جست‌وجوی استاد و پژوهشگر

Brooke Foucault Wellesمشاهده پروفایل

استاد

• Network Science
• Social Networks
• Computational Social Science
• +۷ مورد دیگر

Brooke Foucault Welles is a Professor in the College of Arts, Media and Design at Northeastern University, where she also serves as Interim Dean and Director of the Network Science PhD program. Her research focuses on how social networks and communication technologies shape power dynamics, particularly in contexts of marginalization and social justice. PhD in Media, Technology and Society from Northwestern University MS and BS in Communication from Cornell University Her research spans multiple domains including: Network science of AI and social systems Digital activism and social movement dynamics Health information and (mis)information flows Open source community structures Race/ethnicity in digital contexts Computational social science methodologies Recent publications focus on attention dynamics in social networks, hate speech protection mechanisms, and open-source software sustainability. Her work has been supported by grants from the NSF, NULab, and Chan Zuckerberg Initiative. Awards include: McGannon Book Award (2021) for #HashtagActivism Best Paper Honorable Mention at CSCW 2019 She leads the Communication Media and Marginalization Lab (CoMM Lab) which includes PhD students and postdocs from diverse disciplines. Her advising approach emphasizes interdisciplinary collaboration and methodological training in both quantitative and qualitative approaches.

• Wireless Communications
• Signal Processing
• MIMO Systems
• +۳ مورد دیگر

Konstantinos Nikitopoulos is a Professor at the University of Surrey , UK, specializing in Wireless Communications and Signal Processing . His research focuses on MIMO Systems , Open-RAN , and Non-Linear Processing for next-generation wireless networks. His recent work explores Analogue Processing for Tbps Wireless Systems and Neuromorphic Computing in MU-MIMO detection. He has developed frameworks like MIMO-SoftiPHY and SACCESS for software-based radio acceleration and power-efficient network design. Key Publications : Power-Efficient RIC, NL-COMM, NeuroMIMO Collaborators : Rahim Tafazolli, George Katsaros, Marcin Filo His research impacts 6G Network Development through innovations in Beamforming , Channel Estimation , and Software-Defined Radios .

Bipin Rajendranمشاهده پروفایل

استاد

• Intelligent Computing Systems
• Hardware-software co-design
• Novel materials & devices
• +۴ مورد دیگر

Bipin Rajendran is a Professor of Intelligent Computing Systems at King's College London, based in the Department of Engineering within the Faculty of Natural, Mathematical & Engineering Sciences. He directs the King's Laboratory for Intelligent Computing and co-leads the Centre for Intelligent Information Processing (CIIPS). Previously, he held positions at IBM Research and academic institutions in the U.S. and India. His research focuses on algorithms, devices, and systems for intelligent computing, emphasizing neuromorphic computing, memristive devices, and hardware-software co-design. Education: B.Tech, IIT Kharagpur (2000) M.S. and Ph.D., Electrical Engineering, Stanford University (2003, 2006) Research Interests: Rajendran's work spans hardware-software co-design, novel materials for neuromorphic systems, event-driven computing algorithms, and energy-efficient AI hardware. His contributions include foundational research on memristive devices for spiking neural networks and phase-change memory-based learning systems. Grants & Awards: He has received funding from EPSRC, NSF, European Commission, and industry partners like Intel and IBM. Notable awards include the IBM Faculty Award (2019) and election to the U.S. National Academy of Inventors (2019). Labs & Initiatives: Leads the King's Laboratory for Intelligent Computing and collaborates on projects like NeuroComm (6G neuromorphic comms) and SGAI (green AI systems). His work bridges nanoscale devices with AI algorithms for sustainable computing.

