Dr. Yining Hu is a Lecturer at the School of Computer Science , University of Technology Sydney since January 2024. Her research and teaching focus on Artificial Intelligence , Blockchain , Cloud Computing , and Wearable Technology . She holds a PhD from the University of New South Wales and has collaborated with industry partners on blockchain applications for IoT security and sustainability. PhD: University of New South Wales Current role: Lecturer at UTS School of Computer Science Key research areas: Wearables, Blockchain, Cloud Computing Dr. Hu's publications demonstrate her technical expertise in blockchain-IoT integration, with notable works on secure transaction frameworks and carbon offset management. Her recent 2025 paper in Electronics explores blockchain-DNN synergy for IoT security. Earlier works cover wearables' security protocols and adaptive fitness tracking frameworks. She contributes to academic service as a member of the Editorial Board for the International Journal on Data Science and Technology (2024-2027). Her teaching portfolio includes advanced cloud computing and software development courses, with availability for Masters/PhD supervision . Current funded research includes blockchain for food traceability and a 2025-2028 LLM-driven text-to-SQL grant with Hampton Capital.
جستوجوی استاد و پژوهشگر
استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشیتان را پیدا کنید و با او ارتباط بگیرید.
نمایش ۱۰۶-۱۲۰ از ۴۷۳ استاد راهنما
اطلاعات این پروفایلها از صفحات عمومی دانشگاهها جمعآوری شده و ممکن است بهروز نباشد.
- Radio Astronomy
- Pulsars
- Neutron Stars
- +۷ مورد دیگر
James M. Cordes holds the George Feldstein Professorship in Astronomy at Cornell University, affiliated with the Department of Astronomy within the College of Arts and Sciences. He maintains dual associations with the Carl Sagan Institute and the Center for Radiophysics and Space Research (CCAPS), conducting observations across global facilities including Arecibo Observatory, the Very Large Array, Parkes Telescope, and space-based instruments like Hubble and Chandra. His research centers on pulsar astronomy as a tool for fundamental physics, with expertise in radio signal processing , interstellar medium studies , and the search for extraterrestrial intelligence . Cordes pioneers statistical inference methods for gravitational wave detection and leads development of next-generation instrumentation like Arecibo's multiple-feed receiver system, while serving as a key contributor to the international Square Kilometer Array project. Analysis of Cordes's 2008–2012 publications reveals a cohesive research program using pulsars to probe spacetime curvature near black holes, detect gravitational waves, and investigate galactic center environments. His work consistently integrates multiwavelength observations with innovative data analysis, establishing foundational methodologies for pulsar timing arrays and demonstrating how circumpulsar phenomena can reveal hidden astrophysical structures. Cordes collaborates through the Carl Sagan Institute team and major consortia including NANOGrav. His observational campaigns coordinate radio, optical, infrared, and gamma-ray facilities worldwide—from Arecibo upgrades to Hubble Space Telescope campaigns—enabling breakthrough studies of cosmic plasma environments and gravitational phenomena, as highlighted in Cornell's coverage of the 2020 gravitational wave 'hum' detection.
