Find Academic Supervisors

• Evolutionary Computing
• Adaptive Systems
• Artificial Intelligence
• +3 more

Prof. Gusz Eiben is a Full Professor at Vrije Universiteit Amsterdam, affiliated with the Faculty of Science (Artificial Intelligence), Network Institute, and Computational Intelligence. His research focuses on evolutionary computing, adaptive systems, and robotics, particularly in controller optimization and AI-driven robotics. He holds an ORCID ID: 0000-0002-3106-4213 . His work explores evolutionary algorithms, reinforcement learning, and robotic morphologies, with applications in hardware-software integration and autonomous systems. Notable contributions include studies on robot curriculum learning and evolvable traits in robotics. Awards : 2001 IEEE Transactions on Evolutionary Computation Outstanding Paper Award Best Paper Award at EvoApps (2012) Best Paper Award at PPSN (2014) Activities : Active in academic memberships including IEEE Transactions on Evolutionary Computation, Journal of Evolutionary Optimization, and various conferences since 2000. Teaches the Evolutionary Computing course (2024–2025). Research datasets include studies on drone flocking optimization and modular robot skill learning, available via Dryad and Zenodo.

• Digital Forensics
• Cybersecurity
• Network Forensics
• +5 more

Dr. Mark Scanlon is an Associate Professor in the School of Computer Science at University College Dublin (UCD), where he also serves as Founding Director of the UCD Forensics and Security Research Group and Programme Director of the MSc in Forensic Computing and Cybercrime Investigation. He holds a PhD in Remote Digital Forensic Evidence Acquisition and Analysis from UCD and is a Fulbright Scholar in Cybersecurity. His research focuses on digital forensics, cybersecurity, and IoT device analysis, with notable contributions in electromagnetic side-channel analysis, AI-driven forensic tools, and password cracking methodologies. Education: BA, University College Dublin MSc and PhD in Remote Digital Forensic Evidence Acquisition and Analysis, University College Dublin Professional Diploma in University Teaching & Learning, UCD Affiliations: Principal Investigator at CeADAR (National Centre for Applied AI) Senior Editor, Forensic Science International: Digital Investigation Scanlon’s research interests span digital forensics, cybersecurity, and AI applications in investigation. He has pioneered work in electromagnetic side-channel analysis for IoT devices, non-invasive cryptographic analysis, and leveraging LLMs for forensic efficiency. His work addresses challenges such as data deduplication, password cracking optimization, and improving practitioner workflows through automated tools like TraceGen and EMvidence frameworks. His articles highlight trends in AI integration (e.g., LLMs for evidence analysis), IoT forensic readiness, and practitioner challenges (via the DFPulse survey). Scanlon has secured grants including a Fulbright award for collaborative research and led initiatives in forensic education and ethical hacking training. His contributions bridge academic research and real-world forensic practices, emphasizing ethical considerations and tool development. Scientific Awards: Fulbright Scholar in Cybersecurity and Cybercrime Investigation In teaching, he coordinates modules such as Advanced Computer Forensics, Ethical Hacking, and OSINT Analysis, reflecting his commitment to advancing forensic education and cybersecurity training.

Ryan GrantView profile

Assistant Professor

• Cloud Computing
• High Performance Networks
• Low-level Hardware-Software Interfaces
• +6 more

