جستجوی استاد راهنمای دانشگاهی

Zehor Belkhatirمشاهده پروفایل

مدرس

• Control Systems
• Biomedical Engineering
• Data Analytics
• +۵ مورد دیگر

Dr. Zehor Belkhatir is a Lecturer (equivalent to Assistant Professor) at the University of Southampton, affiliated with the School of Electronics and Computer Science, and serves as the Biomedical Engineering Programme Leader. She is also an Honorary Senior Lecturer at De Montfort University and a member of the Institute of Life Sciences. Her research focuses on control systems theory, data analytics, and biomedical applications, with emphasis on developing robust algorithms for complex systems. Education: Joint MEng and M.Sc. in Automatics and Control Systems Engineering from École Nationale Polytechnique (Algiers), followed by a Ph.D. in Electrical Engineering from KAUST (Saudi Arabia). Prior roles include positions at the University of Leicester, De Montfort University, and a postdoctoral fellowship at Memorial Sloan Kettering Cancer Center (USA). Research projects include EPSRC-funded initiatives like the REFORMIST program for interdisciplinary cancer decision frameworks and dynamic tumor-dose scheduling. Her work bridges theoretical control engineering with real-world applications in biomedical systems, oncology, and cardiovascular health. Teaching specialties include control engineering modules such as Digital Control, Nonlinear Control, and Biosystems Engineering. She actively supervises PhD students in cancer sciences, electronics, and computer science, fostering interdisciplinary collaboration. Awards include a filled US patent for her research contributions. She reviews for top journals/conferences (e.g., IEEE Transactions on Automatic Control) and serves on the EUCA Conference Editorial Board.

David W Snokeمشاهده پروفایل

استاد

• Quantum Mechanics
• Condensed Matter Physics
• Bose-Einstein Condensation
• +۶ مورد دیگر

David W. Snoke is a Distinguished Professor in the Department of Physics & Astronomy at the University of Pittsburgh’s Dietrich School of Arts and Sciences. His research focuses on quantum phenomena in semiconductor systems, particularly Bose-Einstein condensation of exciton-polaritons, nonlinear optics, and the interplay between quantum coherence and thermodynamics. He leads an experimental group employing ultrafast spectroscopy, interferometry, and advanced imaging techniques to study polariton condensates and novel material systems. He has contributed to foundational studies of polariton superfluidity, coherence dynamics, and light-induced superconductivity. His work bridges quantum mechanics and thermodynamics, addressing questions like the arrow of time and nonequilibrium phase transitions. Snoke is also an accomplished author and editor of textbooks and monographs on solid-state physics and quantum mechanics. Research Interests: Polariton condensates, quantum coherence, semiconductor optoelectronics, superconductivity, thermodynamic irreversibility Key Projects: Room-temperature polariton condensation, light-induced superconductivity, coherence in nonequilibrium systems His group’s experimental tools include femtosecond lasers, cryogenics, and advanced optical setups to probe nanoscale quantum systems. Snoke has advised graduate students like Jonathan Beaumariage and Qi Yao, and his work is supported by grants exploring fundamental physics and applied optoelectronics.

Yangming Liمشاهده پروفایل

پژوهشگر ارشد

• Image Analysis
• Machine Learning
• Mathematical Modeling
• +۷ مورد دیگر

Yangming Li is a Research Fellow at the Department of Applied Mathematics and Theoretical Physics (DAMTP) at the University of Cambridge, affiliated with the Cambridge Image Analysis research group. His work bridges applied mathematics, theoretical physics, and machine learning, with a focus on developing innovative models for image analysis, generative processes, and natural language understanding. Research interests include Fourier Neural Operators, diffusion models, generative adversarial networks (GANs), and their applications in solving complex problems across scientific computing and data-driven domains. His recent contributions explore operator learning for PDEs, robust diffusion models under noisy conditions, and adversarial attacks in text watermarking systems. Publications highlight advancements in operator-based neural networks, risk-sensitive generative modeling, and domain-aware NLP frameworks. His methodologies emphasize mathematical rigor while addressing practical challenges like missing data and model expressivity limitations. Active collaborations span interdisciplinary teams at DAMTP and the broader University of Cambridge research community.

