specializes in theoretical distributed computing, including algorithm design, lower bounds, and impossibility results for asynchronous/semi-synchronous systems. Current investigations focus on leveraging inexact timing information to solve canonical distributed computing problems. She develops techniques for simulating synchronous fault-tolerant algorithms in timing-uncertain environments and establishing complexity hierarchies for shared objects. Dr. Chaudhuri teaches undergraduate and graduate courses in algorithm design, theory of computation, operating systems, and specialized topics in distributed systems. She has served on program committees for major conferences including PODC and ICDCS, and reviews for leading journals in computer science. Her publications establish foundational results in consensus problems, shared memory consistency, and register implementations, contributing to theoretical frameworks for fault-tolerant distributed computing.

He Baiمشاهده پروفایل

دانشیار

• Unmanned Systems
• Multi-Agent Systems
• Nonlinear Control
• +۷ مورد دیگر

He Bai is an Associate Professor in the Department of Mechanical and Aerospace Engineering at Oklahoma State University (OSU), part of the College of Engineering, Architecture and Technology (CEAT). His research focuses on unmanned systems in GPS-denied environments, multi-agent systems, nonlinear control, atmospheric turbulence modeling, and human-robot interaction. He advises OSU's Mercury Robotics Society and Automation Society and serves as a faculty adviser for graduate and undergraduate students. Education includes a Ph.D. (2009), M.S. (2007), and B.E. (2005) in Electrical Engineering and Automation from Rensselaer Polytechnic Institute and the University of Science and Technology of China. Research interests emphasize robust control strategies for autonomous systems, including cooperative navigation, adaptive control under disturbances, and machine learning applications in robotics. His work addresses challenges like wind estimation for unmanned aerial systems (UAS) and human-vehicle collaboration in mixed traffic environments. Professional roles include Associate Editor for IEEE Control System Letters and the IEEE Control System Society Conferences. Recent publications explore reinforcement learning for multi-agent coordination, decentralized Bayesian learning, and turbulence impact on UAS navigation. Advising and lab involvement includes directing the Mercury Robotics Society and collaborating on projects like the intelligent cooperative driving testbed. His research bridges theoretical control systems with practical applications in autonomous systems and robotics.

Stefania Santiniمشاهده پروفایل

استاد

• Nonlinear Control
• Cyber-Physical Systems
• Time-Delayed Systems
• +۷ مورد دیگر

Stefania Santini is a Professor of Systems and Control Engineering at the University of Naples Federico II, leading the Distributed Automation Systems (DAiSY) Lab. Her research focuses on nonlinear control, cyber-physical systems, time-delayed systems, and their applications in automotive engineering, transportation, smart manufacturing, and energy. She has held roles in the Academic Senate (2013–2021) and serves as Senior Editor for IEEE Transactions on Intelligent Transportation Systems and Associate Editor for IEEE Transactions on Control Systems Technology. She actively collaborates with industry on national/international projects, emphasizing resilience and innovation in distributed control systems. Her research investigates distributed automation challenges in multi-agent systems, networked control, and cyber-physical security. Notable areas include fault-tolerant control for autonomous vehicles, resilient microgrid management under cyber-physical threats, and digital twin-based predictive maintenance. Recent work explores AI-driven solutions in smart manufacturing and energy systems, combining domain-specific expertise with advanced control methodologies. Publications span control theory advancements (e.g., time-delay systems stability, event-triggered control) and applied domains (autonomous vehicle platoons, telescope tracking, healthcare analytics). She leads projects addressing real-world challenges like eco-driving optimization for electric vehicles and cyber-resilient infrastructure. Current efforts emphasize sustainability in smart cities and railway automation through hybrid reinforcement learning and optimal control architectures. Her contributions include over 150 peer-reviewed articles and patents, with active engagement in IEEE ITS initiatives. Research outcomes are validated through industry partnerships, lab experiments, and high-fidelity cyber-physical platforms. Key projects involve SME collaboration on predictive maintenance frameworks and microgrid resilience under communication delays/attacks.