Dr. Ryan Grant is an Assistant Professor in the Department of Electrical and Computer Engineering at Queen’s University, Canada. He leads the Computing at Extreme Scale Advanced Research (CAESAR) lab and is affiliated with the Ingenuity Labs Research Institute. His expertise spans cloud computing, high-performance networks, low-level hardware-software interfaces, and energy-efficient supercomputing systems. Dr. Grant holds a PhD from Queen’s University (2012) and previously worked at Sandia National Laboratories (2012–2021), where he contributed to critical supercomputer communication protocols now deployed globally. He has authored over 80 peer-reviewed articles and received prestigious awards including the R&D100 Award and Queen’s University’s 125th Engineering Alumni Award. His research emphasizes advancing Canada’s supercomputing infrastructure to support AI, climate science, and national security applications. Education: PhD in Computer Engineering, Queen’s University (2012) MSc in Computer Engineering, Queen’s University (2005) BSc in Computer Engineering, Queen’s University (2004) Research Interests: Dr. Grant’s work focuses on optimizing supercomputing architectures for extreme-scale systems, with an emphasis on: High-performance networking and MPI communication protocols Power/energy management in HPC systems AI-driven network traffic prediction and resource disaggregation GPU-accelerated computing and cloud infrastructure integration National sovereignty in supercomputing for sensitive applications (e.g., defense, healthcare) Awards & Recognition: R&D100 Award (Oscars of Research) U.S. Defense Programs Awards Public Good Innovator Award Queen’s University 125th Engineering Alumni Award Grants & Labs: Dr. Grant directs the CAESAR lab, one of the world’s leading supercomputing architecture research groups. His work is supported by grants from Canadian and international agencies, focusing on sovereign supercomputing and HPC-AI convergence. Labs/Teams: CAESAR Lab (Queen’s University) Ingenuity Labs Research Institute

John R. WagnerView profile

Professor

• Mechatronics
• Nonlinear Control
• Intelligent Control
• +7 more

Dr. John R. Wagner is a Professor in the Department of Automotive Engineering at Clemson University's College of Engineering, Computing and Applied Sciences. He joined the department in August 1998 after industry roles at Delco Electronics, Hughes Electronics, and Delphi Automotive Systems, where he developed automotive control systems using hardware-in-the-loop and in-vehicle testing. Wagner established the Driving Simulator Laboratory and Rockwell Automation Mechatronics Educational Laboratory, and serves as faculty advisor for the Clemson SAE student chapter. His educational background includes: Ph.D. in Mechanical Engineering from Purdue University (1989) M.S. in Mechanical Engineering from SUNY at Buffalo (1985) B.S. in Mechanical Engineering from SUNY at Buffalo (1983) Wagner's research centers on Mechatronics , Nonlinear Control , and Intelligent Control systems with applications in automotive, energy, and manufacturing. He pioneers diagnostic/prognostic strategies and dynamic system modeling for turbine systems and vehicle safety, recently advancing digital twin technology for predictive maintenance and collaborative design. His work integrates AI-driven methodologies for autonomous vehicle safety and thermal management. Recent publications (2023-2025) reveal a dominant shift toward digital twin applications in ground vehicle maintenance, design validation, and tradespace exploration. Key trends include adversarial learning for highway safety, driver behavior analysis for traffic improvement, and PLM tool integration in engineering education, reflecting convergence of AI, systems engineering, and practical automotive solutions. His primary recognition includes: ASME Fellow Wagner actively mentors students through SAE chapter leadership and laboratory research, guiding capstone projects in mechatronics and vehicle dynamics. His educational initiatives include developing the Rockwell Mechatronics Laboratory and integrating PLM concepts into curriculum. Industry collaborations (e.g., Rockwell Automation) and editorial roles (IEEE/ASME Transactions on Mechatronics) underscore his impact on automotive engineering practice and pedagogy. He directs the Driving Simulator Laboratory and Rockwell Automation Mechatronics Educational Laboratory, enabling interdisciplinary research in vehicle control systems, energy harvesting, and human-vehicle interaction for next-generation automotive solutions.

