جست‌وجوی استاد و پژوهشگر

Suprakash Dattaمشاهده پروفایل

دانشیار

• Bioinformatics
• Computer Networks
• Parallel and Distributed Computation
• +۷ مورد دیگر

Suprakash Datta is an Associate Professor and Associate Dean Academic and Students at the Lassonde School of Engineering , York University , specializing in Electrical Engineering & Computer Science . His research spans Bioinformatics , Computer Networks , and Parallel & Distributed Computation . Contact: datta@eecs.yorku.ca Location: CSEB 3043, 4700 Keele Street, Toronto, ON M3J 1P3 Education B.Tech (E&ECE), IIT Kharagpur, India M.Tech (CSE), IIT Kharagpur, India Ph.D. (CS), University of Massachusetts at Amherst, USA Research Interests Dr. Datta's work focuses on communication networks and bioinformatics . He investigates mathematical models for packet-dropping networks, sensor network routing algorithms for realistic battery models, and genomic signal processing techniques for DNA sequence analysis. His recent projects include: Wireless Sensor Networks : Energy-efficient routing, MAC protocols, and hardware implementation challenges. Genomic Signal Processing : Deterministic algorithms for gene prediction, clustering microarray data, and modeling email virus spread. Network Algorithms : Competitive analysis of TCP, active queue management, and multicast tree inference. Recent Publication Trends Over the last decade, his publications have emphasized vehicular networks , evolved features for DNA classification , and connectivity-based positioning algorithms . Key themes include energy efficiency , localization in mobile networks , and theoretical bounds for network protocols . Students & Teaching Dr. Datta has supervised numerous M.Sc. and Ph.D. students in topics like wireless sensor routing and genomic algorithms. He teaches courses including CSE 2001 and has served as ACM programming contest coach.

• Acoustic Metamaterials
• Vibration Control
• Non-destructive Evaluation
• +۲ مورد دیگر

Christopher Sugino is an Assistant Professor in the Department of Mechanical Engineering at Stevens Institute of Technology's Charles V. Schaefer, Jr. School of Engineering and Science. He holds a PhD from Georgia Institute of Technology and a BS from Harvey Mudd College. His research focuses on controlling sound and vibration using metamaterials for aerospace structures, non-destructive evaluation, and biomedical ultrasound. This work integrates active components, feedback circuitry, and electrical networks to manipulate elastic and acoustic waves. Research publications demonstrate strong emphasis on programmable metamaterials, piezoelectric systems, and non-reciprocal wave phenomena with applications spanning aerospace, healthcare diagnostics, and energy transfer. Awards include the 2024 ASME SMASIS Best Paper Award, 2021 Doak Award, and 2020 Sigma Xi Best Ph.D. Thesis. He serves on ASME technical committees and organizes symposia for major conferences. Funded projects include an NSF CAREER award for developing next-generation non-reciprocal acoustic devices using non-local metamaterials.

• Signal Processing
• Machine Learning
• Compressive Sensing
• +۲ مورد دیگر

Hongbin Li holds the Charles and Rosanna Batchelor Memorial Chair Professorship in the Department of Electrical and Computer Engineering at Stevens Institute of Technology's Charles V. Schaefer, Jr. School of Engineering and Science. Education includes PhD in Electrical Engineering from University of Florida (1999). Research focuses on: Advanced signal processing algorithms Machine learning for RF systems Compressive sensing methodologies Wireless communications architectures Radar and sensor network technologies Recent publications concentrate on automotive radar systems, physical-layer authentication, sub-Nyquist sampling techniques, and intelligent reflecting surface applications. Honors include IEEE Fellow, Provost's Award for Research Excellence, IEEE Jack Neubauer Memorial Award, and fellowships in AAIA and AIIA. His research is funded by DARPA, NSF, ONR, AFOSR, ARO, and other agencies.

