جست‌وجوی استاد و پژوهشگر

Stefan Klusمشاهده پروفایل

مدرس

• Data-driven model reduction
• Transfer operator approximation
• Machine learning
• +۸ مورد دیگر

Dr. Stefan Klus is a Lecturer at the School of Mathematics and Physics, University of Surrey. His research focuses on data-driven model reduction, transfer operator approximation, and kernel-based machine learning applied to dynamical systems. He specializes in interdisciplinary applications across quantum physics, fluid dynamics, and computational biology. Education: PhD in Industrial Mathematics (2011, Paderborn University) and Habilitation (2020, Freie Universität Berlin). Research Interests : Data-driven modeling and reduced-order methods Koopman operator theory and transfer operators Machine learning for dynamical systems (e.g., Deeptime library) Tensor decompositions and quantum systems analysis Graph-based analysis (e.g., microbiome dynamics) Publications : Klus has contributed to over 50 peer-reviewed articles, with recent work emphasizing: Kernel methods for quantum chemistry and physics Tensor-based approaches for high-dimensional systems Applications in climate science (e.g., Pacific SST modeling) Agent-based modeling and social systems Technical Contributions : Co-developer of the Deeptime Python library for dynamical modeling Pioneer in Koopman operator-based model reduction Advanced graph kernel methods for microbiome analysis

Sharad Mehrotraمشاهده پروفایل

استاد

• Data Management
• Distributed Systems
• Database as a Service
• +۷ مورد دیگر

Sharad Mehrotra is a Distinguished Professor at the University of California, Irvine (UCI), leading the Center for Emergency Response Technologies (CERT) and directing the NSF-funded RESCUE project. He previously served at the University of Illinois, Urbana-Champaign, and holds a Ph.D. from the University of Texas at Austin (1993). His research focuses on data management, IoT systems, privacy-preserving technologies, and smart spaces, with contributions to frameworks like TIPPERS and MARS. Education: Ph.D., Computer Science, University of Texas at Austin, 1993 Research Interests: His work bridges database systems, security, and IoT, emphasizing privacy in smart environments. Notable projects include sentient space technologies for disaster response, cryptographic methods for encrypted data queries, and semantic IoT integration. Recent efforts address privacy in multi-owner data systems and resilient community water infrastructure. Awards & Recognition: ACM Fellow (2024) SIGMOD Best Paper (2001), DASFAA Best Paper (2004) NAVWAR Innovation Award (2021) Outstanding Graduate Mentor (2005) Grants & Leadership: As RESCUE PI, he managed $12.5M NSF funding, developing crisis-response software deployed by emergency agencies. Collaborations include the Cal-IT2 institute (UCSD/UCI) and the US Navy’s TIPPERS platform. He co-leads initiatives like the NSF Civic Innovation Challenge for disaster resilience in aging communities. Labs & Teams: Directs UCI’s Information Systems Group and CERT, fostering interdisciplinary research with 60+ members. His teams produce open-source tools (e.g., SEMIoTIC, PrivacySphere) and engage in global partnerships via Fulbright Visiting Scholar programs.

• Robotics
• Machine Learning
• Reinforcement Learning
• +۳ مورد دیگر

Pawel Ladosz is a Lecturer in Engineering Systems for Robotics at the Department of Mechanical and Aerospace Engineering, The University of Manchester. His research focuses on applying machine learning and computer vision to mobile robots, particularly in extreme environments such as total darkness or cluttered spaces. He is actively involved in developing autonomous navigation systems, wireless signal mapping, and high-level decision-making for robotic swarms. He teaches courses including Robotic Systems Design Project and Autonomous Mobile Robots. Education: PhD in Establishing and Optimising Unmanned Airborne Relay Networks (Loughborough University, 2014–2019) MEng in Aerospace Engineering (The University of Manchester, 2010–2014) Research Interests: Ladosz’s work emphasizes reinforcement learning for robotics, vision-based autonomous systems, and exploration in challenging environments. His projects often intersect with UN Sustainable Development Goals, contributing to innovations in robotic autonomy and sensor networks. Awards: He received the 2nd Autonomous Flying Technology Competition award in 2021, recognizing his contributions to autonomous flight systems. His research has also led to the establishment of the Centre for Robotic Autonomy in Demanding and Long-Lasting Environments (CRADLE), fostering cross-disciplinary collaborations. Grants & Projects: As Principal Investigator in the Aerospace Engineering initiative (2010–2035), he explores UAV communication networks and trajectory planning. His work addresses urban environment challenges, including relay positioning and signal prediction. Labs/Teams: Ladosz contributes to CRADLE, advancing robotic autonomy in extreme scenarios. His lab focuses on integrating AI and robotics for real-world applications.