• Cardiovascular Physiology
• Critical Care Medicine
• Hemodynamics
• +۳ مورد دیگر

Sheldon Magder is a Professor in the Department of Physiology at McGill University. He is affiliated with the Critical Care Division at the MUHC-Glen in Montreal, Quebec. His research focuses on cardiovascular physiology, particularly the control and distribution of peripheral blood flow during exercise, heat stress, and shock. Dr. Magder holds an M.D. from the University of Toronto. His work integrates clinical practice with physiological mechanisms, emphasizing hemodynamic monitoring, fluid management, and cardiopulmonary interactions in critical care settings. He has contributed extensively to understanding central venous pressure, right ventricular function, and the physiological basis of shock. His research also addresses challenges in mechanical ventilation, acid-base balance, and the application of Guytonian cardiovascular models in clinical decision-making. Education: M.D., University of Toronto. Research interests include fluid resuscitation strategies, hemodynamic monitoring technologies, and the pathophysiology of acute right heart failure. His recent studies explore the interplay between respiratory and cardiovascular systems in critical illness, with a focus on translational physiology. Dr. Magder’s publications highlight advancements in clinical guidelines for IV fluids, the role of neuropeptides in endothelial function, and the optimization of vasoactive therapies in shock. His scientific contributions span over four decades, with a focus on bridging basic physiology and clinical practice. Notable areas include the reinterpretation of central venous pressure, the mechanistic understanding of intraabdominal hypertension, and the physiological basis of cardiopulmonary monitoring in the ICU. His work has informed international guidelines for fluid management and mechanical ventilation protocols.

Sameh SELIMمشاهده پروفایل

پژوهشگر

• Molecular Biology
• Plant Pathology
• Biochemistry
• +۳ مورد دیگر

Sameh SELIM is a Teacher-Researcher in Plant Pathology and Molecular Biology at the Université de Picardie Jules Verne, affiliated with the Faculty of Agrosciences and the Department of Agricultural and Animal Sciences. He is a member of the AGHYLE research unit and actively collaborates with institutions like INRA, CNRS, and industry partners such as Bayer and BASF. His research focuses on plant-microbe interactions, alternative methods to chemical control, and the genetic biodiversity of soil microbial communities. SELIM holds a Ph.D. in Biochemistry, Molecular and Cellular Biology from the University of Burgundy (2005) and an MS in Biotechnology and Plant Pathology from El-Suez Canal University (1998). His work emphasizes the development of resistance inducers, fungicide efficacy, and the molecular mechanisms underlying plant defense responses. Recent publications highlight advancements in using Bacillus velezensis BE2 for disease control, transcriptomic analyses of wheat-pathogen interactions, and soil ecosystem service assessments. His research also addresses the durability of resistance mechanisms against pathogens like Zymoseptoria tritici and Mycosphaerella graminicola. SELIM collaborates with global institutions, including the University of Burgundy and ISA Lille, and participates in networks like RMT ELICITRA and the French Society of Phytopathology. His projects span from lab studies to field applications, addressing real-world challenges in sustainable agriculture and disease management.

Wayne W. Weaverمشاهده پروفایل

استاد

• Power Electronics
• Electric and Hybrid Vehicles
• Non-Linear Control Systems
• +۷ مورد دیگر

Wayne W. Weaver is a Professor of Mechanical and Aerospace Engineering at Michigan Technological University (MTU), serving as Associate Chair and Director of Graduate Studies. He also holds an affiliation as a Professor in the Electrical and Computer Engineering department. Weaver earned dual BS degrees in Electrical and Mechanical Engineering from GMI Engineering & Management Institute (1997), followed by MS and PhD in Electrical Engineering from the University of Illinois at Urbana-Champaign. His research focuses on power electronics, electric vehicle systems, nonlinear control strategies, and microgrid technologies, with particular emphasis on renewable energy integration and grid resilience. His professional experience includes roles at Caterpillar Inc. (1997-2003) and the US Army Corps of Engineers ERDC (2006-2008). He is a registered professional engineer in Illinois. Key research areas include microgrid stabilization, optimal control of energy systems, and wave energy converter optimization. Weaver has contributed to advancements in distributed energy resources, pulsed-power load management, and exergy-based control methodologies. Teaching responsibilities include courses on hybrid electric vehicle propulsion and linear systems theory. His work often bridges theoretical control frameworks with practical applications in maritime, military, and aerospace systems. Despite the lack of listed awards, his extensive publication record reflects impactful contributions to energy systems research. He collaborates with labs focused on renewable energy integration and resilient power grid architectures.

