جست‌وجوی استاد و پژوهشگر

Erzsebet Reganمشاهده پروفایل

دانشیار

• Computational Biology
• Systems Biology
• Cellular Regulatory Networks
• +۴ مورد دیگر

Erzsebet Regan is the Whitmore-Williams Associate Professor of Biochemistry and Molecular Biology at The College of Wooster . Her research focuses on uncovering principles of coordination between cellular phenotypes across multiple scales, using computational modeling to predict emergent behaviors in health and disease. She is currently on leave for Fall 2025. Education Ph.D., University of Notre Dame, 2004 M.S., Babes-Bolyai University, 2000 B.S., Babes-Bolyai University, 1999 Research Interests Dr. Regan's work explores hierarchical biological systems, emphasizing the dynamic coordination of cellular regulatory networks. Her studies span: Cancer cell biology (proliferation, senescence, apoptosis) Cellular aging mechanisms Neuronal differentiation and inflammation Stem cell state transitions Endothelial heterogeneity Scientific Awards Henry Luce III Fund for Distinguished Scholarship (multiple grants) Hamburger Endowment for Collaborative Projects Advising & Collaborations She has advised numerous College of Wooster Independent Study students in projects involving Boolean modeling of cellular processes. Collaborations include NIH-funded work with William Aird (BIDMC) on endothelial dynamics and Dr. Katie Bentley on vascular morphogenesis.

Zeno TOFFANOمشاهده پروفایل

استاد

• Quantum Computing
• Systems and Control
• Telecommunications
• +۶ مورد دیگر

Zeno TOFFANO is a Professor at CentraleSupélec, part of the Laboratoire des Signaux et Systèmes (L2S). His research focuses on quantum computing, eigenlogic, systems and control theory, telecommunications, and their applications in signal processing, semiotics, and artificial intelligence. He holds a Ph.D. from Université Paris Sud XI (1985) and an HDR (2004) in optoelectronic systems modeling. Key research projects include COMEDY (Model for Control of Dynamical Systems), MODESTY (Modeling, Estimation, and System Analysis), and SYCAMORE (Telecommunications). His work bridges quantum theory with practical applications in robotics, behavioral dynamics, and text semantics. Recent contributions span quantum algorithms for PageRank computation, quantum-inspired models for hate speech analysis, and eigenlogic frameworks for fuzzy systems. He has organized and presented at international conferences (e.g., Quantum Information Processing, IEEE Quantum Computing Workshop) and authored chapters on quantum semiotics and robotic behavior. His labs and teams explore interdisciplinary topics such as quantum-inspired control systems and health informatics.

Sarah Assmannمشاهده پروفایل

استاد

• Plant Biology
• Molecular Biology
• Signal Transduction
• +۴ مورد دیگر

Sarah Assmann is the Waller Professor of Biology at Pennsylvania State University, affiliated with the IEE Research Themes in Climate and Natural Systems. Her research focuses on molecular and electrophysiological mechanisms of plant signal transduction, particularly in guard cells and responses to environmental stimuli like light, hormones, and abiotic stress. She leads the Assmann Lab in the Mueller Lab facility, contributing to interdisciplinary projects bridging plant biology, genomics, and computational modeling. Her work spans topics such as stomatal physiology, heterotrimeric G protein signaling, RNA structure dynamics, and climate adaptation in plants. Notable contributions include the development of Oryza CLIMtools for rice genomic-environmental associations and studies on riboSNitches' roles in climate-driven plant adaptation. She has been recognized with the Masatoshi Nei Innovation Prize in Biology (2025) and collaborates with researchers like Réka Albert, advancing systems biology approaches to plant stress responses. Her recent publications (2021–2025) highlight advancements in understanding G protein variants' agronomic impacts, RNA structural dynamics under stress, and computational modeling of signal transduction networks. Her research bridges fundamental biology with applications in crop improvement and climate resilience.