• Natural Computing
• Financial Modelling
• Operations Research
• +۳ مورد دیگر

Professor Anthony Brabazon is the College Principal and Dean of the UCD College of Business at University College Dublin. He holds a prominent administrative role alongside his academic contributions in natural computing and business analytics. His research focuses on natural computing theory, financial modeling using evolutionary algorithms, and complex adaptive systems in business contexts. Brabazon co-founded the Natural Computing Research and Applications Group (NCRA) at UCD, which explores theoretical and practical applications of bio-inspired algorithms. Education: B Comm and Dip. Prof Accounting – University College Dublin DBA – Kingston University, London DPA and Dip Stat – University College Dublin and Trinity College Dublin MBA – Heriot-Watt University, Edinburgh MS – Stanford University Research Interests: Anthony's work bridges computational intelligence and finance, with contributions to genetic programming, foraging-inspired optimization, and business analytics. His research highlights the application of evolutionary algorithms to real-world problems in finance, operations research, and organizational strategy. Grants and Collaborations: HEA Support for COVID-19 Related Research (2020–2025) Financial Mathematics and Computation Cluster (FMC²) (2009–2016) Teaching: Coordinated MAcc Management Accounting courses at the postgraduate level (2018–2019). Professional Activities: Member of CIMA Ethics Board Editorial board roles in multiple journals Founder of EvoBAFin workshop on computational finance

• Information Theory
• Active Learning
• Decentralized Learning
• +۴ مورد دیگر

Tara Javidi holds the Jerzy (George) Lewak Endowed Chair and is a Professor in the Department of Electrical and Computer Engineering and Halicioglu Data Science at the University of California San Diego (UCSD). She leads multiple initiatives, including serving as Founding CTO of KavAI, Co-Director of the Center for Machine Intelligence, Computing and Security, and Co-Principal Investigator (CoPI) of the NSF AI Institute TILOS. Her research focuses on stochastic analysis, design, and control of information systems, emphasizing active learning, decentralized optimization, and wireless networks. Key areas include information acquisition/utilization, stochastic control, and AI-driven communication solutions. Her work bridges theoretical foundations and practical implementations, such as drone systems for information gathering (via detecdrone.ucsd.edu) and optical data center networking. Notable contributions include end-to-end scheduling for all-optical data centers and hybrid wireless-optical architectures. Javidi is an IEEE Fellow and has received significant grants, including leading UCSD’s Schmidt AI in Science Postdoctoral Fellowship program. She actively collaborates with industry and academia, with a focus on next-generation wireless networks and decentralized systems. Education: Ph.D. in Electrical Engineering (implied from title). Affiliations: IEEE Journal of Selected Areas in Information Theory (Editor-in-Chief), CALIT2, CNS, and TILOS. Grants: NSF AI Institute TILOS ($20M over 5 years), Schmidt AI Fellowship program. Her research group emphasizes both theoretical rigor (e.g., sequential hypothesis testing) and practical testing, with applications in service drones, cognitive networks, and federated learning. Recent articles highlight advancements in optical networking, secure communication, and distributed learning protocols. Awards: IEEE Fellow, Jerzy Lewak Chair. Labs/Teams: Center for Machine Intelligence, TILOS Institute, KavAI, and UCSD’s AI in Science initiatives.

Glenford Mappمشاهده پروفایل

دانشیار

• Intelligent Transportation Systems
• Networking Protocols
• Cybersecurity
• +۶ مورد دیگر

Dr. Glenford Mapp is an Associate Professor in the Department of Computer Science at Middlesex University. His research focuses on Cooperative Intelligent Transportation Systems (C-ITS), transport protocols for mobile environments, and edge computing frameworks such as the Y-Comm system. He explores intelligent algorithms for caching, network memory servers, and energy-efficient resource allocation in vehicular edge networks. His work emphasizes cybersecurity in healthcare, digital forensics for big data networks, and smart city infrastructure. Notable contributions include frameworks for secure service ecosystems, decentralized digital forensics, and AI-driven network design integrating IoT and cloud computing. He collaborates on projects involving vehicular communications, wireless medical networks, and post-pandemic healthcare security. Publications span topics like edge computing, vehicular networks, and smart city technologies. His research bridges theoretical models (e.g., queuing theory, particle swarm optimization) with practical implementations, including prototypes for traffic management and secure cloud-based services.