Mehdi Asheghiمشاهده پروفایل

استاد مدعو

• Thermal Engineering
• Electronics Cooling
• Heat Transfer
• +۳ مورد دیگر

Mehdi Asheghi is an Adjunct Professor at Stanford University specializing in advanced thermal management solutions. His research focuses on heat transfer optimization, electronics cooling, and energy-efficient systems using cutting-edge materials science and micro/nanofabrication techniques. His work spans high-heat-flux cooling, phase-change materials, and thermal interface technologies, with applications in power electronics, integrated circuits, and sustainable energy systems. Innovations include microchannel coolers, copper nanowire composites, and porous thermal structures. With publications addressing thermal challenges from chip-scale to industrial systems, his research advances reliability and performance in electronic devices and energy infrastructure.

Stuart Bruce Dalzielمشاهده پروفایل

استاد

• Fluid Mechanics
• Environmental Fluid Dynamics
• Geophysical Fluid Dynamics
• +۶ مورد دیگر

Professor Stuart Bruce Dalziel is a Professor of Fluid Mechanics at the Department of Applied Mathematics and Theoretical Physics (DAMTP), University of Cambridge, where he has held academic roles since 2001. He leads the GK Batchelor Laboratory, a world-leading facility for experimental fluid dynamics. His research focuses on geophysical, environmental, and industrial fluid mechanics, employing theoretical, numerical, and experimental methods. Key areas include internal gravity waves, granular flows, turbulence, and building ventilation. Recent projects involve buoyant plumes, reactive flows, and applications like decontamination and hydrogen gas pipeline management. He is actively involved in supervising PhD students and has earmarked funding for projects on skipping stone dynamics and hydrogen gas purging in pipelines. Education and Career: Professor of Fluid Mechanics (2016–present) Reader in Fluid Mechanics (2012–2016) University Senior Lecturer (2001–2012) Director of the GK Batchelor Laboratory (1997–present) Research Interests: Dalziel’s work bridges experimental, numerical, and theoretical approaches to address challenges in fluid mechanics. Recent projects include studying stratified turbulence, Rayleigh-Taylor instabilities, and fluid dynamics in rotating systems. His applied research extends to environmental engineering, such as improving building ventilation systems and mitigating airborne disease transmission. Advising and Grants: He mentors PhD students from diverse backgrounds (mathematics, engineering, physics) and oversees funded projects combining experimental and computational methods. Current opportunities focus on novel fluid dynamics problems with practical applications. Labs and Facilities: The GK Batchelor Laboratory, under his leadership, develops advanced diagnostics and software for fluid dynamics research, widely adopted in the scientific community.

Shahin Sirouspourمشاهده پروفایل

استاد

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

Shahin Sirouspour is a Professor in the Department of Electrical and Computer Engineering at McMaster University. His research focuses on robotics, autonomous systems, control systems, and optimization, with applications in aerial robotics, teleoperation, haptics, medical robotics, and smart energy grids. He is affiliated with the Telerobotics, Haptics and Computational Vision Laboratory and teaches courses such as Non-linear Control Systems and Electrical Systems Integration Project. He holds a Ph.D. from the University of British Columbia and has supervised numerous graduate students. His lab includes advanced equipment like multi-axis robotic manipulators, haptic interfaces, and real-time computing systems. Education: B.Sc. and M.Sc. from Sharif University of Technology (Iran), Ph.D. from University of British Columbia (Canada). Current roles include accepting graduate students and leading research clusters in Digital & Smart Systems, Energy, and Transportation. Awards include the McMaster President's Award for Excellence in Graduate Supervision. His work bridges theoretical control systems with practical applications in healthcare, energy, and autonomous systems. Research highlights include developing control strategies for multi-agent robotic systems, smart grid optimization, and medical robotics. Collaborations with institutions like MacAUTO and industry partners (e.g., MDA Space Missions) enhance translational impact. His lab supports projects on asymmetric teleoperation, deformable tissue simulation, and microgrid energy management.