Sarah M. Assmannمشاهده پروفایل

استاد

• Plant Physiology
• Cell Signaling
• Abiotic Stress Response
• +۴ مورد دیگر

Sarah M. Assmann is the Waller Professor of Biology at the Department of Biology, Pennsylvania State University. She is affiliated with the Huck Institutes of the Life Sciences. Her research focuses on plant electrophysiology, cell signaling, and abiotic stress responses, particularly in guard cell function and G-protein signaling pathways. She leads projects aimed at improving crop resilience through genetic and environmental studies in rice and Arabidopsis. Research Interests: Dr. Assmann investigates how plants perceive and respond to environmental stresses like drought and heat. Key areas include guard cell signaling, heterotrimeric G-protein regulation, and RNA structure-function relationships. Her work integrates molecular, physiological, and systems biology approaches. Grants & Projects: NIFA-USDA 2019-67013-29234: Rice G-protein signaling for drought tolerance NIH-R01GM126079: G-protein phosphorylation mechanisms NSF-MCB 1715826: G-protein networks in stomatal closure Labs & Teams: The Assmann Lab focuses on plant stress biology, employing advanced techniques like Structure-seq for RNA structural analysis. Collaborations include interdisciplinary teams addressing crop improvement and environmental adaptation.

Luigi Glielmoمشاهده پروفایل

استاد

• Automatic Control
• Model Predictive Control
• Renewable Energy Systems
• +۵ مورد دیگر

Luigi Glielmo is a Professor of Automatic Control at the University of Sannio in Benevento, Italy. He holds a Master's and PhD in Electronic Engineering and Automatic Control from the University of Naples Federico II. Previously, he taught at the University of Palermo before returning to Naples. His academic leadership roles include Head of the Department of Engineering at University of Sannio (2001–2007), Rector’s Delegate for Technology Transfer (2009–2019), and Coordinator of PhD programs in Information Engineering and Information Technologies for Engineering. Research interests focus on automatic control engineering, including model predictive control, renewable energy systems, smart grids, robotics, biomedical applications (e.g., deep brain stimulation modeling), satellite autonomy, and Boolean control networks. He founded the GRACE research group and has authored over 190 papers, two books, and holds two patents. He is a Senior Member of IEEE, serves on the editorial board of IEEE Control Systems Letters, and chairs the IEEE Control Systems Society Technical Committee on Automotive Controls. Leadership roles include General Co-Chair of the 2019 European Control Conference and ordinary member of IFAC’s Conference Board. His work bridges theoretical advancements with practical applications in energy systems, robotics, and industrial automation.

Mahdi Imaniمشاهده پروفایل

استادیار

• Machine Learning
• Control Theory
• Learning Theory
• +۳ مورد دیگر

Mahdi Imani is an Assistant Professor in the Department of Electrical and Computer Engineering at Northeastern University, with a courtesy appointment in the Khoury College of Computer Sciences. He holds a PhD in Electrical Engineering from Texas A&M University (2019), and MSc and BSc degrees in Electrical and Mechanical Engineering from the University of Tehran (2014 and 2012, respectively). His research focuses on machine learning, control theory, Bayesian statistics, and signal processing, with applications in gene regulatory networks, network security, and human-AI collaboration. Dr. Imani has received prestigious awards, including the NIH NIBIB Trailblazer Award (2022), the NSF CISE Career Award (2020), and the Outstanding Associate Editor Award from IEEE Transactions on Neural Networks and Learning Systems (2023 and 2024). He serves as an Associate Editor for IEEE Transactions on Neural Networks and Learning Systems and IEEE Transactions on Vehicular Technology, and is a Senior Member of IEEE. His research projects include DARPA-funded work on verified probabilistic reasoning in mixed reality systems, NSF-funded statistical inference methods, and ONR-funded studies on human-AI team synergy. He leads a lab focused on developing scalable Bayesian methods and reinforcement learning techniques for complex systems.

• Application of Mathematics to Programming Languages
• Programming
• Software Engineering
• +۳ مورد دیگر

Dr. Jeremy L Jacob is a Senior Lecturer in the Department of Computer Science at the University of York. He holds a BSc in Mathematics from the University of Hull, an MSc in Computation from the University of Oxford (Oxon), and a DPhil (PhD) from Oxon. With over 10 years of postgraduate research experience, he has been a Lecturer since 1992 and joined the University of York in 1993. His research focuses on applying mathematical principles to programming language design, software engineering, and security protocols. His work spans formal methods, threat modeling in cloud and IoT systems, and security protocol analysis. He is affiliated with the Automated Software Engineering research group led by Professor Dimitris Kolovos. Contact details include office CSE/043 and phone +44 (0)1904 325667, though direct email access requires using the department's web form to protect against spam. Key contributions include pioneering work on translating CSP into timed automata, adapting threat modeling frameworks for modern systems, and exploring confidentiality properties in formal specifications (e.g., Circus and Z formalisms). His research bridges theoretical foundations with practical applications in cybersecurity and software engineering.