Angela Meyerمشاهده پروفایل
استادیار
Dr. Angela Meyer is an Assistant Professor of Energy Meteorology and Artificial Intelligence at TU Delft, Faculty of Civil Engineering and Geosciences, Department of Geoscience and Remote Sensing since October 2023. She concurrently leads the Energy Weather & AI Lab at the Bern University of Applied Sciences (BFH), School of Engineering and Computer Science. She earned her PhD in atmospheric physics from ETH Zurich (2015) and a master’s degree in mathematics from the University of Cambridge (2009). Research Focus: Intersection of data science, atmospheric science, and renewable energy applications. Machine learning for solar and wind energy forecasting. Federated learning for privacy-preserving wind turbine condition monitoring. Satellite-based solar radiation retrieval and bias correction. Probabilistic intraday and sub-seasonal forecasting. Her research is supported by major grants from the Swiss National Science Foundation (SNSF) and Innosuisse , and she is a project partner in the Horizon Europe UrbanAIR initiative. Scientific Contributions: Over 40 peer-reviewed publications since 2015 in journals such as Applied Energy , Solar Energy , Energy and AI , and Journal of Climate . Key publications include advances in deep generative models for solar forecasting, federated learning in renewable energy, and AI-based satellite retrieval of solar radiation. Active reviewer for Applied Energy , Energies , and program committee member for ECML PKDD and LOD conferences. Research Team & Supervision: Dr. Meyer currently supervises six PhD candidates and six postdoctoral researchers across her labs at TU Delft and BFH. Her group focuses on AI-driven solutions for renewable energy reliability and resilience. Laboratories & Collaborations: Energy Weather & AI Lab – Bern University of Applied Sciences. GRS Lab – TU Delft, Department of Geoscience and Remote Sensing. Active collaborations with ETH Zurich, Siemens Smart Infrastructure, Hexagon AB, and NVIDIA. For more information, visit her personal website or ResearchGate profile .
Hassen AZIZAمشاهده پروفایل
دانشیار
Hassen AZIZA is a senior Associate Professor and Head of the Memory Team (MEM) within the IM2NP research unit at Aix-Marseille University, specializing in microelectronics and emerging memory technologies. His work bridges academic research and industrial applications through collaborations with ST-Microelectronics, CEA-Leti, Thales, and international universities. He earned both his Master of Science in Electrical Engineering (MSEE) and PhD with honors from Aix-Marseille University. His educational background established the foundation for his expertise in semiconductor devices and memory systems. His research centers on Microelectronics , Emerging Memories , and Neuromorphic Computing , with specific focus on RRAM reliability, computation-in-memory architectures, and hardware security. Current projects address critical challenges in RRAM variability, fault tolerance, and energy-efficient neural network implementations using memristive crossbars. His work spans from fundamental device physics to system-level integration for IoT and biomedical applications. Analysis of his 15 most recent publications reveals dominant trends in RRAM reliability engineering (35% of articles), neuromorphic hardware implementation (30%), and sensor system development (20%). Key subfields include fault-tolerant memory design, variability-aware neural networks, and low-power IoT circuit optimization, demonstrating consistent focus on bridging device physics with practical system requirements. Best Paper Award at IEEE ETS (2021) for RRAM fault analysis CoolGames Silver Medal (2019) for high-altitude balloon project Eiffel Scholarship for PhD student (2018) Guillemin-Cauer Best Paper Award (2014) Multiple IEEE conference best paper awards (2013, 2011) SIMagine contest finalist/silver medalist (2010, 2009) He has supervised 10 PhD students (8 graduated via industry-oriented CIFRE theses), including Eiffel scholarship recipient Hussein BAZZI. His research is funded through strategic industry partnerships with ST-Microelectronics, CEA-Leti, and Thales Silicon Security, plus European initiatives like the French Tech LAB grant for the SMILE air quality monitoring startup project. Current grants focus on RRAM commercialization and neuromorphic hardware development. As leader of the Memory Team (MEM) within IM2NP's Department of Analysis and Design of Electronic Systems, he directs research on resistive memories, neuromorphic circuits, and sensor interfaces. The team maintains strong industry links through joint projects with semiconductor manufacturers and participates in international standardization efforts for emerging memory technologies.
