جست‌وجوی استاد و پژوهشگر

• Sensor Networks
• Pervasive Computing
• Middleware
• +۵ مورد دیگر

Sanem Kabadayı is an Assistant Professor at the Department of Computer Engineering, Istanbul Technical University. Her research focuses on sensor networks, middleware frameworks, and pervasive computing. Research Interests Sensor Networks (Wireless, Ad-hoc, Heterogeneous) Pervasive and Ubiquitous Computing Middleware Design for Smart Environments Data Abstraction and Communication Paradigms Advisory Role Advisor for Yakup Kayatas' thesis on AI-assisted IoT agents for smart spaces (2025). Recent Research Trends Her 15 most recent publications (2006–2024) emphasize sensor network architectures, middleware innovations for programmable environments, and abstractions for heterogeneous sensor integration. Key themes include AI-driven IoT agents, positioning techniques in wireless networks, and virtual sensor frameworks.

Samarjit Chakrabortyمشاهده پروفایل

استاد

• Distributed Embedded Systems
• Hardware/Software Co-design
• Embedded Control Systems
• +۹ مورد دیگر

Samarjit Chakraborty is the William R. Kenan, Jr. Distinguished Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill. He previously held the Chair of Real-Time Computer Systems at the Technical University of Munich (2008–2019) and was an assistant professor at the National University of Singapore (2003–2008). His research spans real-time embedded systems, cyber-physical systems (CPS), and automotive security. Research Interests include distributed embedded systems, hardware/software co-design, low-power systems, energy storage, electromobility, and sensor network-based information processing. His work addresses challenges in scheduling algorithms for autonomous vehicles, timing predictability in automotive networks, and safety-critical controller implementations. Recent Publications highlight advancements in Timing analysis for automotive networks Energy modeling of Bluetooth Low Energy Autonomous vehicle perception computing Security in automotive systems Flexible manufacturing with process dynamics Scientific Awards include the ETH Medal, European DAAD Outstanding Doctoral Dissertation Award, multiple best paper awards at conferences (ISLPED, ICCD, RTCSA, etc.), the 2023 Humboldt Professorship, and IEEE Fellowship. Advising active PhD students: Clara Hobbs, Shengjie Xu, Sharmin Aktar, and postdoc Enrico Fraccaroli. His research is supported by NSF grants and industry partnerships with General Motors, Intel, Google, BMW, Audi, Siemens, and Bosch.

• Autonomous Industrial Vehicles
• Multi-Agent Systems
• Fuzzy Logic
• +۷ مورد دیگر

Jean-Marie Bonnin is a Researcher at IMT Atlantique , affiliated with the Network Systems, Cyber Security and Digital Law department. His work spans autonomous industrial vehicles, vehicular networks, and cooperative systems, with a focus on energy management, task allocation, and safety protocols. IMT Atlantique, Rennes Campus Research in Industry 4.0 and Smart Mobility Research Interests : Autonomous Industrial Vehicle Fleets Fuzzy Logic for Multi-Agent Systems V2X Communication Protocols Scientific Contributions include: Modeling energy consumption in extreme-edge IoT nodes Decentralized task allocation for autonomous vehicles Collision avoidance in industrial environments

Eve M. Schoolerمشاهده پروفایل

استاد مهمان

• Networking
• Distributed Systems
• Sustainable Computing
• +۷ مورد دیگر

Dr. Eve M. Schooler is a Visiting Professor of Sustainable Computing at the University of Oxford , sponsored by the Royal Academy of Engineering. She is an IEEE Fellow and co-recipient of the IEEE Internet Award (2020), with expertise in Networking , Distributed Systems , and Carbon-aware Networking . Her work bridges industry-academia partnerships, focusing on edge-cloud infrastructure and AI for cybersecurity . BS, MS, PhD in Computer Science (Yale, UCLA, Caltech) Board of Directors, Computing Research Association (US) Advisory Council, University of Delaware College of Engineering Her research spans IoT security , smart grids , reverse CDNs , and data-centric networking . She co-founded the IETF's SUSTAIN research group on sustainability and chairs standards initiatives in fog computing and open footprints. Recent trends in her publications include carbon-aware networking , edge-cloud convergence , and AI-driven cybersecurity , with over 100 papers and 35 patents. IEEE Fellow (2021) IEEE Internet Award (2020) N2Women Stars in Networking (2023) Dr. Schooler champions STEM outreach , serving organizations like Grace Hopper Conference and Sally Ride Science. She leads industry-academia collaborations through projects like EU H2020 SPATIAL and NSF-Intel ICN-WEN.

