جست‌وجوی استاد و پژوهشگر

• Data Mining
• Machine Learning
• Information Theory
• +۴ مورد دیگر

Manabu Kobayashi is a Professor at the Center for Data Science of Waseda University, with previous faculty roles at Shonan Institute of Technology (1998-2014). His research spans data mining, machine learning, and information theory, with a focus on applications in document classification, ECOC frameworks, and latent structural models. Current Affiliation: Waseda University (2018-present) Previous: Shonan Institute of Technology (2002-2014) Research Interests: Specializes in distance metric learning, latent class modeling, and fault diagnosis systems using probabilistic frameworks. Key areas include: ECOC (Error-Correcting Output Codes) optimization Collaborative filtering for recommendation systems Reconfigurable logic circuits using DG-CNTFETs Privacy-preserving distributed linear regression Scientific Awards: PC Conference Best Paper Award (2025) World CIST'18 Best Paper Award IEICE Achievement Award (2017) 74th Information Processing Society of Japan Conference Excellence Award (2012) Article Trends: Recent work focuses on latent structure analysis for relational data (2025), ECOC performance with noisy classifiers (2023), and flipped classroom effectiveness through log-based grouping (2022-2025). Earlier contributions include reconfigurable logic circuits (2013-2014) and probabilistic fault diagnosis (2011-2012).

• Quantum Computing
• Quantum Information Theory
• Quantum Algorithms
• +۶ مورد دیگر

Seiichiro Tani is a Professor at Waseda University's Faculty of Education and Integrated Arts and Sciences since April 2024. He previously held prominent roles at NTT Communication Science Laboratories (2003-2024), including Leader of the Computing Theory Research Group and Project Manager of the Research Center for Theoretical Quantum Information. He has also served as a Visiting Professor at Tokyo Institute of Technology (2022-2024) and a researcher at JST's ERATO projects (2004-2009). His academic journey includes a Ph.D. in Computer Science from the University of Tokyo (2006), preceded by M.E. and B.E. degrees from the University of Tokyo and Kyoto University, respectively.

Nagarajan Kandasamyمشاهده پروفایل

استاد

• Computer Engineering
• Embedded Systems
• Self-Managing Systems
• +۵ مورد دیگر

Nagarajan Kandasamy is a Professor and Interim Department Head in the Department of Electrical and Computer Engineering at Drexel University. His research focuses on computer engineering, with expertise in neuromorphic computing, embedded systems, fault-tolerant architectures, and distributed systems. Prior to Drexel, he worked as a research scientist at Vanderbilt University's Institute for Software Integrated Systems. PhD, University of Michigan (2003) MS, University of Connecticut BE, Guindy Engineering College, Anna University, Chennai, India His research interests include neuromorphic computing, spiking neural networks, and reliable system design. He has contributed to fields like deformable image registration, self-testing hardware, and wireless security frameworks. Kandasamy's publications emphasize neuromorphic architectures, medical imaging algorithms, and secure communication protocols. His work often intersects hardware-software co-design and machine learning applications. National Science Foundation Early Faculty (CAREER) Award (2007) Best Paper Award, IEEE International Conference on Autonomic Computing (2006) He collaborates across disciplines in neuromorphic engineering, with grants from NSF and industry partners. His team develops tools for radiation oncology, low-power AI systems, and FPGA-based security protocols.

Myra B. Cohenمشاهده پروفایل

استاد

• Software Testing
• Search-Based Software Engineering
• Combinatorial Designs
• +۴ مورد دیگر

Myra B. Cohen is a Professor and the Lanh and Oanh Nguyen Chair in Software Engineering within the Department of Computer Science at Iowa State University's College of Engineering. She previously served as a Susan J. Rosowski Professor at the University of Nebraska-Lincoln and leads the LaVA-OPs Laboratory for Variability-Aware Assurance and Testing of Organic Programs. Her research spans software testing of highly-configurable systems, search-based software engineering, combinatorial design applications, and synergies between software engineering and synthetic biology. She investigates assurance techniques for self-adaptive systems through bio-inspired algorithms and examines software testing representations of natural processes like chemical reaction networks. Her 15 most recent publications demonstrate strong focus on cyber-physical systems (particularly drone safety), biological computing, and configuration-aware testing. These works reveal interdisciplinary trends combining software engineering with synthetic biology, emphasizing real-world applications in autonomous systems and computational biology. NSF CAREER Award AFOSR Young Investigator Award ACM Distinguished Scientist Best Student Paper Award at SPLC 2019 ACM Distinguished Paper Award at ASE 2020 Best Paper Award at GI@ICSE 2021 Professor Cohen advises PhD students Salil Purandare, Md Obaidul Kabir, and Michael Gerten, with research focusing on cyber-physical systems and biological software applications. She leads multiple significant projects including the DOE-funded Dependable, Explainable, Reusable, AI-Driven Computational Biology initiative and blockchain fault tolerance research. Her LaVA-OPs laboratory develops assurance techniques for highly-configurable and self-adaptive programs through bio-inspired algorithms.