Ruzica Piskac is a Professor of Computer Science at Yale University, where she leads the Rigorous Software Engineering (ROSE) group. She has made significant contributions to the fields of software verification, security, automated reasoning, and code synthesis, focusing on improving software reliability and trustworthiness through formal techniques. Dr. Piskac received her PhD from the Swiss Federal Institute of Technology (EPFL) in 2011, where her dissertation won the Patrick Denantes Prize. Prior to joining Yale, she led an independent research group at the Max Planck Institute for Software Systems in Germany (2012-2013). Her research spans several key areas: symbolic execution for Haskell (G2), privacy-preserving formal methods (PPFM), functional reactive synthesis, verification of configuration files, and analysis of software updates. Her work consistently bridges theoretical formal methods with practical applications in real-world systems. Dr. Piskac's recent publications demonstrate a strong trend toward applying formal verification techniques to emerging challenges including large language models, quantum computing security, legal accountability of automated systems, and cyber-physical systems. Her research increasingly intersects with AI, cryptography, and legal domains while maintaining strong foundations in formal methods. Her scientific achievements have been recognized with numerous prestigious awards: Multiple Amazon Research Awards Yale University's Ackerman Award for Teaching and Mentoring Facebook Communications and Networking Award Microsoft Research Award for the Software Engineering Innovation Foundation (SEIF) Patrick Denantes Prize for her PhD dissertation Dr. Piskac has graduated five PhD students, four of whom have gone on to become assistant professors of computer science. She has served as Program Chair of the 37th International Conference on Computer Aided Verification and is on the Steering Committee of the Formal Methods in Computer-Aided Design conference. She leads the Rigorous Software Engineering (ROSE) group at Yale, which focuses on several key projects including: Symbolic Execution Engine for Haskell (G2) Privacy Preserving Formal Methods (PPFM) Functional Reactive Synthesis Verifications for Configuration Files Analysis of Software Updates and Configuration Files
Qinglong Hanمشاهده پروفایل
دانشیار
Qinglong Han is the Pro-Vice Chancellor (Research Quality) and a Distinguished Professor at Swinburne University of Technology in Melbourne, Australia. He previously held academic and leadership roles at Griffith University and Central Queensland University. His research focuses on networked control systems, multi-agent systems, time-delay systems, smart grids, and unmanned vehicles. He is a Fellow of IEEE, IFAC, and multiple other institutions, and has received prestigious awards including the IEEE Dr.-Ing. Eugene Mittelmann Achievement Award (2024) and Norbert Wiener Award (2021). His research interests span control engineering, applied mathematics, and artificial intelligence. Notable contributions include secure platooning control for autonomous vehicles, resilient control under cyber-physical threats, and optimization of industrial systems. He leads editorial roles in journals like IEEE Transactions on Industrial Informatics and IEEE/CAA Journal of Automatica Sinica. His work emphasizes interdisciplinary applications in smart grids, robotics, and industrial automation. Dr. Han has supervised numerous PhD students in areas like networked control and vehicle dynamics. He has secured grants from ARC and NSFC for projects on networked control systems and renewable energy integration. His achievements include multiple best paper awards and recognition as a Clarivate Highly Cited Researcher in Engineering and Computer Science.
Anthony Wiskichمشاهده پروفایل
استاد مهمان
Anthony Wiskich is a Visiting Professor at the Australian National University's (ANU) Centre for Applied Macroeconomic Analysis, part of the Crawford School of Public Policy. He holds a PhD from ANU (2021) and has professional experience as a postdoctoral fellow at CSIRO, economist at the IMF, and IT consultant. His research focuses on climate policy design, decarbonisation pathways for synthetic biology and deep-sea shipping, optimal carbon pricing under climate tipping risks, and electricity market transitions. He also examines financing constraints for clean technologies and policy effectiveness evaluation. Research interests include: Decarbonisation opportunities in synthetic biology and shipping sectors Optimal carbon pricing mechanisms under climate uncertainty Clean-energy policy mix optimization Substitutability analysis between renewable and fossil fuel energy sources Financing barriers for green innovation Comparative effectiveness of climate policy instruments His recent work emphasizes: Quantifying methane vs. carbon dioxide climate impacts Evaluating ammonia fertilizer production innovations Analyzing wind/solar substitution dynamics Comparing carbon taxes vs. subsidy approaches Game-theoretic climate policy coordination Labs/Teams: Active contributor to ANU's Centre for Applied Macroeconomic Analysis research programs. Previously affiliated with CSIRO's postdoctoral program and IMF policy teams.