Shiwen Maoمشاهده پروفایل

استاد

• Wireless Networks
• Multimedia Communications
• RF Sensing
• +۴ مورد دیگر

Shiwen Mao is a Professor and Earle C. Williams Eminent Scholar Chair at Auburn University's Department of Electrical and Computer Engineering. He serves as Director of the Wireless Engineering Research and Education Center. His education includes a Ph.D. in Electrical Engineering from Polytechnic University, M.S. in Systems Engineering, and dual B.E. degrees in Electronic Engineering and Enterprise Management from Tsinghua University. Research interests span wireless networks, multimedia communications, RF sensing for healthcare IoT, smart grid systems, and machine learning applications. Mao's work focuses on transforming edge intelligence, 6G systems, drone localization, and AI integration for next-generation networks. Recent publications demonstrate strong trends in AI-driven wireless communications, satellite-terrestrial networks, cybersecurity applications of large language models, and generative AI for wireless sensing. Awards and Honors: IEEE Communications Society's Best Paper Award (2021) IEEE Jack Neubauer Memorial Award (2020) Multiple National Science Foundation grants including a $300K award for 6G systems research Best Paper and Best Demo awards from IEEE conferences As Director of the Wireless Engineering Research and Education Center, Mao leads collaborative research involving over 20 faculty members addressing real-world communication challenges. The center develops solutions integrating drone technology, millimeter wave communications, and AI for future wireless systems.

• Statistics
• Sports science and exercise
• Ecological applications
• +۷ مورد دیگر

Paul Wu is an Associate Professor in the School of Mathematical Sciences at Queensland University of Technology (QUT), Faculty of Science, where he also serves as an industry research fellow in the strategic partnership between the Centre for Data Science (CDS) and AIS/QAS. He leads the sports systems domain within CDS and applies statistical and machine learning models to complex systems across sports, marine science, and defence sectors. PhD, Queensland University of Technology Master of Engineering Science (Computer and Comm Engineering), Queensland University of Technology Bachelor of Engineering (Electrical and Computer Engineering), Queensland University of Technology His research focuses on Bayesian statistics, dynamic Bayesian networks, state space modelling, and simulation techniques. He works closely with domain experts to solve real-world problems in sports performance, ecological resilience, and human systems. His interdisciplinary work spans sports science , marine ecology , and defence applications . Paul’s recent publications demonstrate a strong trajectory in predictive analytics for elite sports and ecosystem modelling, particularly using Bayesian frameworks. His work on swimming performance prediction has informed national training strategies and contributed to competitive success. He has also advanced methods in clustering, model adaptation, and psychosocial risk assessment. His scientific contributions have been recognized through impactful collaborations with elite sports organizations including the Australian Institute of Sport, Swimming Australia, and the West Coast Eagles. Testimonials highlight his role in transforming data analytics in sports injury recovery and performance optimization. Applied Bayesian models in elite sports decision-making Developed predictive tools for marine ecosystem resilience Collaborated on over 30 industry and government projects Supervises research in complex sports data analytics Paul leads a dynamic research environment focused on translating statistical innovation into practical impact across diverse domains.

• Finance
• Investments
• Derivative Securities
• +۴ مورد دیگر

Patrick J. Dennis is an Associate Professor of Commerce at the McIntire School of Commerce, University of Virginia. His research focuses on investments, derivative securities, market microstructure, and the impact of institutional investors on financial markets. He holds a Ph.D. in Finance from the University of North Carolina at Chapel Hill, an M.B.A. from Duke University, and a B.S. in Applied Physics from SUNY Geneseo. Research Expertise Professor Dennis specializes in empirical finance with emphasis on: Derivative Securities : Option pricing models, risk-neutral valuation Market Microstructure : Trading mechanisms, liquidity dynamics Institutional Investors : Impact on market competition and pricing Behavioral Finance : Decision-making patterns under cognitive load Publication Trends His 14 publications demonstrate consistent focus on market mechanisms from 1995-2022. Early work centered on derivative pricing and microstructure, evolving toward institutional ownership effects and behavioral aspects of trading. Recent publications feature high-impact empirical studies challenging established theories of market competition. Awards and Honors All-University Teaching Award (2012) European Finance Association Best Conference Paper (2018) Teaching and Advising Teaches advanced courses in investments and quantitative finance including: Quantitative Finance (COMM 3721) Asset Management (COMM 7750) Advanced Investments: Fixed Income & Derivatives (COMM 4730)