Haibing Luمشاهده پروفایل

استاد

• AI Fairness and Governance
• Data Security & Privacy
• Big Data Analytics
• +۴ مورد دیگر

Haibing Lu is a Professor and Department Co-Chair of Information Systems & Analytics at Santa Clara University's Leavey School of Business. He holds a Ph.D. in Information Technology from Rutgers University (2011), and B.S./M.S. in Mathematics from Xi'an Jiaotong University (2002/2005). His research focuses on AI fairness, data privacy, cybersecurity, and big data analytics, addressing real-world challenges in healthcare, transportation, and cloud computing. Education: Ph.D. in Information Technology, Rutgers University, 2011 M.S. in Mathematics, Xi'an Jiaotong University, 2005 B.S. in Mathematics, Xi'an Jiaotong University, 2002 Research interests include: AI governance and ethical frameworks Privacy-preserving technologies (e.g., differential privacy) Cybersecurity for IoT and smart grids Applications of machine learning in healthcare and transportation His work has been featured in prestigious journals like IEEE Transactions on Dependable and Secure Computing, ACM Transactions on MIS, and M&SOM, alongside media outlets such as The New York Times and WIRED. Key publications include studies on AI fairness in LLMs, privacy in cloud computing, and secure authentication protocols. Awards include: AACSB Innovations That Inspire Award (2021) M&SOM Best Paper Award Repeated SCU Leavey School Excellence Awards for Teaching/Research/Service Grants and funding sources include NSF, IBM, PARC, and industry partnerships like AKTANA and Ultimate Software. He advises on interdisciplinary projects involving data science, cybersecurity, and sustainable energy systems. Labs/Initiatives: Leads research in Information Systems & Analytics at SCU, with collaborations on metaverse-driven data management and AI governance frameworks.

Maria C. A. Leiteمشاهده پروفایل

دانشیار

• Mathematical Modeling
• Dynamical Systems
• Nonlinear Networks
• +۶ مورد دیگر

Maria C. A. Leite is an Associate Professor in the Department of Mathematics & Statistics at the University of South Florida St. Petersburg. She holds a Ph.D. in Mathematics from the University of Houston (2005), an M.S. in Mathematics from the University of Porto (2001), and additional degrees in Quality Compliance and Chemical Engineering. Her research focuses on mathematical modeling, dynamical systems, nonlinear networks, and optimal control, with applications to epidemiology, ecology, neurosciences, environmental sustainability, and molecular dynamics. Her work emphasizes understanding the relationship between network structure and dynamics, particularly in complex biosystems. Recent projects include computational molecular dynamics collaborations with the Basque Center for Applied Mathematics, ecological modeling of species viability under environmental stress, and Boolean framework studies on neural control of breathing. She has also explored interdisciplinary topics such as food sustainability through AI-driven approaches and daylight's physiological impacts. Leite has secured multiple grants and published extensively, with over 20 peer-reviewed articles since 2006. Her work spans theoretical advances in nonlinear networks to applied projects like optimizing tree harvesting in forests and analyzing the 2017 Nigerian meningitis outbreak. Her research has been presented at international conferences including the ISAAC Congress and IEEE Data Engineering Workshops. She actively mentors students and collaborates with researchers globally to bridge mathematical theory with real-world environmental, health, and sustainability challenges.