Alessio OrsinoView profile

Research Fellow

• Big Data Analysis
• Distributed Computing
• Edge-Cloud Computing
• +5 more

Alessio Orsino is a Research Fellow at the Department of Computer Science, Modeling, Electronics and Systems Engineering (DIMES) at the University of Calabria. His academic journey includes a Ph.D. in Information and Communication Technologies (ICT) awarded in January 2025, a Master’s in Computer Engineering (Big Data Analytics and Data Science) from 2020, and a Bachelor’s in Computer Engineering from 2018, all from the University of Calabria. He also served as a visiting researcher at the University of Cambridge’s Department of Computer Science and Technology (July–December 2023). His research focuses on big data analysis, distributed computing, machine learning, and edge-cloud integration. He contributes to projects like ASPIDE (Exascale programming models) and INSIDER (cloud-edge IoT deployment optimization), funded by EU Horizon 2020 and Italy’s MIUR. He is a contract professor at DIMES and a member of the Scalable Computing and Cloud Laboratory (SCALab). Orsino’s work bridges theoretical and applied computing, emphasizing efficient machine learning on resource-constrained systems and real-time adaptive models for edge environments. His publications address edge-cloud continuum challenges, adversarial robustness in AI, and scalable big data frameworks. Key grants include Horizon 2020 (ASPIDE) and PRIN 2022 (INSIDER), supporting his interdisciplinary research in hybrid cloud-edge infrastructures and data-intensive applications. He has authored/co-authored a book on big data programming and collaborates internationally through visiting positions and lab engagements.

Zakirul Alam BhuiyanView profile

Associate Professor

• Cybersecurity
• Privacy-Preserving Systems
• Trustworthy AI/ML
• +7 more

Dr. Md Zakirul Alam Bhuiyan is an Associate Professor in the Department of Computer and Information Sciences at Fordham University, New York. He leads the DependSys Lab (Dependable and Secure Systems Lab) and is affiliated with the Fordham Center for Cybersecurity. His research focuses on cybersecurity, data-driven dependability, trustworthy AI/ML, and IoT/CPS applications. He has authored over 250 publications, including top-tier journals and conferences like IEEE Transactions on Industrial Informatics and IEEE INFOCOM. Dr. Bhuiyan has held adjunct roles at Harvard University and Temple University. His work emphasizes securing healthcare monitoring systems, event detection in CPS, and privacy-preserving data collection. Education details are not explicitly stated, but his career trajectory includes prior positions at Temple University and Harvard. He has secured grants and awards, including the IEEE TCSC Award for Excellence, ScholarGPS recognition, and being named one of the world's top 2% scientists. His professional activities include editor roles for IEEE Transactions and ACM journals, and organizing major conferences like IEEE DASC and TrustCom. Research interests span cybersecurity, IoT, and AI/ML, with a focus on real-world applications like structural health monitoring and smart city infrastructure. His lab, DependSys, addresses challenges in dependable and secure systems. He has advised numerous students and collaborates globally, delivering keynote speeches at events like IEEE ISPA and ICECI. Key achievements include 25+ ESI Highly Cited Papers, 7 Best Paper Awards, and leadership in over 50 conferences. Current projects involve federated learning, edge computing, and blockchain for healthcare privacy. His lab explores innovative uses of Wi-Fi signals for sensing and security, including contactless health monitoring and intrusion detection.

Jesus SalidoView profile

Professor

• Robotics
• Artificial Intelligence
• Image Processing
• +4 more

Jesus Salido is a Professor at the University of Castilla-La Mancha's School of Computer Science, affiliated with the Department of Systems Engineering and Automation (ISA). He holds a PhD in Industrial Engineering (Robotics and AI) from Universidad Politécnica de Madrid (UPM) and completed a PostDoc at Carnegie Mellon University's Robotics Institute in Pittsburgh, USA. Education: PhD in Industrial Engineering (Robotics and AI), Universidad Politécnica de Madrid (UPM) PostDoc at AML – The Robotics Institute, Carnegie Mellon University Research Interests: Focuses on Robotics, Artificial Intelligence, Medical Imaging, Computer Vision, and Educational Technology . His work includes developing low-cost microscopy systems (e.g., MicroHikari3D), AI-driven pathology tools, and educational resources in digital logic design using Logisim. He leads the VISILAB-UCLM research group, emphasizing Open Science and accessibility in technology. Key Projects: Eyes of Things (EOT): Smart sensor networks for environmental monitoring AIDPATH: Collaboration between academia and industry in digital pathology Bonseyes: Marketplace for edge device collaboration Publications & Contributions: Authored textbooks like Learning Image Processing with OpenCV and Lógica Digital y Tecnología de Computadores . Over 50 peer-reviewed articles on topics ranging from deep learning applications to automated microscopy systems. Actively contributes to open-source educational repositories on GitHub. Teaching: Teaches courses in Computer Technology, VLSI Design, and Artificial Intelligence at the undergraduate and master’s levels. Leads personalized tutoring initiatives to enhance student success and critical thinking.