• Computer Science
• Computational Geometry
• Compiler Design
• +۲ مورد دیگر

Christian A. Duncan is a Professor of Computer Science and Director of BS and MS programs in Computer Science at Quinnipiac University , College of Engineering. His responsibilities include teaching advanced courses such as Compilers , Computational Geometry , and Computer Science Internship , while overseeing curriculum development for undergraduate and graduate programs. He can be contacted at (203) 582-3817 or via email at Christian.Duncan@quinnipiac.edu. Office hours are held in Comms, Computing & Engineering Room 248. Education: BS in Computer Science, Johns Hopkins University MSE in Computer Science, Johns Hopkins University PhD in Computer Science, Johns Hopkins University Research Focus: Computational geometry algorithms and applications Compiler optimization techniques Computer science pedagogy and curriculum development Implementation of specialized computing topics

Stephen Czarnuchمشاهده پروفایل

دانشیار

• Biomedical Engineering
• Computer Vision
• Machine Learning
• +۵ مورد دیگر

Dr. Stephen Czarnuch is an Associate Professor with joint appointments in the Faculty of Engineering and Applied Science and the Faculty of Medicine at Memorial University of Newfoundland. He directs the Centre for Artificial Intelligence and co-chairs the joint Masters of Applied Science in Software Engineering and Masters of Artificial Intelligence . His research focuses on biomedical engineering, computer vision, and machine learning applied to healthcare, gerontology, and public safety. Affiliations: Department of Electrical and Computer Engineering, Discipline of Emergency Medicine Education: B.Eng./Mgmt. (McMaster), MASc (McMaster), PhD (University of Toronto) Research emphasizes interdisciplinary work at the intersection of engineering, computer science, and medicine. Key areas include human motion tracking, public safety personnel mental health, and AI-driven healthcare solutions. He leads projects on Next-Gen 911 systems, assistive technologies for dementia care, and gait analysis for MS patients. Over 50 publications span computer vision algorithms, mental health interventions, and rehabilitation technologies. Notable collaborations include APCO Canada, CIHR, and the MS Society. His work addresses real-world challenges through user-centered designs and clinical partnerships. Funding Sources: NSERC, CIHR, SSHRC, Mitacs, and Memorial University grants Grants: Includes projects on assistive tech for dementia, mental health in public safety, and AI for emergency comms Advises over 20 graduate students across Engineering, Computer Science, and Sociology. His labs develop technologies for vulnerable populations, emphasizing accessibility and ethical AI deployment.

• Mechanics
• Design Optimization
• Computational Modeling
• +۵ مورد دیگر

Kokou Esso is a Lecturer at the University of Technology Belfort-Montbéliard (UTBM), affiliated with the Institute of Mechanics, Materials and Civil Engineering (ICB-COMM) and the Design, Optimization and Modeling in Mechanics department. His career spans over three decades with expertise in mechanics, materials science, and sustainable engineering. Key Research Themes : Mechanical design optimization, multi-material damage modeling, agroresource-based composites, and eco-design for sustainability. Leadership Roles : Scientific project manager, interuniversity collaboration coordinator, and member of HDR (Research Director Qualification) committees. International Engagement : Extensive work with the University of Lomé (Togo) on materials research and environmental projects, including PCBs inventory for UNIDO/UNEP. His technical expertise intersects with environmental responsibility, reflected in projects like Campus/Corus and EcoDesign & Innovation Materials.

Christ Richmondمشاهده پروفایل

استاد

• Signal Processing
• Radar Systems
• Communication Networks
• +۳ مورد دیگر

Christ Richmond is a Professor in the Department of Electrical and Computer Engineering, focusing on advanced signal processing and communication systems. His work bridges theoretical analysis and practical applications in radar, sonar, and wireless networks. Institution: Department of Electrical and Computer Engineering Role: Faculty member His research interests include signal processing for high-clutter environments, cooperative radar-communication systems, and robust adaptive beamforming. He explores statistical methods to handle model misspecification and employs Bayesian nonparametric techniques for tracking and estimation challenges. Key trends in his publications span radar-communication integration (2019-2022), SAR image change detection (2015-2020), and theoretical bounds for parameter estimation under uncertain models (2000-2020). The Learning to Communicate project (2022) investigates next-generation communication networks using data-driven approaches, addressing variability in wireless links and evolving system modeling paradigms.