Mort D. Webster is Professor of Energy Engineering and Associate Department Head for Graduate Education at the John and Willie Leone Family Department of Energy and Mineral Engineering, College of Engineering, Pennsylvania State University. His research focuses on stochastic optimization and decision-making under uncertainty for energy and environmental systems, with particular expertise in electric power systems, climate impacts, and coupled multi-sector dynamics. Ph.D. in Engineering Systems, MIT (2000) M.S. in Technology and Policy, MIT (1996) B.S.E. in Computer Science and Engineering, University of Pennsylvania (1988) Webster's research program includes stochastic multi-stage optimization algorithms , electric power systems planning , coupled energy-water-land modeling , and resilience studies . He leads the Program for Coupled Human and Earth Systems (PCHES), funded by the U.S. Department of Energy, which develops integrated models for weather-related variability impacts on power systems. Recent work involves transmission expansion under uncertainty , electricity market flexibility valuation , and cross-sectoral climate impact analysis . His publications span journals in energy systems, environmental science, and operations research, with methodological innovations in scenario reduction and stochastic programming. Scientific Awards : U.S. Department of Energy Early Career Award (2010) Mentorship includes advising graduate students Jesse Bukenberger, Vijay Kumar, Brayam Valqui, and Sourabh Dalvi. His research has received funding from the National Science Foundation, U.S. Department of Energy, and General Electric Power Services Division. Collaborative efforts include partnerships with Karen Fisher-Vanden and Uday Shanbhag on coupled system resilience, and Thomas Hertel on energy-agriculture-water nexus projects.
Habiba Farrukhمشاهده پروفایل
استادیار
Habiba Farrukh is an Assistant Professor in the Department of Computer Science at the University of California, Irvine , where she directs the Security and Privacy of Emerging Computing Technology (SPECT) Lab . Her research focuses on security & privacy and mobile computing , using system design, machine learning, and human-centered approaches to address threats in emerging computing platforms. Ph.D. in Computer Science from Purdue University (advisor: Dr. Z. Berkay Celik) Research Trends : Her recent work spans XR security (UI attacks, eye gaze privacy), mobile/IoT security (magnetometer side-channels, secure group pairing), online abuse (toxic content against refugees), and wearable privacy . Publications appear at top venues like USENIX Security , IEEE S&P , and ACM CCS . Scientific Awards : Best Poster Runner-Up Award at MobiSys 2025 Outstanding Reviewer Award at VehicleSec 2024 Bilsland Dissertation Fellowship 2021-2022 Teaching : CS190: Introduction to Security & Privacy (Spring 2025) CS204: Usable Security and Privacy (Fall 204) CS295: Security and Privacy of Emerging Computing Platforms (Spring 2024)
Changhee Jungمشاهده پروفایل
دانشیار
Changhee Jung is the Samuel D. Conte Associate Professor of Computer Science at Purdue University, Department of Computer Science. His research focuses on compilers and computer architecture with an emphasis on performance, reliability, and security. He joined Purdue in Fall 2019 after serving as an Assistant Professor at Virginia Tech (2013–2019). Prior academic roles include a post at ETRI (2005–2008) and internships at Google (2010–2012). Education: PhD in Computer Science from Georgia Institute of Technology (2013) under Prof. Santosh Pande. His work spans compiler-architecture co-design for intermittent computing, nonvolatile memory systems, and security frameworks like PeX for Linux kernel permission checks. Notable recognitions include the NSF CAREER Award (2018) and induction into the MICRO Hall of Fame (2021). Research interests include energy-efficient computing, fault resilience, and compiler-driven hardware optimizations. His lab, CompArch, emphasizes cross-layer solutions for performance, reliability, and security challenges. Recent projects include IPEX (ISCA 2025), Write-Light Cache (ISCA 2023), and DevFuzz (Oakland 2023). Awards: NSF CAREER, MICRO Hall of Fame, Memorable Paper Finalist (NVMW 2024), Best Student Paper Finalist (SC 2016), and multiple industry awards. Active in service roles, including program chair for LCTES 2020 and editorial roles for ACM journals. Teaching: Courses include CS 352 (Compilers), CS 502 (Compiling Systems), and advanced special topics. Supervised over 15 graduate students and postdocs, with alumni in academia and industry (e.g., Samsung, Intel, Xilinx).