Jihoon Ryooمشاهده پروفایل

دانشیار

• Wireless Networking
• Mobile Computing
• Internet of Things
• +۷ مورد دیگر

Jihoon Ryoo is an Associate Professor in the Department of Computer Science at SUNY Korea, where he has been employed since 2017. He directs the AI2S Lab and co-founded the startup IDCITI. He holds a Ph.D. from Stony Brook University (2017) and M.S./B.S. degrees from Korea University. Research Interests: Dr. Ryoo's work focuses on practical implementations in wireless networking and mobile systems, including backscatter communication, IoT connectivity, saliency-based video streaming, and GNSS-independent localization. His projects span uGPS (metro localization), SALI360 (360° video optimization), and autonomous anti-drone systems, often leveraging deep learning and RF analytics. Awards & Grants: Incheon City Mayor Award (Entrepreneur, 2024 & S/W Hackathon, 2020) Prime Minister Awards (ICT Colloquium & Applied Data Competition, 2020) IITP Excellence Research Award (2019) Grants: National XR-Lab initiatives (MSIT), Incheon-RISE program (2025–2030), NRF streaming platform research, and multiple Incheon Techno Park projects. Teaching & Service: Courses include Computer Networks, Computer Vision, Algorithms, and Wireless Networks. Service includes TPC roles (MobiSys, ICCCN), Director of SUNY Korea's ICT CCP Program (2018–2020), and XR-Lab Director (2021–2023).

• Embedded Sensors
• Sensor Networks
• Distributed Systems
• +۳ مورد دیگر

Bruno Rodrigues is an Assistant Professor of Computer Science (Embedded Sensing Systems) at the University of St. Gallen (HSG). His research focuses on embedded sensors, sensor networks, distributed systems, and network security, with additional expertise in software-defined networks and distributed ledgers. He holds a PhD from the University of Zurich (2020), a Master's from the Polytechnic School of the University of São Paulo (2016), and a Bachelor's from the University of Santa Catarina, Brazil (2013). Prof. Rodrigues' professional career includes roles as a Senior Researcher (2020–2024) and Junior Researcher (2016–2020) at the University of Zurich, where he contributed to projects like the EU-funded CONCORDIA H2020 and collaborations with Swiss innovation agencies (KTI/Innosuisse). His work spans DDoS mitigation, blockchain applications in voting systems, and energy-efficient cloud networks. Notable projects include the 'Passive Wireless Intelligence Tracking System (PasWITS)' and 'Energy-Efficiency to Clouds (E2C)' with Ericsson Research. His research portfolio includes over 50 publications on topics such as secure IoT frameworks (SHIFT, WeTrace), blockchain-based voting systems (ProvotuMN, Æternum), and cybersecurity tools like SecGrid for traffic analysis. He has pioneered solutions for privacy-preserving mobile tracking (LaFlector), real-time medical device inventory systems (PMD-Track), and decentralized financial inclusion tools (AfriBit). Prof. Rodrigues' work bridges theoretical computer science with practical applications, emphasizing sustainability, security, and innovation in distributed systems. He has led interdisciplinary projects at the intersection of blockchain technology, sensor networks, and ethical AI, with a focus on real-world implementation challenges.

Thomas Fevensمشاهده پروفایل

استاد

• Deep Learning
• Medical Image Processing
• Computer-Aided Medical Diagnosis
• +۵ مورد دیگر

Thomas G. Fevens is a Professor in the Department of Computer Science and Software Engineering at Concordia University, and an Adjunct Professor in the Department of Surgery at McGill University. He holds a PhD in Computing and Information Science from Queen's University (1999), with prior degrees in Astrophysics and Physics. His research focuses on medical imaging applications of deep learning, computational geometry, and surgical software innovation. Notable work includes computer-aided diagnosis systems for breast cancer using cytological images, 3D surgical planning algorithms, and motion tracking frameworks for ACL injury assessment. Education: PhD in Computing and Information Science, Queen's University (1999) MSc in Computing and Information Science, Queen's University (1994) MSc in Physics (General Relativity), Queen's University (1993) BSc in Astrophysics (Honours), Queen's University (1990) Research emphasizes interdisciplinary applications of AI in healthcare, including: Medical image segmentation using U-Net architectures Deep learning for tumor localization Kinect-based motion analysis systems Generative adversarial networks (GANs) for medical imaging Publications demonstrate contributions to both core computer science (mobile ad hoc networks, computational geometry) and clinical applications (surgical planning, cancer diagnosis). Active in industry collaboration through the ML-MVP lab, focusing on translating AI research into clinical tools.