Michał Kowalewskiمشاهده پروفایل

استادیار

• Embedded Systems
• Wireless Sensor Networks
• Metrology
• +۳ مورد دیگر

Dr. Michał Kowalewski serves as an Assistant Professor at the Department of Metrology and Electronic Systems within the Faculty of Electronics, Telecommunications and Informatics at Gdańsk University of Technology. His research bridges theoretical electronics with practical embedded systems applications, focusing on metrological solutions for industrial and sensor networks. His primary research domains include Embedded Systems (specializing in microcontroller programming with ANSI C and AVR Assembler), Wireless Sensor Networks (particularly Z-Wave protocol implementations), Metrology (evaluating accuracy, linearity, and resolution in measurement systems), and Neural Networks for Sensor Applications . He has pioneered methods for random signal generation using DACs/ADCs, developed neural classifiers for corrosion modeling, and engineered Z-Wave-based measurement systems with mesh networking capabilities. Analysis of his 2015-2018 publications reveals a consistent trajectory toward wireless distributed measurement systems, with increasing emphasis on neural network integration for fault diagnosis and sensor classification. His work demonstrates strong interdisciplinary connections between analog circuit design, wireless communication standards, and machine learning applications in industrial metrology. Dr. Kowalewski frequently collaborates with researcher Z. Czaja on projects involving noise generation and analog circuit testing, though specific grant details remain unreported. His technical contributions span both theoretical frameworks (e.g., TCBF classifiers) and practical implementations (e.g., USB Z-Wave controllers using OpenZWave library in C++).

Mark Harmanمشاهده پروفایل

استاد

• Search Based Software Engineering
• Software Testing
• Program Analysis
• +۳ مورد دیگر

Mark Harman is a part-time Professor of Software Engineering at University College London's Department of Computer Science within the Faculty of Engineering Sciences, while working full-time as a Research Scientist at Meta Platforms in the Instagram Product Performance team. He previously served as head of Software Engineering at UCL and director of its CREST centre from 2006 to 2017 before joining Meta when his startup Majicke was acquired in 2017. Harman's research spans multiple domains of software engineering, with particular emphasis on Search Based Software Engineering (SBSE), which he co-founded in 2001. His work has evolved to include LLM-based software engineering, software testing, program analysis, and bias mitigation in machine learning systems. He has made significant contributions to automated testing through systems like Sapienz and WW that have been deployed at scale at Meta. His publication record shows a clear evolution from traditional software testing and analysis toward increasingly sophisticated integration of machine learning techniques. Recent work demonstrates strong focus on addressing fairness challenges in ML systems, improving test reliability in continuous integration environments, and exploring the applications of large language models in software engineering tasks. This reflects both his ability to identify emerging challenges and his commitment to practical, industry-relevant research. IEEE Harlan Mills Award (2019) ACM Outstanding Research Award (2019) Fellowship of the Royal Academy of Engineering (2020) Harman maintains a unique bridge between academia and industry, having co-founded the Simulation-Based Testing team at Meta and previously directing UCL's CREST research centre. His work on Sapienz grew from his startup Majicke and has had significant industrial impact while maintaining strong academic foundations. He frequently participates in academic conferences as both contributor and committee member, demonstrating ongoing commitment to the research community despite his industry position. At Meta, Harman works within the Instagram Product Performance team, building on his earlier work with the Simulation-Based Testing team where he co-developed platforms for client- and server-side testing. His research on cyber-cyber digital twins represents an innovative application of simulation techniques to virtual software systems rather than physical ones.