Rafael Patrickمشاهده پروفایل

استادیار

• Human Factors Engineering
• Applied Psychophysics
• Auditory Situation Awareness
• +۵ مورد دیگر

Rafael Patrick is an Assistant Professor in the Department of Industrial and Systems Engineering at Virginia Polytechnic Institute and State University (Virginia Tech), part of the College of Engineering. His research focuses on human factors psychology, auditory situation awareness, and user-centered design with applications in transportation systems, virtual reality, and wearable technology. He holds a Ph.D. in Industrial & Systems Engineering from North Carolina A&T State University (2018), an M.S. in Human Factors and Systems from Embry-Riddle Aeronautical University (2012), and a B.S. in Human Factors Psychology from the same institution (2008). Dr. Patrick’s professional history includes roles as a graduate research assistant at North Carolina A&T’s Transportation Institute and research supervisor at Embry-Riddle’s McNair Scholars Program. He teaches courses such as Discrete Event Systems Modeling & Simulation and Occupational Biomechanics & Ergonomics. His work has been recognized through awards including the McNair Program’s Outstanding Alumnus Mentor Award and Title III Dissertation Fellow designation. His research trends emphasize improving safety through auditory interface design, with recent studies examining bone conduction technology in VR environments and pedestrian-vehicle communication systems. Collaborations include developing the TESSERACT loudspeaker array for spatial sonification and investigating distractions at campus crosswalks. Professional affiliations include the Human Factors and Ergonomics Society (HFES) and Institute of Industrial and Systems Engineers (IISE). Education: Ph.D., Industrial & Systems Engineering, North Carolina A&T State University (2018) M.S., Human Factors and Systems, Embry-Riddle Aeronautical University (2012) B.S., Human Factors Psychology, Embry-Riddle Aeronautical University (2008) Awards: Dr. Ronald E. McNair Scholars Program: Outstanding Alumnus Mentor Award NC A&T Title III Dissertation Fellow NC A&T ISE Department Awards: Humanitarian, Research, & Teaching Labs/Teams: Engages in interdisciplinary projects involving virtual reality safety systems and wearable auditory interfaces through Virginia Tech’s College of Engineering initiatives.

Shannon David Bluntمشاهده پروفایل

استاد

• Radar Signal Processing
• Waveform Design and Optimization
• Cognitive Radar Systems
• +۳ مورد دیگر

Shannon David Blunt is the Roy A. Roberts Distinguished Professor at the University of Kansas, affiliated with the School of Engineering's Department of Electrical Engineering and Computer Science. His research focuses on advanced radar signal processing, waveform design, cognitive radar systems, and radar-communications integration. He leads experimental projects such as the Waveform Diversity Experimentation System (WaDES) and the SMART Hub initiative addressing spectrum crisis challenges. His work emphasizes spectral efficiency, adaptive processing, and real-time cognitive radar solutions. Blunt holds editorial roles, including founding the IEEE Transactions on Radar Systems, and has contributed to over 100 peer-reviewed articles since 2017. Research Interests: Radar signal processing innovations include optimizing radar waveforms for multifunction digital arrays, developing random FM techniques, and advancing clutter suppression algorithms. His research bridges radar and communications via initiatives like Phase-Attached Radar-Communications (PARC) and Multi-User Radar/Communications (MURC). Key areas include waveform diversity, spectrum sharing, and real-time spectral notching for cognitive radar. He explores bio-inspired systems and medical signal processing applications, though his primary focus remains radar systems engineering. Recent Trends in Articles: Recent work (2023–2025) emphasizes hybrid FM waveforms, reiterative super-resolution algorithms, and physical waveform optimization. Publications address challenges in Doppler robustness, waveform recycling, and experimental validation of spectrum-sharing technologies. Collaborations with industry and government labs highlight applied research in spectrum management and mm-wave radar for automotive/urban mobility. Awards & Recognition: Roy A. Roberts Distinguished Professorship Leadership in the IEEE Radar Journal and Special Sections Grants & Labs: Directs the SMART Hub (Solving the Spectrum Crisis) and oversees WaDES. His lab's experimental systems demonstrate real-time cognitive radar and spectrum-sharing solutions. Advises on federal grants for radar spectrum engineering and vehicular RF convergence projects. Labs & Teams: Active in the University of Kansas's radar engineering group, collaborating with the SMART Hub consortium and industry partners like Raytheon and Boeing.