Soufiene Djahelمشاهده پروفایل

استاد

• Connected and Autonomous Vehicles (CAVs)
• Unmanned Aerial Vehicles (UAVs)
• Cyber Security
• +۷ مورد دیگر

Soufiene Djahel is a Professor at the Centre for Future Transport and Cities (CFTC) at Coventry University, UK. His research focuses on connected and autonomous vehicles (CAVs), unmanned aerial vehicles (UAVs), cyber security, and smart cities. He holds a PhD in Secure Routing and Medium Access Protocols from Université des Sciences et Technologies de Lille (2010), and has held academic positions including Senior Lecturer at the University of Huddersfield and Manchester Metropolitan University. His research interests include CAV coordination protocols, cyber-physical security solutions, and intelligent transportation systems. Djahel leads projects such as the £1.2M AeroPharma Logistics initiative and has secured funding from the Newton Fund and JSPS. He is a recipient of the 2021 JSPS Invitational Fellowship and has published extensively in IEEE journals and conferences. Current projects explore UAVs-as-a-service, digital twins for CAVs, and B5G/6G for smart infrastructure. He advises PhD students on topics like AI-based threat mitigation and transport electrification. Djahel also serves as an external examiner and editorial board member for journals like IEEE Transactions on Intelligent Transportation Systems.

Tina Comesمشاهده پروفایل

استاد

• Crisis Informatics
• Decision Theory
• Disaster Management
• +۲ مورد دیگر

Tina Comes is a Full Professor in Decision-Making & Digitalisation at the University of Maastricht, Netherlands. She holds a part-time position (0.2 FTE) and has previously held academic roles at TU Delft (Associate Professor in Decision-Making for Resilience, 2017), University of Agder (Full Professor in ICT, 2015-2017), and Visiting Professor at Lamsade, Université Dauphine, Paris (2014). Her research focuses on Crisis Informatics , Decision Theory , Disaster Management , Humanitarian Logistics , and Resilience . Her work spans building simulation , ventilation systems , and energy-efficient design , with grants totaling €9.6 million since 2012. Key projects include Resilient Systems (NL Ministry of Defense, 2020-2026), H2020 HERoS (2020-2023), and Climate Resilient Urban Infrastructure (Amsterdam, 2020-2022). She has supervised 6 PhD students at TU Delft (2017-2022), 3 Postdocs/PhDs at University of Agder (2013-2020), and 1 PhD at Université Toulouse (2014-2018). Her scientific awards include: 2020 José Maria Sarriegi Award by the Spanish Red Cross 2019 Emerald Literati Award 2016 Delft Technology Fellowship (acceptance rate 2012 Best Paper Award at ISCRAM Conference

Ramana Vinjamuriمشاهده پروفایل

دانشیار

• Brain-Machine Interfaces
• Neuroprosthetics and Exoskeletons
• Machine Learning
• +۴ مورد دیگر

Ramana Vinjamuri is an Associate Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC). He holds a secondary appointment as Visiting Professor at the Indian Institute of Technology, Hyderabad, India. His academic journey includes a Ph.D. in Electrical Engineering from the University of Pittsburgh (2008), M.S. in Bioinstrumentation from Villanova University (2004), and B.Tech. in Electrical and Electronics Engineering from Kakatiya University (2002). Dr. Vinjamuri's research focuses on Brain-Machine Interfaces (BMIs) for upper-limb prostheses control , neuroprosthetics and exoskeletons , machine learning in motor control , and neurophysiological signal processing . His work extends synergy-based models to control 37-dimensional hand movements, addresses human-robot interaction through emotionally intelligent systems, and develops neurotechnologies for substance use disorder using wearable sensors and AI. NSF CAREER Award (2019) NSF IUCRC BRAIN Center Planning Grant (2020) Harvey N Davis Distinguished Teaching Assistant Professor Award (2018) His publications demonstrate expertise in EEG and EMG signal analysis , deep learning for motor decoding , synergy modeling , and humanoid robot control . The Vinjamuri Lab at UMBC involves graduate, undergraduate, and high school researchers, with international collaborations in India and the US.