Joel M. Bachمشاهده پروفایل

دانشیار

• Adaptive sports equipment design
• Rehabilitation Engineering
• Medical device design
• +۵ مورد دیگر

Joel M. Bach serves as a Teaching Associate Professor within the Department of Mechanical Engineering at the Colorado School of Mines. Transitioning to a half-time teaching position in Fall 2022, his professional activities center on advancing the Human Centered Design Studio (HCDS) and establishing a Public Benefit Corporation to commercialize student-developed assistive technologies. His academic foundation includes: Ph.D. in Biomedical Engineering from the University of California, Davis B.S. in Aerospace Engineering from the State University of New York at Buffalo Bach's scholarly work historically focused on human-centered engineering applications: Adaptive sports equipment design for enhanced athletic participation Rehabilitation engineering solutions for improved mobility Medical device innovation targeting clinical challenges Computer-assisted surgical techniques development Musculoskeletal, orthopaedic, occupational, and sports biomechanics analysis Examination of his recent publication record (2015-2022) reveals continued biomechanics research with particular emphasis on orthopaedic mechanics and carpal tunnel pressure dynamics, alongside growing contributions to engineering education methodology and capstone design program development. Current initiatives prominently feature the Human Centered Design Studio (HCDS), which functions as both an educational platform for student innovation and a pipeline for commercializing assistive technologies through an emerging Public Benefit Corporation structure.

Conor Brennanمشاهده پروفایل

دانشیار

• Wave Propagation Modelling
• Computational Electromagnetics
• Rough Surface Scattering
• +۵ مورد دیگر

Affiliations & Roles Dr. Conor Brennan is an Associate Professor in the School of Electronic Engineering at Dublin City University. His roles include academic leadership, research supervision, and teaching in propagation modeling, RF simulation, and computational methods. He is affiliated with the Stokes and FutureTech buildings and collaborates internationally, including with Wuhan University for joint Master's programs. Research Interests His work focuses on wave propagation modeling across rural, urban, and indoor environments, emphasizing computational electromagnetics, rough surface scattering, and metamaterial design. Innovations include full-wave models using integral equations and acceleration techniques like the Fast Far Field Algorithm (FAFFA) and Improved Tabulated Interaction Method (I-TIM). Urban studies involve vehicular channels and millimeter-wave systems, while indoor research explores volume integral equation methods and seamless localization (SEAMLOC). Teaching Brennan teaches advanced modules such as Propagation and Channel Modelling , , and engineering mathematics courses. His pedagogical contributions include developing technology-enhanced assessments (TeRMEd) and the UniDoodle student response system. Grants & Collaborations Research is supported by grants in wireless communication, sensor networks, and metamaterials. Collaborations span academia and industry, with notable projects in vegetation THz propagation, plant monitoring nanosensors, and curriculum design for telecommunication engineering. Labs & Teams He leads a dynamic team including graduates (e.g., Patrick Bradley, Marie Mullen) and current researchers (Vinh Pham, Ian Kavanagh). The group utilizes advanced simulation tools and experimental setups for propagation analysis, localization, and materials testing.

Jinbo Biمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine learning
• Data mining
• +۷ مورد دیگر

Jinbo Bi is the Frederick H. Leonhardt Professor of Computer Science and Associate Head in the Department of Computer Science & Engineering at the University of Connecticut's School of Engineering. He holds additional affiliations with the Department of Community Medicine and Health Care at UConn Health Center, Department of Mathematics, Department of Statistics in the College of Liberal Arts and Sciences, and the Department of Biomedical Engineering. Bi earned his Ph.D. from Rensselaer Polytechnic Institute and M.Sc. from Beijing Institute of Technology. His research spans artificial intelligence, machine learning, data mining, pattern recognition, computer vision, bioinformatics, medical informatics, and drug discovery. He directs two laboratories: the Laboratory of Machine Learning & Health Informatics and the Laboratory of Artificial Intelligence & Drug Discovery. His recent publications demonstrate a strong focus on applying machine learning to healthcare challenges, particularly in mental health monitoring through smartphone data, depression prediction, substance use disorder analysis, and drug discovery. His work combines theoretical advances in AI with practical healthcare applications, showing particular strength in multi-view learning, graph neural networks, and optimization techniques. Bi has received recognition including a best paper award at BIBM 2014 workshop and two highly accessed articles in BMC Genomics and BMC Genetics. His research is supported by numerous grants from NSF, NIH, VA, and industry partners including Travelers Insurance and Pfizer. As an educator, Bi teaches advanced courses in machine learning and reinforcement learning. His laboratory currently has multiple postdoctoral fellowship openings, reflecting his active research program and mentorship of numerous students who appear as co-authors on his publications.