Abdel-Karim Al-TamimiView profile

Senior Lecturer

• Machine Learning
• Natural Language Processing
• Multimedia Networks
• +3 more

Dr. Abdel-Karim Al-Tamimi is a Senior Lecturer in Computer Science and Software Engineering at Sheffield Hallam University (SHU), where he leads the Interactive Data Analytics Group (iDAG) and contributes to the Applied Software Engineering Research Group (ASERG). He previously served as an Associate Professor at Yarmouk University (Jordan), Director of the Entrepreneurship and Innovation Center (EIC), and Department Chair at the Higher Colleges of Technology (UAE). His roles include consultancy in digital transformation via the DIfG program and editorial board memberships for PLOS ONE and Research Reports on Computer Science . Education: MSc and PhD in Computer Engineering, Washington University in St. Louis (2007, 2010) Senior Fellow of the Higher Education Academy (SFHEA) Research Interests: Machine Learning applications in Natural Language Processing (NLP), Multimedia Networks, Computer Security, and IoT. Recent work focuses on conversational agents (e.g., Phyllis chatbot for adolescent health) and cybersecurity education frameworks. Projects include EU-funded initiatives (e.g., H2020, DFG) and interdisciplinary collaborations in AI-driven solutions. Publications: Over 50+ peer-reviewed articles, including recent contributions on optimization algorithms, game-based learning, and threat intelligence models. His work spans journals like Cluster Computing , ACM Transactions on Computing Education , and conferences such as IEEE BigComp. Grants & Awards: Received £10k for the Phyllis chatbot project and £9.8k for Sheffield’s population health initiative. Awards include SFHEA and industry certifications (Huawei HCIA-AI, Cisco CCNA). Advising & Teams: Oversees interdisciplinary projects and labs like the Orange-Yarmouk Innovation Lab. Active in academic entrepreneurship through roles like Co-Founder of Phyllis and mentor at global hackathons.

Wes BethelView profile

Associate Professor

• Quantum Computing
• Machine Learning
• Scientific Computing
• +4 more

Wes Bethel is an Associate Professor in the Department of Computer Science at San Francisco State University. His research focuses on quantum computing, machine learning applications in scientific modeling, and high-performance computing frameworks such as the SENSEI in situ visualization system. He leads efforts in optimizing quantum algorithms, real-time fusion energy modeling, and scalable data processing for large-scale simulations. Key research themes include quantum protocols for polynomial computation, GPU-based quantum circuit simulation, and machine learning-driven approaches to plasma physics and radio frequency (RF) heating analysis. His work bridges theoretical advancements with practical implementations in energy science and computational infrastructure. Recent projects emphasize accelerating RF modeling using AI surrogates, improving in situ visualization frameworks for heterogeneous architectures, and addressing challenges in classical-quantum system integration. Contributions span both methodological innovations and applied solutions for fusion energy research and distributed computing environments. No scientific awards are listed in the provided materials. Advising and grants information is not explicitly detailed here, though his publications indicate collaborative involvement in DOE-funded projects and fusion energy initiatives. He contributes to open-source tools like SENSEI and WarpVisIt, supporting community-driven advancements in scientific computing. Research labs and teams associated with his work likely include computational science groups focused on quantum computing, plasma physics modeling, and high-performance data management at San Francisco State University and collaborating institutions.