Xavier Devroeyمشاهده پروفایل

استادیار

• Software Testing
• Search-Based Software Engineering
• Software Variability
• +۵ مورد دیگر

Xavier Devroey is an Assistant Professor of Software Engineering at the University of Namur in Belgium. He co-leads the SNAIL Team with Benoît Vanderose, focusing on innovative approaches to software testing and automation. His work bridges academic research with practical applications in the software engineering community. His educational background includes a Ph.D. and Master's in Computer Science from the University of Namur, plus a Bachelor's in Analyst Programming from Haute Ecole de Bruxelles, Belgium. This comprehensive academic training informs his research and teaching approach. Devroey's research interests center on Software Testing , with particular emphasis on Search-Based Software Engineering and Software Variability . His specific focus areas include: Search-Based Testing and Fuzzing Model-Based Testing Mutation Testing Variability Modeling Software Product Line Testing Test suite augmentation DevOps integration These interests reflect his commitment to advancing automated approaches for test case design, generation, selection, and prioritization. His recent publication portfolio (2019-2025) demonstrates consistent contributions to software testing research, with particular focus on crash reproduction, API testing, and innovative approaches to test automation. The articles reveal a strong emphasis on practical applications of search-based techniques across various testing domains. Devroey maintains active engagement with the academic community through conference participation, having served on program committees for major software engineering conferences including ASE, ICSE, ISSTA, and ICST across multiple years (2019-2025). He also contributes to educational aspects of software engineering, with publications examining testing education approaches and tools for programming exercise assessment. His personal website (xdevroey.be) and GitHub profile demonstrate his commitment to open academic practices and community engagement.

Aitor Arrietaمشاهده پروفایل

مدرس

• Software Engineering
• Software Testing
• Cyber-Physical Systems
• +۴ مورد دیگر

Dr. Aitor Arrieta is a permanent full-time Lecturer and Researcher at Mondragon University in Spain. His research focuses on software engineering and testing methodologies for complex systems including Cyber-Physical Systems, AI-based systems, and Generative AI models. He maintains strong industry collaborations with companies like Orona and Developair to address real-world engineering challenges. Research interests span: AI system validation and safety testing Metamorphic testing techniques Autonomous vehicle verification Large Language Model bias/fairness analysis Search-based software engineering His recent publications demonstrate a focus on developing automated testing tools for AI systems, particularly in safety-critical domains. Awarded Best Paper at the 15th International Symposium on Search-Based Software Engineering. Active in European research projects: InnoGuard: Generative AI for autonomous cyber-physical systems TRUST4AI: Trustable AI-driven internet search

• Geophysics
• Seismology
• 3D Earth Imaging
• +۵ مورد دیگر

Dr. Babak Hejrani is a Visiting Research Fellow at the Research School of Earth Sciences (RSES), Australian National University (ANU). He holds a PhD in Geophysics from Aarhus University (2014) and has held roles including PostDoc fellow at RSES, Visiting Researcher at ETH Zurich, and affiliations with Geoscience Australia. His research focuses on 3D Earth imaging, upper mantle tomography, earthquake source physics, and machine learning applications in seismology. Education: PhD in Geophysics, Aarhus University, Denmark (2014) MSc in Geophysics, University of Tehran, Iran (2010) BSc in Pure Mathematics, University of Kurdistan, Iran (2007) Research interests include probabilistic Bayesian inversion for earthquake source complexity, seismic tomography, and structural tectonics. Recent work addresses fault rupture dynamics, volcanic eruption modeling, and improving tsunami warning systems via W-phase data analysis. He supervises projects on megathrust rupture processes and seismic moment tensor inversion. Publications span geophysical journal articles and conference abstracts, emphasizing 3D seismic wave modeling and lithospheric structure analysis. Collaborations include AusArray continental-scale seismic projects and development of high-performance computational tools like HiPerSeis. His research contributes to understanding deep earthquakes, subduction zone processes, and integrating machine learning (CNN-based seismic arrival classification) into seismological workflows.