Hua Huangمشاهده پروفایل

استادیار

• Sensor Systems
• Wireless Networks
• Ubiquitous Computing
• +۲ مورد دیگر

Hua Huang is an Assistant Professor in the Department of Computer Science and Engineering at the University of California, Merced. He holds a Ph.D. in Computer Engineering from Stony Brook University (2020), an M.S. in Computer and Information Sciences from Temple University (2014), and a B.E. in Electronic and Information Engineering from Huazhong University of Science and Technology (2012). Ph.D. in Computer Engineering, 2020 — Stony Brook University, New York M.S. in Computer and Information Sciences, 2014 — Temple University, Pennsylvania B.E. in Electronic and Information Engineering, 2012 — Huazhong University of Science and Technology, Wuhan, China Hua Huang's research focuses on sensor systems, wireless networks, ubiquitous computing, and smart healthcare. His work bridges theoretical and practical challenges in mobile computing, emphasizing real-world applications like device-free intrusion detection, driving safety monitoring, and healthcare wearables. His publications span key conferences and journals such as ACM MobiCom, IEEE ICCPS, ACM Transactions on Sensor Networks, and INFOCOM, with a notable Best Paper Runner-Up award at ACM MSWiM 2018. Themes include wireless sensor optimization, deep learning applications, and mobility-aware infrastructure design. Scientific Awards Best paper runner-up at ACM MSWiM 2018 Research Collaborations Collaborated with prominent researchers like Shan Lin, Fei Miao, and Tian He Advising Seeks self-motivated students with backgrounds in wireless systems and signal processing Labs & Teams Leads a research group at UC Merced focusing on wireless and ubiquitous systems

• Electromagnetics
• Photonics
• Metamaterials
• +۳ مورد دیگر

Mohammadmahdi Asgari is a Doctoral Researcher at Aalto University's Department of Electronics and Nanoengineering. His research focuses on advanced electromagnetic and photonic materials, particularly metasurfaces , metamaterials , and photonic time crystals . His work explores applications in wireless communication enhancement, inverse topology design for multifunctional surfaces, and non-reciprocal optical phenomena. Key research themes include: Wave propagation control Spontaneous magnetization effects Space-time modulated materials Passive metacrystal systems Publications reveal a concentration on both theoretical frameworks and practical implementations in electromagnetic and optical engineering. Asgari collaborates with prominent researchers including Shanhui Fan and Viktar Asadchy.

Ahmad Lotfiمشاهده پروفایل

استاد

• Computational Intelligence
• Ambient Intelligence
• Robotics
• +۷ مورد دیگر

Ahmad Lotfi is a Professor of Computational Intelligence and Head of Department of Computer Science at Nottingham Trent University , with a Visiting Professor role at Tokyo Metropolitan University . He leads the Computational Intelligence and Applications (CIA) research group and has supervised over 30 PhD students to completion. PhD in Learning Fuzzy Systems (University of Queensland, 1995) MTech in Control Systems (Indian Institute of Technology, India) BSc in Control Systems (Isfahan University of Technology, Iran) His research spans computational intelligence , ambient intelligence , robotics , and machine learning , with applications in dementia monitoring , smart environments , and healthcare technology . Recent work focuses on using thermal sensor arrays for privacy-preserving human activity analysis. He has secured funding from Innovate UK , EPSRC , The Royal Society , and Horizon 2020 , with projects like iCarer (assistive living), SmartBerry (agricultural AI), and BigSpark (financial data augmentation). His 15 most recent articles demonstrate expertise in Wi-Fi-based activity recognition , EEG fall detection , and thermal sensor fusion . Senior Member IEEE Member of British Computer Society (MBCS) Editorial roles in Soft Computing and Journal of Ambient Intelligence and Smart Environments He has served as Program Chair for conferences like PETRA and ICCRT , and as Keynote Speaker at PETRA 2023 . His 28+ years of academic leadership include organizing UKCI and UKRAS conferences.

Mahbubur Rahmanمشاهده پروفایل

استادیار

• Internet of Things (IoT)
• Cyber-Physical Systems (CPS)
• Wireless Networks and Communication
• +۳ مورد دیگر

Mahbubur Rahman is an Assistant Professor in the Department of Computer Science at Queens College and the Graduate Center, City University of New York (CUNY). He earned his PhD in Computer Science from Wayne State University in 2020 and a BSc in Computer Science & Engineering from Bangladesh University of Engineering and Technology in 2012.