Bin YangView profile

Professor

• Computer Science
• Data Management
• Machine Learning
• +9 more

Bin Yang is a Professor at the Department of Computer Science, Aalborg University, affiliated with The Technical Faculty of IT and Design. His research focuses on data engineering, artificial intelligence, and machine learning, with emphasis on spatiotemporal data analysis, representation learning, and time series forecasting. He leads projects like aSTEP (spatio-temporal data analytics) and Light-AI for Cognitive Power Electronics. Key contributions include advancements in trajectory data processing, anomaly detection, and lightweight neural architectures. Research interests span machine learning, data mining, intelligent transport systems, and material science applications. Notable awards include the IJCAI 2019 Distinguished PC Member and Sapere Aude Research Leader (2018). He has supervised six PhD students and contributed to over 119 publications. His work is supported by grants from Villum Foundation and EU initiatives. Yang is involved in interdisciplinary collaborations, including data-driven decision-making frameworks and environmental monitoring systems. Labs and teams include the Daisy Center for Data-intensive Systems and AI for the People initiatives. Projects emphasize real-world applications in smart cities, traffic forecasting, and sustainable technologies. His research bridges theoretical foundations with practical implementations in domains like oceanography and crowdsourcing systems.

Saptarshi DebroyView profile

Associate Professor

• Computer Networking
• Network Security
• Big Data Networking
• +9 more

Saptarshi Debroy is an Associate Professor of Computer Science at Hunter College and a member of the Doctoral Faculties at The Graduate Center, CUNY. He leads the Distributed Systems and Security (DiSSect) Lab and co-leads the CoSSMO Lab, focusing on resilient distributed systems, edge computing, and cyber security. His research addresses challenges in disaster response systems, federated cloud workflows, and moving target defense mechanisms. He holds a PhD in Computer Engineering from the University of Central Florida and has held roles including Post-Doctoral Fellow at the University of Missouri. Education: PhD (Computer Engineering, UCF, 2014), MTech (Distributed & Mobile Computing, Jadavpur University, 2008), BTech (Information Technology, West Bengal University of Technology, 2006) Research Interests His work spans distributed systems, edge/AI-driven networks, cyber security, and resource optimization in disaster scenarios. Key areas include fog computing frameworks for real-time video processing (EFFECT), secure federated workflows (ADON), and MTD-based cloud defense strategies. He emphasizes practical applications like disaster response and healthcare data security. Grants & Awards Recipient of NSF CAREER Award (2020), NSF grants totaling over $1.1M, and Google Research Award. Notable projects include a trusted framework for health incident response (NSF), volunteer edge-cloud resource allocation (NSF), and DDoS mitigation strategies (NSF). Teaching & Service Teaches graduate courses on distributed systems, cloud computing, and networks at CUNY. Serves on NSF review panels and as chair for IEEE/ACM conferences. Leads initiatives like the Cyber Security Summer School for Women to promote diversity in tech. Labs & Collaborations Directs the DiSSect Lab, which develops edge-native systems for disaster response and secure AI. Collaborates with FDNY, perfSONAR, and NSF-funded testbeds like PAWR. Partnerships include projects with bioinformatics and high-performance computing communities (CyVerse, XSEDE).

Arjuna MadanayakeView profile

Associate Professor

• Multidimensional systems
• Wireless communications
• Array processing
• +7 more

Arjuna Madanayake is an Associate Professor in the Department of Electrical & Computer Engineering at Florida International University (FIU), part of the College of Engineering. His research focuses on multidimensional systems, wireless communications, array processing, and analog computing. He holds a Ph.D. from the University of Calgary and B.S. from the University of Moratuwa, Sri Lanka. Dr. Madanayake's work emphasizes low-complexity algorithms for multi-beam beamforming, RF sensing, and FPGA implementations. His lab (RAND Lab) develops innovative solutions in terahertz communications, spectrum intelligence, and AI-driven signal processing. He teaches EEL 5500 Digital Communication Systems and collaborates on projects involving reconfigurable intelligent surfaces and 5G/6G technologies. His recent publications (2020–2025) address challenges in ultra-broadband communication systems, analog computing for PDEs, and spectrum management. He has contributed to IEEE journals and conferences, focusing on practical implementations in hardware and software-defined radio platforms.