Manxi Wuمشاهده پروفایل

استادیار

• Societal Networks
• Game Theory
• Network Optimization
• +۴ مورد دیگر

Manxi Wu is an Assistant Professor in Cornell University's School of Operations Research and Information Engineering, specializing in societal networks and game-theoretic approaches to system design. Her research develops computational models for strategic learning and incentive mechanisms in socio-technical systems, with applications to transportation networks and digital platforms. Education: B.S. Applied Mathematics, Peking University (2015) M.S. Transportation, Massachusetts Institute of Technology (2017) Ph.D. Social and Engineering Systems, Massachusetts Institute of Technology (2021) Her research integrates game theory, optimization, and machine learning to address challenges in autonomous services, traffic management, and decentralized decision-making. Current investigations focus on adaptive incentive structures, spatial resource allocation, and equilibrium analysis in complex networked environments. Publication analysis reveals consistent emphasis on game-theoretic frameworks applied to urban mobility systems, with recent work exploring multi-agent reinforcement learning, congestion pricing equity, and electric fleet management. Methodological innovations include novel convergence proofs for decentralized algorithms and computational approaches to fairness constraints. Awards and Honors: Hammer Fellowship UTC Milton Pikarsky Memorial Award Siebel Scholarship EECS Rising Star recognition No information is currently available regarding student advising, research grants, or laboratory affiliations.

Lokendra Palمشاهده پروفایل

استاد

• Sustainable Materials Engineering
• Nanomaterials
• Barrier Coatings
• +۵ مورد دیگر

Dr. Lokendra Pal is the EJ Woody Rice Professor and University Faculty Scholar in Sustainable Materials/Paper Science and Engineering at NC State University's Department of Forest Biomaterials. He leads research in bio-based materials, smart manufacturing, and energy innovation, with 23+ years of global industry experience. His lab focuses on decarbonizing forest/waste industries through electrification and AI-driven smart manufacturing. He directs NC State's Paper Pilot Plant-Smart Manufacturing Center and co-founded the Tissue Pack Innovation Lab (TPIL). Education: Ph.D. in Paper and Imaging Science (Western Michigan University). Awards include NC State Faculty Scholar (2021), TAPPI Fellow (2021), and University Outstanding Teacher Award (2022). Professional roles include leadership in TAPPI, ACS, and AIChE. Research Interests: Sustainable bioproducts, nanomaterials, barrier coatings, 3D printing, smart manufacturing systems, and AI/ML integration. Current projects address waste-to-energy conversion, lignocellulose dewatering, and crop protection via biodegradable matrices. Grants: Over $10M in funding from USDA, DOE, and industry consortia for projects like AI-enabled MSW analysis, hemp valorization, and smart manufacturing platforms. Key initiatives include USDA-funded biomass conversion and DOE-backed smart manufacturing innovation. Labs/Teams: Leads the Pal Research Group and collaborates with industry partners through APPTI, CESMII, and EPICX. Active in global projects like the 'Wrap & Plant' nematode control technology for African agriculture.

Sarah Wilsonمشاهده پروفایل

دانشیار

• Trusts Law
• Financial Crime
• Charity Law
• +۹ مورد دیگر

Dr. Sarah Wilson is a Reader at the York Law School, University of York. She holds a LLB from the University of Wales, an MA in History from the University of Wales, Swansea, and a PhD in legal responses to financial crime. Her research focuses on trusts law, charity law, financial crime, banking regulation, and the historical and socio-legal dimensions of financial systems. She has previously held academic positions at the Universities of Manchester, Leeds, and Keele. Her research explores topics such as mandatory rules in trust creation, fiduciary obligations, and the regulatory aftermath of the 2007-2008 financial crisis. Notable projects include investigations into socially useful banking, the historiography of financial crime, and interdisciplinary approaches to financial crime studies. She is also engaged in collaborative projects with institutions like Nottingham Trent University and the University of Newcastle. Dr. Wilson is an Editorial Board Member of the Lloyds Law Reports (Financial Crime), a Consultant Expert for the BBC’s 'Who Do You Think You Are?', and an external examiner at Liverpool John Moores University. Her teaching spans undergraduate and postgraduate modules in trusts law, financial crime, and legal history.