Tom Maden-Wilkinsonمشاهده پروفایل
پژوهشگر ارشد
Dr. Tom Maden-Wilkinson is a Senior Research Fellow at Sheffield Hallam University, affiliated with the School of Sport and Physical Activity and the Health Research Institute. His work bridges skeletal muscle physiology research between elite sports performance and clinical musculoskeletal health, focusing on muscle strength, function, and resilience. He collaborates with organizations such as Sheffield Teaching Hospitals, Canon Medical Systems, and the Chartered Society of Physiotherapy. His research has two key strands: Clinical Musculoskeletal Health: Promoting resistance training in older adults and those with long-term conditions (e.g., Stroke, Arthritis, Long COVID). Co-creator of the Strength4Life community program, addressing gaps in strength training for over-55s and improving practitioner knowledge. Active in national falls prevention initiatives. Elite Sport: Investigates muscle architecture, injury risk (e.g., hamstring strains), and performance optimization using imaging techniques like MRI, pQCT, and ultrasound. Collaborates with elite sports organizations such as British Cycling, Lawn Tennis Association, and the Royal Dutch Cycling Federation. Teaching includes modules on Exercise and Health, Physiology for Sports Performance, and Research Projects across undergraduate and postgraduate courses in Sport and Exercise Science. He supervises PhD students in muscle physiology, aging, and long-term conditions. Current projects include developing rehabilitation protocols for Long COVID patients and stroke survivors using Canon Medical Systems’ ultrasound technology. He also leads initiatives to improve physical activity during lockdowns and co-founded the Virtual Clinic for Long COVID in underserved communities.
Bin Zhangمشاهده پروفایل
دانشیار
Dr. Bin Zhang is an Associate Professor in the Department of Electrical Engineering at the Molinaroli College of Engineering and Computing, University of South Carolina. With over 20 years of experience in prognostics and health management, intelligent systems and control, and robotics, he has established himself as a leading researcher in battery management systems, power electronics, and fault-tolerant control systems. Dr. Zhang's educational background includes: Ph.D. in Electrical Engineering from Nanyang Technological University, Singapore M.E. in Mechanical Engineering from Nanjing University of Science and Technology, China B.E. in Mechanical Engineering from Nanjing University of Science and Technology, China His research focuses on active approaches to achieve intelligent smart systems with self-situational-awareness and self-adapting capabilities. Primary interests include prognostics and health management (PHM), which covers fault detection and isolation, failure prognosis, and fault tolerance; robotics and unmanned systems; intelligent systems and control; and dynamic systems design, modeling, simulation and control. His work integrates physics-based models with data-driven techniques and computational intelligence, including pattern recognition and machine learning. Analysis of Dr. Zhang's recent publications reveals a strong emphasis on battery modeling (particularly lithium-ion batteries), power electronics control (including fractional order delay and virtual variable sampling techniques), and deep learning methods (including graph neural networks, deep residual convolutional neural networks, and deep belief networks). His research spans multiple application domains including power grids, batteries, aircraft, helicopters, and manned/unmanned vehicles. Dr. Zhang serves as Associate Editor for prestigious journals including IEEE Transactions on Industrial Electronics, IEEE Transactions on Systems, Man, and Cybernetics: Systems, and Neurocomputing. He is a Senior Member of IEEE and a member of ASME. As director of the Resilient Systems Laboratory, Dr. Zhang advises numerous graduate students working on cutting-edge research in battery technology, power cable insulation, and control systems. His lab is equipped with advanced facilities including an 8-channel ARBIN BT-Smart battery testing system, power electronics control systems, cable/wire testing systems, rotating machinery testing systems, and unmanned vehicles including quadrotors and hexacopters.