• Business Process Management
• Process Mining
• Business Process Simulation
• +۴ مورد دیگر

Marlon Dumas is a leading researcher in business process management and process mining at the University of Tartu, Estonia. With over 467 publications spanning from 1997 to 2025, his work has significantly advanced methodologies in business process analysis, simulation, and optimization. His research bridges theoretical foundations with practical applications, developing tools and frameworks that enable organizations to analyze and optimize operational processes. Dumas's primary research interests include business process management, process mining, business process simulation, prescriptive process monitoring, and data-aware business processes. He has pioneered methods for modeling resource availability, activity delays, and waiting times in business processes. His work on prescriptive process monitoring addresses critical challenges such as resource constraints, uncertainty in predictions, and causal effect estimation for interventions. Recent publications reveal a strong trend toward integrating artificial intelligence with business process management, particularly exploring the application of large language models to process optimization, monitoring, and redesign tasks. His research demonstrates consistent innovation, with publications appearing in top venues including Information Systems, Data & Knowledge Engineering, and the International Conference on Business Process Management. Dumas has developed several influential tools including SIMOD for automated discovery of business process simulation models, Optimos for simulation-driven process optimization, and Kairos for prescriptive monitoring. His collaborative network is extensive, featuring frequent co-authorship with prominent researchers including Marcello La Rosa, Luciano García-Bañuelos, Fabrizio Maria Maggi, and Wil M. P. van der Aalst. His work on privacy-preserving process mining, particularly regarding differentially private release of event logs, addresses critical challenges in applying process mining techniques while maintaining data privacy and compliance with regulations like GDPR. Dumas's research continues to push boundaries, with recent work exploring the integration of large language models with business process management systems, suggesting an ongoing commitment to advancing the field through innovative applications of emerging technologies.

Christine J. Picardمشاهده پروفایل

استاد

• Genetics
• Population Genetics
• Genomics
• +۳ مورد دیگر

Christine J. Picard is a Professor in the Biology Department at Indiana University, where she also serves as the Associate Dean for Research and Graduate Education in the School of Science. Her office is located in LD 222D, and she can be reached at (317) 278-1050 or cpicard@iu.edu. Her research is conducted through the Picard Lab, accessible at science.indianapolis.iu.edu/biology/picardlab. Education: Ph.D., Department of Biology, West Virginia University (2005-2010) M.Sc., Department of Chemistry, University of Toronto (2000-2002) B.Sc., Biology/Chemistry, University of New Brunswick (1996-2000) Research Interests: Dr. Picard specializes in the population genetics and genomics of forensically important insects. Her work leverages high-throughput sequencing technologies to understand the genetic control and natural variation in carrion insect phenotypes. She investigates how insects interact with decomposing remains and how this information can be applied in forensic contexts. Her research spans molecular evolution, forensic entomology, and the application of genomic tools to solve practical problems in forensic science. Publication Trends: Dr. Picard's recent work demonstrates a consistent focus on forensic entomology with expanding applications. Her publications show progression from fundamental genomic studies of carrion insects to innovative applications in environmental monitoring, chemical detection, and forensic analysis. The research increasingly incorporates interdisciplinary approaches, combining genetics, ecology, and analytical chemistry to develop novel forensic tools and insights into insect biology. Professional Contributions: Dr. Picard has contributed to significant book chapters in the field, including "Population genetics and molecular evolution of carrion-associated arthropods" and "Molecular biology in forensic entomology." Her work has appeared in prestigious journals including Journal of Medical Entomology, Scientific Reports, PLoS One, and Environmental Science & Technology. Research Leadership: As Associate Dean for Research and Graduate Education, Dr. Picard oversees research initiatives and graduate programs within the School of Science. Her laboratory serves as a hub for interdisciplinary research at the intersection of genetics, entomology, and forensic science, training students in both theoretical and applied aspects of these fields.