Saibal Mukhopadhyayمشاهده پروفایل

استاد

• VLSI Systems
• Nanotechnology
• Low-Power Electronics
• +۵ مورد دیگر

Dr. Saibal Mukhopadhyay is a Professor in the Department of Electrical and Computer Engineering at the Georgia Institute of Technology, where he joined in 2007. He holds the Joseph M. Pettit Professorship and is recognized as an IEEE Fellow for his contributions to low-power and reliable VLSI systems. Education: BEng (Jadavpur University, India), Ph.D. (Purdue University) Labs: Gigascale Reliable Energy Efficient Nanosystem (GREEN) Lab His research focuses on VLSI Systems , Nanotechnology , and Low-Power Electronics , with emphasis on technology-circuit co-design for energy-efficient computing. Recent work explores Compute-in-Memory (CIM) architectures and Spiking Neural Networks for edge AI. Key article themes include Transformer Model Acceleration , Quantum Computing Calibration , 3D Object Detection , and Device Aging Analysis , reflecting his interdisciplinary approach bridging hardware design and machine learning. Scientific Awards IEEE Fellow (2018) ONR Young Investigator (2012) NSF CAREER Award (2011) IBM Faculty Awards (2009, 2010) Best Paper Awards (IEEE-Nano 2003, ICCD 2004)

Fendy Santosoمشاهده پروفایل

عضو هیئت علمی

• cyber-physical systems
• cybersecurity
• artificial intelligence
• +۶ مورد دیگر

Dr. Fendy Santoso is a Visiting Fellow at UNSW Canberra's School of Engineering and Information Technology, where he conducts cutting-edge research at the intersection of cyber-physical systems, cybersecurity, and artificial intelligence. His work focuses on developing robust security mechanisms for autonomous systems, particularly UAVs and robotics operating in adversarial environments. His educational background includes a PhD in Electrical Engineering from UNSW Sydney and a Master of Engineering (Electrical and Computer Systems) from Monash University. Dr. Santoso's research interests span cyber-physical systems security, adversarial machine learning, trustworthy autonomy, and AI-driven cybersecurity for autonomous platforms. His work specifically targets penetration-resistant architectures and secure decision-making frameworks for UAVs and robotic systems operating in dynamic, threat-prone environments. His approach integrates advanced fuzzy logic systems with deep learning techniques to create resilient control mechanisms that can withstand cyberattacks and operational uncertainties. Analysis of his recent publications reveals a consistent focus on applying type-2 fuzzy systems, deep learning, and negative imaginary control theory to solve critical challenges in autonomous systems security and control. His work demonstrates strong interdisciplinary connections between cybersecurity, control theory, and artificial intelligence, with particular emphasis on real-world implementation and experimental validation. Distinguished Early Career Travel Fellowship 2019, University of Wollongong ARC Linkage Project: Robust Defenses Against Adversarial Machine Learning for UAV Systems (2023) CSIRO Next Generation Grant for AgriTwins: Bridging Cyber-Secure Emerging Technologies and Data-Centric Twin Tech for Resilient Agriculture of the Future (2024) Dr. Santoso has secured over AUD 3 million in competitive research funding from prestigious sources including the Australian Research Council, U.S. Army Ground Vehicle Systems Centre, and Defence Science and Technology Group. He leads multi-disciplinary research teams and maintains strategic partnerships with defense and government agencies to translate theoretical advances into practical cybersecurity frameworks. His laboratory work centers around the Autonomous System Laboratory at UNSW Canberra, where he conducts experimental validation of security protocols for military ground robots and UAVs under realistic cyberattack scenarios.

• Discrete-event systems
• Control theory
• Petri net modeling
• +۶ مورد دیگر

Ramavarapu S Sreenivas is a Professor in the Industrial and Enterprise Systems Engineering department at the University of Illinois at Urbana-Champaign , with research appointments at the Coordinated Science Laboratory (CSL) and the Information Trust Institute (ITI ). He holds a joint affiliation with the Electrical and Computer Engineering department and serves as the Arthur Davis Faculty Scholar since 2016. Ph.D. , Electrical and Computer Engineering, Carnegie Mellon University (1990) M.S.E.E. , Carnegie Mellon University (1987) B.Tech , Electrical Engineering, Indian Institute of Technology Madras (1985) His research focuses on Discrete-Event/Discrete-State (DEDS) systems , applying Coding Theory, Machine Learning, and Information Theory to develop near-optimal supervisory policies for applications in wireless networks, automated manufacturing, and healthcare systems . He leads the Center for Autonomous Construction and Manufacturing at Scale (CACMS) , established in 2023. Recent publications highlight advancements in liveness enforcement in Petri nets , fault-tolerant control , and IoT-based load scheduling . His work bridges theoretical rigor with practical implementations in Distributed Control, Network Coding , and Reinforcement Learning . UIUC Campus Award for Excellence in Graduate and Professional Teaching (2023) Arthur Davis Faculty Scholar (2016) Senior Member, IEEE (2002) James Franklin Sharp Outstanding Teaching Award in Industrial Engineering (2017, 2012) Sreenivas has taught graduate and undergraduate courses in Control Systems, Integer Programming, and Financial Computing since 1992. He co-instructed courses in Health Technology and contributed to the Master of Science in Financial Engineering (MSFE) program, which ranks 4th nationally.