Al Barrمشاهده پروفایل

استاد

• Computer Graphics
• Predictive Modeling
• Scientific Visualization
• +۵ مورد دیگر

Alan H. Barr is a Professor of Computer Science at the California Institute of Technology (Caltech), affiliated with the Division of Engineering and Applied Science and the Computation & Neural Systems (CNS) department. He is a founding member of the Caltech Computer Graphics Group and a leader in developing mathematically rigorous methods for computer graphics and predictive modeling. His research focuses on enhancing computational modeling accuracy through approaches like interval analysis and constraint-based systems. Notable contributions include deformable models, quaternion interpolation, and cellular simulation frameworks. He has advised over 20 graduate students, many of whom became industry leaders at Pixar, Microsoft Research, and academic institutions like NYU and Brown University. Awards include the ACM SIGGRAPH Achievement Award (1988) and ACM Fellow (1995). Research Interests: Predictive modeling with error bounds Scientific visualization and MRI data analysis Biophysical systems simulation (e.g., cellular organelles) Self-assembling robotic structures for space colonization Mathematically robust computer graphics techniques Key Collaborations: Caltech Biological Imaging Center (Beckman Institute) JPL (Jet Propulsion Laboratory) New computational substrates research (quantum/DNA computing) Recent Work: Expanding into computational biology, medical imaging optimization, and high-confidence systems for managing complex computational interactions. Active in interdisciplinary projects across Caltech divisions.

Muhammad Azmi UMERمشاهده پروفایل

مدرس

• Machine Learning
• Data Science
• Cyber Physical Systems
• +۳ مورد دیگر

Dr. Muhammad Azmi UMER is a Lecturer at DHA Suffa University and a Ph.D. Scholar at Karachi Institute of Economics and Technology, Pakistan. His research focuses on Machine Learning applications in Cyber Physical Systems (CPS), particularly intrusion detection in industrial control systems like the SWaT testbed. He holds a Master’s in Computer Science from Karachi Institute of Economics and Technology and a Bachelor’s from the University of Karachi. His academic work emphasizes cybersecurity challenges in smart grids, IoT healthcare systems, and adversarial machine learning techniques. Key contributions include developing decision tree-based intrusion detection frameworks and adversarial attack simulations for industrial systems. He collaborates with researchers like Dr. Jit BISWAS and Dr. Eyasu G. CHEKOLE within interdisciplinary teams. Publications span machine learning applications in smart cities, CPS security protocols, and IoT conceptual frameworks. His research bridges theoretical models with practical implementations in critical infrastructure security and urban technology systems.

Matt Bonneyمشاهده پروفایل

مدرس

• Digital Twins
• Nonlinear Structural Dynamics
• Mechanical Joint Modelling
• +۴ مورد دیگر

Dr. Matt Bonney is a Lecturer in Space Engineering at Swansea University, affiliated with the School of Aerospace, Civil, Electrical and Mechanical Engineering. He holds a position in the Department of Aerospace Engineering and is actively involved in postgraduate supervision. His research focuses on digital twin technology, nonlinear structural dynamics, mechanical joint modeling, seismic reliability, and uncertainty quantification, with recent emphasis on digital twin security and thermo-mechanical coupling in assembled structures. Dr. Bonney's expertise spans multi-physics joint modeling and multi-disciplinary development of digital twins, with international collaborations. He teaches modules such as 'Advanced Space Systems' (EG-M334) and 'Aerospace Systems' (EGA220), emphasizing space system design, orbital mechanics, and cyber-physical security. His research highlights include the development of a Python Flask-based digital twin operational platform, contextualization of information in digital twin processes, and experimental studies on frictional interfaces. His work on uncertainty quantification and seismic reliability has applications in nuclear reactor systems and civil engineering structures. Dr. Bonney currently supervises a PhD student focusing on nonlinearities in thermal-mechanical joints. His research outputs include over 30 peer-reviewed publications, with contributions to journals like Mechanical Systems and Signal Processing and Data-Centric Engineering .