Chris Sharpمشاهده پروفایل
دانشیار
Chris Sharp serves as Associate Professor of Mechanical Engineering at George Fox University's School of Engineering, having joined the institution as an assistant professor in 2018 and receiving promotion in 2023. His academic credentials include a PhD in Mechanical Engineering with emphasis in design and renewable energy from Oregon State University (2018), a Master's degree in Mechanical Engineering from OSU (2015), and dual Bachelor's degrees in Mechanical Engineering and Applied Mathematics from the University of New Mexico (2013). Sharp specializes in automated engineering design for ocean wave energy systems , with research centered on developing optimization algorithms for wave energy converter array configurations. His work bridges mechanical engineering design principles with sustainable renewable energy solutions, focusing on computational methods to enhance efficiency in marine energy harvesting. During his doctoral studies at Oregon State, Sharp contributed to curriculum development by co-creating and instructing the Design for Manufacturing course (2017) while serving as a graduate teaching assistant (2013-14). He maintains active community engagement as camp director for Worldview Academy, leading Christian leadership and apologetics programs for high school students during summer sessions since 2013 (with intermittent service) and continuously from 2017 onward.
Kolbjørn Engeland is a Professor at the Section for Geography and Hydrology, University of Oslo. His work focuses on hydrology, flood risk assessment, and climate change impacts on water resources, utilizing Bayesian and stochastic modeling techniques. He collaborates on international projects like 'Advancing frequency analysis of nonstationary hydrological extremes' and 'SnowSub'. Affiliation: University of Oslo, Department of Geosciences Research Groups: Hydrology and Water Resources, LATICE (Land-Atmosphere Interactions in Cold Environments) His research integrates climate science, statistical hydrology, and renewable energy planning. Key projects address flood risk reduction, snow sublimation in hydropower, and long-term hydrological variability. He has published extensively on Bayesian modeling, flood frequency, and climate-hydrology interactions. Recent publications include advancements in geostatistical runoff modeling, climate change adaptation in flood mapping, and stochastic methods in Nordic hydrology. His work spans both theoretical and applied hydrology, with applications to Norwegian and European catchments. Engeland’s advising and project leadership include collaborations with researchers in geosciences and water management, though specific student names are not listed. He contributes to sustainable hydropower analysis and climate change scenarios.
ANDREA TIGRINIمشاهده پروفایل
پژوهشگر
Andrea Tigrini serves as a Researcher in the Department of Information Engineering at Marche Polytechnic University's School of Engineering in Ancona, Italy. His scientific sector is Bioengineering (IBIO-01/A), with research spanning biomedical signal processing and human motion analysis. Dr. Tigrini's research interests focus on the intersection of biomedical engineering and machine learning, particularly in developing innovative approaches for human motion analysis through electromyography (EMG) and inertial sensing. His work emphasizes creating minimal-sensor solutions for practical applications in rehabilitation technologies, gait analysis, and assistive devices. He investigates neuromuscular control mechanisms during various activities including walking, balance maintenance, and hand gestures. Analysis of his recent publications (2023-2025) reveals a strong trend toward developing accessible diagnostic and assistive technologies using machine learning approaches. His research consistently addresses real-world challenges in diabetic neuropathy detection, prosthetic control, and rehabilitation monitoring, with particular emphasis on creating solutions that require minimal sensor setups to enhance practicality and adoption in clinical settings. His work demonstrates significant contributions to understanding the relationship between neuromuscular signals and movement patterns, with applications spanning rehabilitation engineering, human-computer interaction, and clinical diagnostics. The interdisciplinary nature of his research bridges engineering principles with physiological understanding to create practical healthcare solutions.