Hossein Pedramمشاهده پروفایل

استادیار

• Computer Networking
• Computer Architecture
• Distributed Systems
• +۴ مورد دیگر

Hossein Pedram is an Assistant Professor in the Department of Electrical and Computer Engineering at The University of Texas at Dallas (UTD), affiliated with the Erik Jonsson School of Engineering and Computer Science. His research focuses on computer networking, computer architecture, and distributed systems, with contributions to IoT, fog computing, and energy-efficient resource management. Pedram holds a PhD in Computer Engineering from Washington State University. He leads research initiatives in emerging areas such as fog-based IoT optimization and bioleaching applications of microbial systems. Education : PhD in Computer Engineering, Washington State University Research Interests : Pedram’s work bridges theoretical computer science and practical system design. Key areas include: - Computer Networking : IoT protocols, fog computing architectures, and energy-efficient resource allocation. - Computer Architecture : Fault-tolerant systems, error-correcting codes, and synchronization techniques. - Distributed Systems : Multi-cloud workflow scheduling, grid service composition, and wireless sensor networks. Research Trends : His publications reflect a strong focus on network optimization (e.g., fog-based task offloading) and interdisciplinary work in bioleaching (using microbial strains for industrial waste remediation). Recent work emphasizes real-time systems and cybersecurity in distributed environments. Awards : No specific awards listed in available materials. Advising & Grants : Several faculty positions are open in Pedram’s department, offering opportunities to collaborate on nascent research directions. Specific grant-funded projects or student advisees are not detailed in the provided data. Labs & Teams : Pedram maintains an active research website outlining current projects, though no specific lab names or team structures are documented here.

Brian Ricksمشاهده پروفایل

استادیار

• Network Security
• Wireless Networking
• Bayesian Networks
• +۳ مورد دیگر

Brian Ricks is an Assistant Professor of Instruction in the Computer Science Department at the University of Texas at Dallas (UTD). His academic journey includes a PhD, MS, and BS from UTD, specializing in wireless networking, network security, and Bayesian networks. He was advised by Bhavani Thuraisingham, Sriraam Natarajan, and Patrick Tague during his doctoral studies. Previously, he contributed to the MEWS research group at Carnegie Mellon University: Silicon Valley (CMU-SV), focusing on network simulation and security solutions. Education: PhD in Computer Science, University of Texas at Dallas MS in Computer Science, University of Texas at Dallas BS in Computer Science, University of Texas at Dallas His research interests span network security, Bayesian networks, and cybersecurity. He has pioneered work on network anomaly detection, DDoS mitigation, and probabilistic fault diagnosis in hybrid systems. His publications reflect a focus on practical solutions for real-world network challenges, including data generation, concurrency analysis, and attack isolation. Research Trends: Brian’s work emphasizes integrating probabilistic methods with network security, such as leveraging Bayesian networks for fault diagnosis and developing cost-effective network data generation techniques. His recent publications highlight advancements in detecting underlying anomalies during DDoS attacks and simulating realistic network scenarios. Awards: Best Paper Award at IEEE Intelligence and Security Informatics (ISI), 2018 Best Paper Award at IEEE Intl Conference on Information Reuse and Integration for Data Science (IRI), 2018 Grants & Advising: While no specific grants are listed, his research contributions suggest active engagement in funded projects. He advises students through his teaching and mentorship roles. Labs & Teams: 曾参与MEWS research group at CMU-SV, focusing on network simulation and security. His collaborations span academia and industry, reflecting a commitment to bridging theoretical research with practical applications.

Longfei Shangguanمشاهده پروفایل

استادیار

• Mobile and wireless systems
• IoT systems
• Edge computing
• +۵ مورد دیگر

Longfei Shangguan is an Assistant Professor in the Department of Computer Science at the University of Pittsburgh's School of Computing and Information. He leads the Pittsburgh Experimental Research Group (PERG), focusing on hardware/software systems to advance computing, sensing, and communication in sensor/wireless technologies. Previously, he was a postdoc at Princeton and a senior researcher at Microsoft. He holds a PhD from HKUST (2015) under Professors Yunhao Liu and Ke Yi. Research Interests: Mobile/wireless systems, IoT, edge computing, and hardware/software co-design for sensor networks. Key areas include novel IoT applications, low-power hardware, and wireless protocol optimization. Key Projects Sensor-in-the-loop AI agents leveraging multimodal sensors Human-centric sensing using acoustic/vision modalities Wireless Digital Twin via neural ray tracing Professional Contributions Editor: IEEE Pervasive Computing, ACM GetMobile PC Member for top conferences including MobiCom, NSDI, SenSys Organized Dagstuhl Seminar on IoT Wireless Scenarios Awards NSF CAREER Award (2024) Google Research Scholar Award (2023) Best Paper Awards at MobiCom 2024 and MobiCom 2021 Advising & Grants Supervises 5 PhD students, 3 MS students, and undergraduate researchers Recipient of MassAITC Pilot Award (2025), NSF CAREER (2024) Labs/Teams: PERG lab focuses on experimental systems research with hands-on prototyping.