Hadi Mardani KamaliView profile

Assistant Professor

• VLSI design
• Hardware security
• FPGA design
• +3 more

Hadi Mardani Kamali is an Assistant Professor at the University of Central Florida (UCF) in the Department of Electrical and Computer Engineering . His research focuses on VLSI design and testing , Hardware security and trust , FPGA design , Electronic design automation (EDA) , and Applied machine learning in hardware contexts. Dr. Kamali is actively engaged in research projects related to IC/IP protection , security-aware EDA , and security of learning models .

• Wireless Communications
• Satellite Communications
• RF and Microwave Engineering
• +5 more

Dr. Viktor Doychinov is a Lecturer in Electronics and Software Engineering at the University of Bradford, affiliated with the Bradford-Renduchintala Centre for Space AI. His academic journey includes a BEng in Telecommunications from Sofia Technical University, an MSc in Spacecraft Technology from University College London, and a PhD in Electronic and Electrical Engineering from the University of Leeds. He previously worked as a postdoctoral researcher in robotics at Leeds' Institute of Robotics, Autonomous Systems, and Sensing. His research focuses on wireless communications, satellite systems, and millimeter-wave technologies. Key areas include nanosatellite transceiver hardware, mesh networks for robotics/satellites, and open-source tools for space engineering. He also explores applications in resource-constrained environments like exploration robotics and biomedical devices. Teaching responsibilities include modules on embedded electronics, digital signal processing, satellite communications, and space mission design across undergraduate and postgraduate programs such as BEng/MEng Biomedical Engineering and MSc Satellite Systems Engineering. He actively engages in STEM outreach through roles like Transpennine Hub Ambassador and has received an RAEng Ingenious grant. Education: BEng (Telecom), MSc (Spacecraft Tech), PhD (Electronic Engineering) Professional Skills: RF/microwave design, SDR prototyping, robotics frameworks (ROS2/MAVLink), C/Python programming Outreach: STEM Ambassador, RAEng grant recipient (2020/21) His 19 publications span topics like wireless energy harvesting, antenna design, and underground robotics communication. He collaborates with industry on projects such as the Pipebots infrastructure inspection system and space mission simulation using STK/GMAT software.

Samuel MulderView profile

Academic

• Cyber Security
• Program Analysis
• Reverse Engineering
• +2 more

Samuel Mulder is an Associate Research Professor in the Department of Computer Science and Software Engineering at Auburn University. He holds a Ph.D. in Computer Science from Missouri S&T, along with an M.S. and B.S. in Computer Science from Missouri S&T and Texas Tech University, respectively. His research focuses on cybersecurity, program analysis, reverse engineering, adversarial analysis, and machine learning applications. He is affiliated with the Center for Artificial Intelligence and Cybersecurity Engineering within the College of Engineering. His research interests include developing immersive virtual reality techniques for binary reverse engineering, modeling adversarial competition in satellite communication systems (P-LEO constellations), and enhancing cybersecurity through dynamic defense mechanisms like moving target defense. He has contributed to frameworks for tracking cyber adversaries using adaptive indicators of compromise and improving solver algorithms for constraint satisfaction problems. Mulder's work spans both theoretical advancements (e.g., neuromorphic computing surveys) and applied solutions (e.g., supply chain binary program assessments). His recent efforts emphasize gamification of competitive cybersecurity scenarios and embodied cognition approaches to software analysis. While no scientific awards are explicitly listed, his contributions reflect impactful work in cybersecurity innovation. He collaborates with Auburn's engineering research centers, particularly in AI-driven cybersecurity solutions. His advising and grant activities are not detailed in the provided text, but his research aligns with Auburn's focus on interdisciplinary engineering challenges.