Richard Smithمشاهده پروفایل

استاد

• Geophysics
• Exploration Geophysics
• Mineral Exploration
• +۳ مورد دیگر

Richard Smith is a Professor of Geophysics and Industrial Research Chair in Exploration Geophysics at Laurentian University's Harquail School of Mining and Mineral Resources in Sudbury, Ontario. He holds a BSc and MSc from the University of Adelaide, Australia, and an MSc and PhD from the University of Toronto. His career includes roles at Geoterrex Ltd and Fugro, focusing on airborne geophysical methods, and an ARC post-doctoral fellowship at Macquarie University. His research emphasizes aeromagnetic and electromagnetic data processing, crustal structure analysis, and mineral exploration techniques. Notable projects include studies in the Abitibi greenstone belt, the Matheson area, and the Iraq Southern Desert. He has developed methodologies for conductivity depth sections, gravity modeling, and machine learning applications in geophysical interpretation. Awards: Best Paper in Geophysics (1997) Best Paper in Exploration and Mining Geology (2012) CSEG Distinguished Lecturer (2009/2010) Dr. Smith is affiliated with professional organizations such as SEG, EAGE, and PDAC. His teaching includes courses like Exploration Geophysics and Mineral Exploration Geophysics. He leads research initiatives like the Metal Earth project, integrating geophysical methods to advance mineral exploration knowledge.

Athula Dayanart Rajapakseمشاهده پروفایل

استاد

• Power Systems Protection
• Renewable Energy Integration
• HVDC Grid Protection
• +۳ مورد دیگر

Dr. Athula Rajapakse is a Professor in the Department of Electrical and Computer Engineering at the Price Faculty of Engineering, University of Manitoba, Canada. He leads the Intelligent Power Grid Laboratory and holds Fellow status with Engineers Canada, alongside senior membership in IEEE. His research addresses critical challenges in modern power systems, particularly renewable energy integration and grid resilience. His academic foundation includes: B.Sc. (Eng) First Class Honours in Electrical Engineering from the University of Moratuwa, Sri Lanka (1990) M.Eng. in Energy Technology from the Asian Institute of Technology, Bangkok, Thailand (1993) Ph.D. in Quantum Engineering and Systems Science from the University of Tokyo, Japan (1998) Dr. Rajapakse's research centers on power system protection in evolving grid environments, with specialized expertise in transient-based protection schemes , HVDC grid security , and machine learning applications for fault detection. His work bridges theoretical innovation and industry implementation through synchrophasor technology and wide-area monitoring systems, addressing vulnerabilities introduced by inverter-based renewable resources. Analysis of his 2023-2025 publications reveals three dominant thrusts: (1) Machine learning-driven voltage stability prediction using real-time monitoring, (2) Novel protection architectures for HVDC grids and microgrids requiring sub-cycle fault clearance, and (3) Standardized electro-thermal designs for scalable DC circuit breakers in medium-voltage networks. These reflect the industry's urgent need for adaptive protection in grids with high renewable penetration. His recognition includes: Fellow of Engineers, Canada Dr. Rajapakse serves as Associate Editor for the International Journal of Electric Power and Energy Systems (Elsevier) and Technology and Economics of Smart Grids and Sustainable Energy (Springer), while convening the Cigre/IEEE Joint Working Group C4/C2.62 on synchrophasor applications. Though not accepting new graduate students currently, his editorial leadership and working group contributions significantly shape power systems protection standards. His research has secured industry partnerships focused on real-world grid modernization. The Intelligent Power Grid Laboratory under his direction develops hardware-in-the-loop validation platforms for protection schemes, collaborating with Manitoba Hydro and international grid operators to test solutions for renewable-rich systems and remote microgrids.

Alessandro Baldiniمشاهده پروفایل

پژوهشگر ارشد

• Nonlinear Control
• Fault Tolerant Control
• Unmanned Vehicles
• +۳ مورد دیگر

Alessandro Baldini is a Research Fellow and Ph.D. Student at the Department of Information Engineering (DII), Polytechnic University of Marche. His research focuses on nonlinear control, disturbance observers, and fault-tolerant control systems applied to unmanned vehicles like multirotors and remotely operated vehicles (ROVs). He holds a Computer and Automation Engineering degree from the same university (2016). Research interests include: Nonlinear control theory and observer design Fault detection/isolation for actuator failures Fault-tolerant architectures for UAVs/ROVs Disturbance observer-based control (DOBC) methodologies Real-time fault diagnosis and adaptive control strategies Recent work emphasizes real-time fault detection via vibration analysis (UAV-FD dataset), fault-tolerant control for tilted hexarotors, and disturbance compensation in ROVs. These contributions address critical challenges in autonomous systems' reliability and safety. Publications span 20+ peer-reviewed articles since 2016, with a strong focus on: Actuator fault mitigation strategies Multirotor dynamics under battery degradation Hybrid observer-based control architectures Experimental validation of fault-tolerant systems Current affiliations include the DII's robotics control group, collaborating on projects involving: Experimental testing facilities for UAV/ROV prototypes Partnerships with industry for fault-tolerant systems development