Benedikt Jahnelمشاهده پروفایل

استاد

• Statistical Mechanics
• Stochastic Geometry
• Spatial Epidemiology
• +۳ مورد دیگر

Prof. Dr. Benedikt Jahnel is a Professor at the Institute of Mathematical Stochastics, Carl Friedrich Gauss Faculty, Technical University of Braunschweig, and Head of the Leibniz Junior Research Group on Probabilistic Methods for Dynamic Communication Networks. His research focuses on the modeling and analysis of spatially embedded systems with interacting random components, with applications in physics, epidemiology, and telecommunications. Education: PhD in Organismic and Evolutionary Biology from Ruhr University Bochum (2011), Diploma from Technical University of Berlin. Research interests: Uses tools from statistical mechanics and stochastic geometry to study phase transitions, percolation theory, and spatial random processes. Current projects investigate continuum percolation, interacting particle systems, and probabilistic methods for communication networks. Recent publications demonstrate strong emphasis on spatial stochastic processes and percolation theory, with applications to network connectivity and epidemic modeling. Trends include mathematical analysis of phase transitions in random environments and dynamics of communication networks. Scientific awards include leadership of Leibniz Junior Research Group, EURANDOM Ambassador appointment, and election to the board of the Probability and Statistics Group of the German Mathematical Society. Leads a research team including 3 postdocs and 3 predoctoral researchers. Current projects funded by DFG, ERC, and Math+ Cluster of Excellence. Heads the DYCOMNET research group at Weierstrass Institute Berlin, focusing on dynamic spatial random systems.

AbdelRahman Abdouمشاهده پروفایل

دانشیار

• Internet Security
• Network Measurements
• SSL/TLS Protocols
• +۲ مورد دیگر

Dr. AbdelRahman Abdou is an Associate Professor at Carleton University's School of Computer Science and co-director of the Carleton Internet Security Lab (CISL). Previously a senior research scientist at ETH Zurich, his research focuses on Internet security including SDN security, TLS/PKI, DNS security, and secure geolocation. Research interests include Internet measurements, SSL/TLS protocols, authentication systems, secure BGP, and software-defined network security. Recent publications examine vulnerability management, accessibility in cybersecurity, and trust models. Distinguished Paper Award (ACM AsiaCCS 2017) Best Paper Nominee (IEEE CNS 2014) He teaches courses including Operating Systems, Computer Networks, and Internet Measurements. As CISL co-director, he supervises graduate students researching network security and internet measurements.

Muhammad Ismailمشاهده پروفایل

دانشیار

• Cyber-physical Security
• Quantum Networks and Security
• AI-assisted Cybersecurity
• +۹ مورد دیگر

Muhammad Ismail is an Associate Professor and Director of the Cybersecurity Education, Research, and Outreach Center (CEROC) at the Computer Science Department of Tennessee Tech University's Faculty of Engineering. He has over 12 years of experience from institutions like Texas A&M University at Qatar, University of Waterloo, and Ain Shams University. His research focuses on cyber-physical security , quantum networks , AI-assisted cybersecurity , smart grids , blockchain , and machine learning . He leads projects integrating graph neural networks and quantum cryptography for resilient infrastructure. Recent publications analyze 6G IoT resource allocation , FDIA detection in smart grids , LiFi authentication , and blockchain for energy systems , reflecting his interdisciplinary approach. Best paper awards at IEEE ICC 2014, IEEE Globecom 2014, SGRE 2015/2024, Green 2016 IEEE TCGCN best paper at IEEE ICC 2019 IEEE Intelligent Systems 2020 award He teaches undergraduate and graduate courses and serves as Associate Editor for IEEE IoT Journal, IEEE Transactions on Vehicular Technology, and others. He contributes to IEEE flagship conferences as TPC member and reviewer. The CEROC under his leadership develops hands-on cybersecurity programs, including a 2024 quantum network initiative in Tennessee.