• Formal Methods
• Concurrency Theory
• Distributed Systems
• +۲ مورد دیگر

Wim Hesselink serves as a Professor within the Fundamental Computing group at the University of Groningen's Faculty of Science and Engineering. As an external employee ( Externe medewerker ), he maintains an active research profile with recent publications through 2025 and an ORCID identifier (0000-0002-1413-4320). His research centers on formal verification of concurrent systems, specializing in mutual exclusion protocols, linearizability of data structures, and temporal logic applications. Key contributions include theorem proving for shared memory systems, first-come-first-served scheduling principles, and wait-free algorithm design. His work directly addresses challenges in nondeterminism and atomicity within distributed computing environments. Analysis of his 2021-2025 publications reveals consistent focus on concurrency control mechanisms using formal methods. Major themes include lock algorithm verification (MCSH), temporal logic frameworks (UNITY), and linearizability proofs for arbitrary data objects. His methodology frequently employs proof assistants to establish correctness in shared-memory systems with nondeterministic behavior. Professor Hesselink has supervised 4 students and produced 125 research outputs including 94 articles, 13 book chapters, and 11 conference contributions. His international collaborations span multiple countries as visualized in the research network map, though specific grant details remain unreported in the source material.

Clemens Dubslaffمشاهده پروفایل

استادیار

• Formal Methods
• Probabilistic Model Checking
• Symbolic Methods
• +۴ مورد دیگر

Clemens Dubslaff is an Assistant Professor in the Formal System Analysis group at TU Eindhoven (The Netherlands). His research focuses on improving the reliability and explainability of computing systems through formal methods, particularly probabilistic model checking and symbolic techniques. He holds a Ph.D. from TU Dresden (Germany) and has affiliations with TU Dresden's Cluster of Excellence CeTI and Collaborative Research Center CPEC. His work addresses challenges in analyzing complex configurable systems and enhancing system transparency through explainable AI approaches. Education: B.Sc. in Mathematics and Computer Science (TU Dresden) M.Sc. in Computational Logic (NOVA University Lisbon) Ph.D. in Formal Methods (TU Dresden) Research Interests: Formal methods and model checking Symbolic analysis techniques Configurable and reconfigurable systems Explainability in AI and verification Probabilistic systems analysis Recent Achievements: NWO VENI Grant (2023) Launched OxiDD decision diagram framework (2024) Key contributions to feature-based software analysis Labs/Teams: Formal System Analysis group at TU/e, collaborating with Dresden's CeTI and CPEC initiatives.

Abdelhamid Tayebiمشاهده پروفایل

استاد

• Control Systems Theory
• Robotics
• Autonomous Vehicles
• +۷ مورد دیگر

Abdelhamid Tayebi is a Distinguished Professor and Research Chair in the Department of Electrical and Computer Engineering at Lakehead University. He also holds a courtesy professorship at Western University. His research focuses on control systems, autonomous navigation, and robotics, with applications to UAVs and multi-agent systems. Key roles include Graduate Coordinator and founder/director of the Robotics & Automatic Control Laboratory. Education: B.Sc. in Electrical Engineering, Ecole Nationale Polytechnique (1992) M.Sc. in Robotics, Université Pierre & Marie Curie (1993) Ph.D. in Robotics and Automatic Control, Université de Picardie Jules Verne (1997) Research Interests: Control systems theory, iterative learning control, autonomous vehicles, UAV navigation, hybrid feedback control, and nonlinear state estimation. His work emphasizes provable stability guarantees and real-world applications. Recent Articles Trends: Focus on hybrid control for obstacle avoidance, distributed estimation in multi-agent systems, and nonlinear observers for inertial navigation. Publications span IEEE Transactions on Automatic Control , Automatica , and robotics conferences like CDC and ACC. Awards: 2024 Distinguished Instructor Award (Lakehead University's top teaching honor) 2023 IEEE Fellow and EIC Fellow NSERC Discovery Accelerator Supplements (2013) Top 2% Highly Cited Scientist (Stanford, 2019–) Students & Labs: Advised over 20 PhD/MSc students and postdocs. Current research group includes postdocs Mayur Sawant (autonomous robotics) and Ishak Cheniouni (navigation algorithms). Notable former students include Miaomiao Wang (geometric observers) and Mouaad Boughellaba (multi-agent systems). Grants & Editorial Work: Holder of NSERC grants and Lakehead Research Chairs (2012–2027). Associate Editor for Automatica , IEEE Transactions on Control Systems Technology , and others. Active in reviewing for top journals/conferences.