Sirojan Tharmakulasingamمشاهده پروفایل

مدرس

• Machine Learning
• Artificial Intelligence
• Data Science
• +۶ مورد دیگر

Dr. Sirojan Tharmakulasingam serves as a Lecturer and Research and Development Coordinator at the Signals, Information & Machine Intelligence lab within the Faculty of Engineering at the University of New South Wales (UNSW) Sydney. His work bridges theoretical machine learning with practical applications in edge computing and high-performance systems. His research spans multiple cutting-edge domains including machine learning, artificial intelligence, data science, edge computing, and high-performance computing. Dr. Tharmakulasingam specializes in developing next-generation inference models by integrating machine learning, signal processing, mathematical modeling, and computing across diverse data types including images, video, audio, and quantum molecular data. His work has significant implications for scientific computing, telecommunications, and healthcare applications. Analysis of his publication trends reveals a strong focus on practical AI implementations, with increasing emphasis on edge computing solutions, quantum applications, and energy-efficient models. His recent work demonstrates progression from foundational machine learning techniques toward specialized applications in scientific computing and real-time systems. Dr. Tharmakulasingam holds a Doctor of Philosophy from UNSW Sydney and a Bachelor of Science of Engineering from the University of Moratuwa in Sri Lanka. His academic journey reflects a strong foundation in both theoretical and applied engineering principles. As Research and Development Coordinator for the Signals, Information & Machine Intelligence lab, he oversees critical research infrastructure and collaborations. His work location in Room 447 of the EE&T Building (G17) places him at the heart of UNSW's engineering research ecosystem, with access to the Mark Wainwright Analytical Centre's extensive facilities.

Chadi Jabbourمشاهده پروفایل

استاد

• Analog-to-Digital Converter Design
• Communication Systems
• Mixed-Signal Systems
• +۷ مورد دیگر

Chadi Jabbour is a Professor at Institut Polytechnique de Paris , specializing in analog/digital converter design, communication system linearization, and flexible receiver architectures. He leads the Communication Circuits and Systems (C2S) team at the Information Processing and Communication Laboratory (LTCI) in the Communications and Electronics (Comelec) department.

• Machine Learning
• Network Performance
• IoT Security
• +۳ مورد دیگر

Andreas Johnsson is an Adjunct Senior Lecturer at the Department of Information Technology , Uppsala University, Sweden. His research spans Machine Learning , Network Performance , and IoT Security in the context of 5G/6G Networks and Edge Computing . Research interests include federated learning, transfer learning, and network optimization techniques. His recent work (2024-2021) focuses on self-regulated learning models for 6G, multi-objective neural architecture search, IoT intrusion detection generalizability, and delay prediction in heterogeneous networks. He has co-authored over 15 publications in high-impact venues like IEEE Transactions on Machine Learning in Communications and Networking and IEEE NOMS . Andreas actively collaborates with researchers such as Jalil Taghia, Farnaz Moradi, and Hannes Larsson. His contributions extend to change detection algorithms, policy adaptation frameworks, and feature selection methodologies in dynamic network environments. No formal scientific awards or student advisement details are currently documented.

• Distributed computing
• Real-time computing
• Algorithms and lower bounds
• +۳ مورد دیگر

Nancy A. Lynch is the NEC Professor of Software Science and Engineering and Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology, where she heads the Theory of Distributed Systems (TDS) group within CSAIL. Research Interests Distributed computing algorithms and lower bounds Real-time and fault-tolerant systems Formal modelling and verification Wireless network algorithms Biological distributed algorithms Neural computation and spiking networks Across her work, Lynch blends rigorous theoretical analysis with practical relevance, tackling problems ranging from consensus and leader election in unreliable networks to modelling decision-making circuits in the brain. Publications & Trends Since 2020 she has published extensively on distributed algorithms , swarm robotics , neuromorphic architectures , and biologically-inspired computation . Notable recent directions include hierarchical concept learning in spiking neural networks, nanobot locomotion modelling for cancer detection, and superconducting nanowire platforms for energy-efficient neural hardware. Scientific Awards & Honors Best Paper Award, OPODIS 2018 Best Paper Award, IEEE NCA 2014 Highlight Paper, Neuromorphic Computing and Engineering 2022 Teaching & Advising Lynch teaches core graduate and undergraduate subjects at MIT including 6.042J Mathematics for Computer Science , 6.852J/18.437 Distributed Algorithms , and 6.885/6.006 Algorithms . She has supervised dozens of PhD students and post-docs whose names are listed on her Past Students page. Laboratory & Teams She leads the Theory of Distributed Systems (TDS) Group , a vibrant research team within MIT CSAIL . TDS is part of the larger Theory of Computation group and hosts weekly seminars, reading groups, and collaborative projects with partners across MIT and worldwide.