• Computational Fluid Dynamics (CFD)
• Flow Visualization
• Vortex Dynamics
• +۵ مورد دیگر

Dr. Abbas Ghasemi is an Assistant Professor in the Department of Mechanical, Industrial, and Mechatronics Engineering at the University of Toronto. His research focuses on computational and experimental fluid dynamics with applications in health and sustainability. He holds a PhD from the University of Waterloo (2019), and degrees from the University of Tabriz (BSc 2005, MSc 2008) and University of Windsor (MASc 2012). Education : BSc, University of Tabriz (2005) MSc, University of Tabriz (2008) MASc, University of Windsor (2012) PhD, University of Waterloo (2019) Research interests include vortex dynamics, multiphase flows, pathogen transport modeling, and AI-driven epidemiology frameworks. His work bridges fluid physics with public health challenges, such as disease transmission modeling for mass gatherings (e.g., FIFA World Cup studies). He has published in Journal of Fluid Mechanics , Physics of Fluids , and Scientific Reports . Key achievements include NSERC Postdoctoral Fellowships (2021), a CFD Society of Canada award (2016), and impactful collaborations with MIT and the Fields Institute. His mission is to apply thermo-fluid dynamics principles to improve human health and environmental sustainability. Awards & Recognition : NSERC Postdoctoral Fellowships (2021) CFD Society of Canada Graduate Scholarship (2016) Featured article in Physics of Fluids (2016) He actively supervises students and collaborates internationally. Recent work includes agent-based modeling frameworks for pandemic preparedness and green energy solutions.

Benjamin Azizمشاهده پروفایل

دانشیار

• Cyber Security
• Formal Methods
• Software Engineering
• +۴ مورد دیگر

Benjamin Aziz is an Associate Professor at Buckinghamshire New University, where he leads courses in Software Engineering, Cyber Resilience, and Computer Science. Previously, he was a Senior Lecturer at the University of Portsmouth's School of Computing (2010-2023) and worked as a Senior Research Scientist at Rutherford Appleton Laboratory. He holds a Ph.D. in Computer Science from Dublin City University (2003) and an M.Sc. in Networks and Distributed Systems from Trinity College Dublin (1999). His research focuses on formal methods, cybersecurity, IoT systems, and data-driven approaches to systems security. Key affiliations include Fellow of Advance HE and memberships with IEEE, IET, BCS, and ERCIM. He has contributed to EU projects like GridTrust and Consequence, and serves as Associate Editor for Wiley's Security and Communication Networks journal. His work spans over 160 peer-reviewed publications and two books, emphasizing formal analysis of protocols, steganography detection, and incident response metrics. Research interests include: Cybersecurity frameworks for IoT and cloud systems Formal specification and verification of security protocols Data-driven approaches for anomaly detection Attribute-based access control models Recent articles explore requirements engineering matrices, healthcare monitoring logic models, and Korean police dataset analysis. He has advised on cyber resilience strategies and contributed to tools like Trusty for social network data sharing.

Sepehr Amir-Mohammadianمشاهده پروفایل

دانشیار

• Cybersecurity
• Programming Languages
• Formal Software Security Assurance
• +۵ مورد دیگر

Sepehr Amir-Mohammadian is an Associate Professor in the Department of Computer Science at the University of the Pacific, part of the School of Engineering and Computer Science. His research focuses on cybersecurity, programming languages, and formal software security assurance, particularly applying linguistic approaches to ensure properties in security-critical applications. He earned his PhD in Computer Science from the University of Vermont (2017), focusing on in-depth security policy enforcement, following an MS in Information Security Engineering (Amirkabir University of Technology, 2011) and a BS in Information Technology Engineering (Amirkabir University of Technology, 2009). Teaching interests include computer networking, reliable software design, programming languages, and theoretical computer science. He has held leadership roles such as Engineering & Computer Science Council Chair (2020-2021) and currently represents his school in the Technology in Education Committee. His research bridges theory and practice, with contributions to audit logging correctness, quantitative information flow analysis, and cybersecurity in cyber-physical systems. Recent work emphasizes concurrent audit logging in distributed systems, timing attack analysis in cyber-physical systems, and leveraging digital twins for security quantification. Notable collaborations include the OpenMRS medical records system and PRISM-Leak tool development for probabilistic program analysis. His publications span conferences like ACM CPSS, IEEE COMPSAC, and IEEE ICNC, addressing challenges in microservices, concurrency, and formal methods. While no specific awards are noted, his contributions to security frameworks and practical implementations reflect significant scholarly impact. Research groups and projects include work on hybrid-dynamic systems, concurrent logging, and network protocol testing with large language models.