Keith Edgar Brownمشاهده پروفایل

دانشیار

• Underwater Acoustics
• Bio-inspired Sonar Systems
• Autonomous Underwater Vehicles
• +۵ مورد دیگر

Keith Edgar Brown is an Associate Professor at Heriot-Watt University, affiliated with the School of Engineering & Physical Sciences and the Institute of Sensors, Signals & Systems. He also serves as Head of the Discipline of Electrical, Electronic and Computer Engineering. He holds a BSc (1984) and PhD (1988) in Electronic and Electrical Engineering from the University of Edinburgh, where his doctoral research focused on knowledge-based fault diagnosis in microwave radio relay equipment. His research centers on underwater acoustics, bio-inspired sonar systems, and intelligent diagnostics for complex systems, with applications in autonomous underwater vehicles and subsea infrastructure monitoring. His work contributes to UN Sustainable Development Goals related to ocean health and sustainable energy systems. Research interests include: Underwater acoustics and bio-inspired sonar design Condition-based monitoring of subsea power cables using machine learning Autonomous systems operation in hostile environments Acoustic signal processing and source localization Recent publications emphasize machine learning-driven solutions for underwater asset management, with notable contributions to IEEE journals and conferences. His work has been recognized through awards like the 2018 'Telling tails of Public engagement' prize. Brown collaborates extensively on projects involving subsea infrastructure diagnostics and robotics applications.

Hani Ragab Hassenمشاهده پروفایل

دانشیار

• Cybersecurity
• Deep Learning Applications
• Natural Language Processing (NLP) in Cybersecurity
• +۷ مورد دیگر

Hani Ragab Hassen is an Associate Professor leading the Cybersecurity with AI Research Group at the School of Mathematical & Computer Sciences, Heriot-Watt University. He specializes in cybersecurity, particularly in applying machine learning and NLP to address challenges such as malware analysis, intrusion detection, and access control systems. His roles include Associate Director of PGR Studies, Academic Integrity Officer, and former leadership in Learning & Teaching and Research programs. Research interests focus on cybersecurity fundamentals, including deep learning for malware detection, NLP-driven vulnerability assessment, and P2P systems. He has supervised numerous PhD students, currently advising three candidates on airport cybersecurity, NLP-based vulnerability detection, and network intrusion systems. His work contributes to UN Sustainable Development Goals related to innovation and infrastructure security. Publications span malware detection frameworks (e.g., ActDroid, Droiddissector), network security tools (NTFA), and machine learning optimization (D2TS). He has developed datasets like SI22 for DDoS analysis and contributed to open-source tools. His research emphasizes practical applications of AI in securing networks and cloud environments. Notable contributions include advancing Android malware detection via control flow graphs and text analysis, and pioneering cloud security protocols like Stick for social platforms. His interdisciplinary work bridges cybersecurity with machine learning and data science, addressing real-world threats through innovative solutions.

James Nabityمشاهده پروفایل

دانشیار

• Environmental Engineering
• Aerospace Engineering
• Space Systems Design
• +۳ مورد دیگر

James Nabity is an Associate Professor and Associate Chair for Undergraduate Operations at the University of Colorado's College of Engineering and Applied Science, affiliated with BIOSERVE Space Technologies. His research focuses on Environmental Control & Life Support Systems (ECLSS), space habitat design, propulsion, and power systems for human spaceflight. He earned a Ph.D. in Mechanical Engineering from the University of Colorado (2007), an M.S. in Aeronautics & Astronautics from the Naval Postgraduate School (1989), and a B.S. in Mechanical Engineering from the University of Nebraska (1983). Professional experience includes roles as Principal Engineer at TDA Research (2007-2013) and Mechanical Engineer at the Naval Air Warfare Center Weapons Division (1983-1999). His work emphasizes advanced materials, thermal systems, and bioregenerative life support solutions. Research interests span CO2 capture technologies, ionic liquid membranes, and thermal control architectures. Notable achievements include the 2017 Outstanding Faculty Advisor Award and selection as a NASA astronaut candidate in 2009. His contributions bridge academic research with practical aerospace engineering challenges. Publications highlight innovations in ECLSS design, space habitat systems, and propulsion architectures for Mars missions. Labs/teams include BIOSERVE’s collaborative initiatives in space biotechnology and environmental control systems.