Ian Durhamمشاهده پروفایل

استاد

• Quantum Physics
• Relativity
• Thermodynamics
• +۳ مورد دیگر

Ian Durham is a Professor of Physics at Saint Anselm College, specializing in foundational questions in quantum mechanics, relativity, and the philosophy of science. He holds a Ph.D. in Mathematics from the University of St. Andrews, an MSc in Applied Physics from Johns Hopkins University, and a BSc in Mechanical Engineering from the University of Buffalo. His research explores quantum information theory, relativistic quantum systems, and the interplay between thermodynamics and quantum mechanics. Dr. Durham is an active member of professional societies including the American Physical Society (APS), where he served as Treasurer of the Topical Group on Quantum Information (GQI) from 2012-2014, and the Royal Astronomical Society (RAS). He co-founded the APS GQI's publication The Quantum Times . His recent work addresses topics like quantum superposition in consciousness, observer-independent frameworks in relativity, and the philosophical implications of quantum theory. His awards include election to the Foundational Questions Institute (FQXi) and recognition for editorial contributions to quantum research. Durham's publications span theoretical physics, philosophy of science, and educational strategies for teaching quantum concepts. Notable themes include quantum contextuality, entanglement's role in thermodynamics, and historical interpretations of physics.

Michael Verdicchioمشاهده پروفایل

دانشیار

• Computer Science Education
• Software Engineering
• Algorithms
• +۳ مورد دیگر

Dr. Michael Verdicchio is an Associate Professor of Computer Science at The Citadel, affiliated with the Swain Family School of Science and Mathematics. He joined the institution in 2011 and holds a PhD and BSE in Computer Science from Arizona State University. His research focuses on computer science education, software engineering, algorithms, and previously on computational biology and bioinformatics. He also serves as the Graduate Program Director for Computer Science and chairs the graduate curriculum committee. His professional affiliations include Senior Member of the Association for Computing Machinery (ACM) and Program Evaluator for ABET's Computing Accreditation Commission. Dr. Verdicchio teaches a wide range of courses, from introductory computer science to advanced graduate topics like software testing and deployment. His educational contributions include adapting curricula for emerging technologies like generative AI and creating specialized courses such as DevOps. He has also led initiatives to ensure continuity in course delivery during disruptions like hurricanes and pandemics. His research spans pedagogical innovations, including automated assessment methods and interdisciplinary undergraduate research experiences. He has published extensively on topics ranging from network routing algorithms to gene regulatory networks in cancer research. His work bridges theoretical computer science with practical applications in education and bioinformatics. Dr. Verdicchio’s service roles include leadership in accreditation processes, curriculum design, and program assessment. He collaborates with external institutions like the College of Charleston and actively participates in national conferences, contributing to the advancement of computing education standards.

Jaijeet Roychowdhuryمشاهده پروفایل

استاد

• Machine Learning
• Cyber-Physical Systems
• Novel Computational Paradigms
• +۴ مورد دیگر

Jaijeet Roychowdhury is a Professor of Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley. He specializes in machine learning, novel computational paradigms, and the analysis/simulation of cyber-physical, electronic, and biological systems. His research group pioneered self-sustaining oscillator-based Ising machines and contributed to oscillator phase macromodeling, nonlinear system reduction, and open-source prototyping platforms like MAPP. Education: B.Tech., Electrical Engineering, Indian Institute of Technology (IIT) Kanpur, 1987 M.S., Electrical Engineering & Computer Science, UC Berkeley, 1989 Ph.D., Electrical Engineering & Computer Science, UC Berkeley, 1993 Research Interests: Machine learning integration with physical systems Innovative computational hardware (e.g., oscillator-based Ising machines) Oscillator networks for unconventional computing Nonlinear dynamical systems analysis Analog circuit simulation and verification Awards & Recognition: 2019 Bell Labs Prize (with Tianshi Wang) 2009 IEEE Fellow 2019-2023 Bakar Foundation Awards Bell Labs' Extraordinary Achievement Award (1996) Advising & Industry: Notable advisee: Tianshi Wang (Bell Labs Prize co-winner) Cofounder of Berkeley Design Automation (acquired by Mentor Graphics) Leadership roles at AT&T Bell Labs, Bell Labs, and CeLight Inc. Lab & Tools: Leads the Roychowdhury Research Group, developing MAPP (Model and Algorithm Prototyping Platform) and PHLOGON phase-based logic frameworks.