• Computer Science
• Electrical Engineering
• Robotics
• +۷ مورد دیگر

Pengfei Li is a prolific researcher affiliated with multiple academic institutions, including Harbin Medical University, Yale University, Beihang University, Zhejiang University, and others. His work spans interdisciplinary domains such as machine learning, robotics, remote sensing, and biomedical engineering. Research interests focus on Machine learning and deep learning for industrial and medical applications Signal processing and sensor technologies Remote sensing and geospatial data analysis Robotic control systems and exoskeleton design Code search and software engineering optimization His recent publications highlight trends in FPGA-based real-time systems, multimodal machine learning, and AI-driven diagnostics. While awards and student advising details are absent in the provided data, his contributions to IEEE journals and conferences underscore his expertise in algorithm design and applied informatics.

Alexandre Mendesمشاهده پروفایل

مدرس ارشد

• Machine Learning
• Optimization
• Deep Learning
• +۶ مورد دیگر

Dr. Alexandre Mendes is a Senior Lecturer at the University of Newcastle, affiliated with the School of Information and Physical Sciences and the Department of Computing and Information Technology. His research focuses on machine learning, optimization, and deep learning, with applications in robotics, energy systems, and transport logistics. Education: PhD in Electrical Engineering, Universidade Estadual de Campinas, Brazil MSc in Electrical Engineering, Universidade Estadual de Campinas, Brazil Bachelor in Applied Mathematics, Universidade Estadual de Campinas, Brazil Graduate Certificate in the Practice of Tertiary Teaching, University of Newcastle Research Interests: Mendes specializes in applying machine learning to real-world problems such as optimizing railway logistics, predicting solar energy output, and improving robotic systems. His work bridges theory and practice, collaborating with industries like CSIRO and Hunter Valley Coal Chain. Grants and Funding: He has secured over AU$1.5M in grants from ARC, CSIRO, and industry partners. Key projects include coal train scheduling optimization and solar energy prediction using deep learning. Awards: Work Integrated Learning Staff Member of the Year (2020) Best Student Paper Award (2012) Pro Vice-Chancellor's Research Excellence Award (2011) Labs and Teams: He leads the NUbots robotics team, focusing on humanoid robots and autonomous systems. His research group collaborates on projects like the Sydney Metro and Hunter Region rail network optimization.

Joseph Timoneyمشاهده پروفایل

استاد

• Audio Signal Processing
• Musical Sound Synthesis
• Digital Audio Watermarking
• +۳ مورد دیگر

Joseph Timoney is a professor at the Department of Computer Science , Maynooth International Engineering College , Maynooth University. He teaches undergraduate programs in Computer Science and Music Technology, with expertise in audio signal processing, musical sound synthesis, and digital modeling of analog subtractive synthesis. His research spans sound synthesis algorithms, audio watermarking, and ubiquitous music ecosystems.

Sankardas Royمشاهده پروفایل

دانشیار

• Cybersecurity
• Digital Forensics
• Android Security
• +۵ مورد دیگر

Sankardas Roy is an Associate Professor in the Department of Computer Science at Bowling Green State University. His office is located in Room 238, Hayes Hall, Bowling Green, Ohio. He holds a PhD in Information Technology from George Mason University (2008), an MS in Computer Science from the Indian Statistical Institute (2001), and a BS in Electrical Engineering from Bengal Engineering College (1997). Research Interests: Dr. Roy's research focuses on cybersecurity and digital forensics, with specialization in Android security vetting through static/dynamic analysis and machine learning techniques. Additional interests include digital forensics tool evaluation, game theory applications in security, secure data aggregation in distributed systems, and attribute-based encryption schemes. Publication Trends: His recent publications demonstrate a strong focus on Android security frameworks, malware detection using deep learning, and digital forensics methodologies. Earlier work emphasized wireless sensor network security and game-theoretic defense mechanisms, showing consistent innovation in applied security solutions across different computing domains. Grants and Projects: NSF SaTC-funded project: "Data-driven approaches for security vetting of Android apps" (2017-2021) NIST-funded project: "Incorporating standards in Digital Forensics curricula" (2017-2019) Research Group: Dr. Roy leads an active research team including current MS students (Prabesh Pathak, Prabesh Poudel) and BS students (Andrew Meyer). Past students include Shiva Bhusal (MS 2018), Dewan Chaulagain (MS 2019), and David Shaw (BS 2020).