Dominique Schröderمشاهده پروفایل

استاد

• Privacy
• Distributed Trust
• Privacy-Preserving Technologies
• +۷ مورد دیگر

Dominique Schröder is a Full Professor and Head of the Privacy Enhancing Technologies Research Unit at TU Wien. Previously, he held academic positions at Friedrich-Alexander University of Erlangen-Nuremberg and the University of Saarland. His research focuses on cryptography, privacy-preserving technologies, and decentralized systems. He obtained his Ph.D. from TU Darmstadt and his diploma from TU Braunschweig. Key research areas include privacy-preserving techniques, secure multiparty computation, cryptographic protocols, and low-entropy security. His work bridges theoretical cryptography with practical applications, particularly in blockchain, genomic data management, and decentralized systems. Education: Ph.D. in Cryptography, TU Darmstadt Diploma in Computer Science, TU Braunschweig Postdoc at University of Maryland (advisor: Jonathan Katz) Notable Contributions: Developed Group ORAM for privacy in outsourced records Advanced adaptor signatures and threshold cryptography Contributed to privacy-preserving genomic data systems like PROMISE His publications span top venues in cryptography (e.g., CRYPTO, EUROCRYPT) and address topics like secure computation resilience, functional credentials, and privacy metrics. He actively participates in academic committees and advises on privacy-enhancing technologies.

• Computer Architecture
• Microelectronics
• Nanoscale Technology
• +۹ مورد دیگر

Dr. Paul Beckett is an Honorary Associate Professor in the School of Engineering at RMIT University. His research focuses on cutting-edge areas such as computer architecture, nanoscale microelectronics, digital logic design, and photonics. He specializes in low-power circuit design, FPGA-based systems, and sensor technologies with applications in healthcare and environmental monitoring. Beckett's teaching interests include embedded systems, VLSI design, and hardware description languages (VHDL). His research spans disciplines such as electronics, communications engineering, and distributed computing, with notable contributions to null convention logic (NCL) circuits, plasmonic sensors, and spectral imaging systems. He has collaborated on innovative projects like the TIARA apnea monitoring system and wearable health technologies. His recent work emphasizes interdisciplinary applications, including healthcare technology and biomimetic optical systems. Notable publications include advancements in gas sensing (H2S detection), THz spectrum analysis, and machine learning optimization for embedded systems. Beckett actively supervises research projects in asynchronous computing architectures and nanotechnology.

• Statistics
• Probability
• Markov Chain Monte Carlo
• +۶ مورد دیگر

Professor Yves Atchade is a faculty member at the Department of Mathematics and Statistics at Boston University, holding the Duan Family Faculty Fellow of Data Science position. He leads the FORMES research group focused on statistical methods for environmental sciences. His work bridges probability, high-dimensional computation, and applied environmental modeling. Current projects include large-scale Bayesian inference , deep learning for rainfall prediction in West Africa , and inverse problems in remote sensing . Collaborations with institutions like ENSEA, Abidjan and the TAHMO Foundation drive environmental sensor network deployments in Côte d'Ivoire. His research emphasizes MCMC algorithm design and unbiased Monte Carlo methods , with applications spanning environmental science, machine learning, and high-dimensional statistics. Recent publications explore unbiased MCMC , cyclical sampling , and Bayesian PINNs . Scientific contributions include: Unbiased MCMC with Couplings (2020) High-dimensional Bayesian Computation (2018) Efficiency bounds in semiparametric models (2020) Adaptive MCMC Confidence Intervals (2016) He actively mentors students and postdocs, with methodological developments in Markov chain theory , stochastic optimization , and Monte Carlo variance reduction . The FORMES group welcomes inquiries from prospective researchers via email at atchade@bu.edu .

• Augmented Reality
• Human-Computer Interaction
• Educational Technology
• +۵ مورد دیگر

Associate Professor Stewart Von Itzstein is affiliated with the University of South Australia’s UniSA STEM, specializing in Computer Science. His research focuses on augmented reality (AR), human-computer interaction, and educational technology. He has contributed to studies on spatial AR, haptic interfaces, deceptive digital patterns, and player motivation in games. Notable projects include analyzing IDE vs. traditional methods in programming assessments and evaluating cognitive impacts of AR predictive cues. His work bridges technical innovation with ethical considerations, such as consumer data rights and dark pattern mitigation. Research Areas: Spatial Augmented Reality (SAR) applications and performance optimization Haptic feedback systems and retargeting algorithms Educational technology and programming pedagogy Deceptive digital patterns and consumer protection Player motivation in digital games Key Collaborations: Wearable Computer Lab, Australian Research Centre for Interactive and Virtual Environments, and cross-disciplinary teams in STEM and creative fields.