Wilmar Martinez Martinez is an Associate Professor at the Department of Electrical Engineering (ESAT) , KU Leuven , and Research Line Coordinator at EnergyVille. His work bridges power electronics, renewable energy systems, and electromobility technologies. Education: PhD in Power Electronics (Shimane University, Japan), MSc in Electrical Engineering (Universidad Nacional de Colombia) Research Interests: Power conversion optimization for energy systems, magnetic components design, SiC/GaN semiconductor applications, and machine learning in power electronics Projects: Leads research on high-frequency magnetic components, wireless charging topologies, and sustainable energy storage solutions with ongoing projects until 2028 Publications: 15 most recent works focus on converter architectures, thermal modeling, and AI-driven magnetic loss predictions Affiliations: Member of EnergyVille, Leuven Centre for Affordable Sustainable Technology, and KIES - KU Leuven Institute for Energy and Society
Md Ferdous Alam is a Postdoctoral Associate at the Massachusetts Institute of Technology School of Engineering , affiliated with the Department of Mechanical Engineering. Previously, he earned his Ph.D. from Ohio State University and worked at Autodesk AI Lab as a research intern and collaborator. Academic Affiliations: Current: MIT (Postdoctoral Associate) Ph.D.: Ohio State University Research Collaborator: Autodesk AI Lab Research Interests focus on generative AI, reinforcement learning, and optimal control theory for manufacturing automation. His work integrates AI with hardware for real-time autonomous systems, particularly in 3D CAD/CAM and robotic manufacturing. Key projects include: Developing GenCAD for image-conditioned CAD generation Building a universal manufacturing operating system with AI at its core Advancing data-efficient reinforcement learning algorithms Creating multimodal benchmarks like DesignQA Scientific Awards include the Google Research Scholar Award 2024 in Applied Science and Best Paper Award at MSEC 2020. His publications span journals like Journal of Mechanical Design and conferences including IDETC-CIE. He is active in open-source development, maintaining repositories for autonomous manufacturing and machine learning frameworks.
Dr. Annabel Latham is a Senior Lecturer in Computer Science at Manchester Metropolitan University within the Faculty of Science and Engineering’s Computing and Mathematics department. She holds a PhD in Artificial Intelligence, an MSc in Computing, a Postgraduate Certificate in Academic Practice, a CIM Diploma in Marketing, and a BSc(Hons) in Computation. As a Fellow of the Higher Education Academy (FHEA) and Senior Member of IEEE (SMIEEE), she contributes extensively to AI research and education. PhD in Artificial Intelligence MSc in Computing PGC Academic Practice CIM Diploma in Marketing BSc(Hons) Computation FHEA (2015) SMIEEE (2018) Research Interests include Artificial Intelligence in Education , Ethics of AI , and Computational Intelligence . She specializes in conversational agents, intelligent tutoring systems, and public trust in AI. Her work addresses fairness, accountability, and accessibility in AI-driven education, leveraging technologies like large language models and fuzzy logic. Research Outputs span 15 years, with a focus on explainable AI, educational applications of conversational agents, and ethical frameworks. Recent work (2024-2025) explores postdigital citizen science, trustworthy AI implementation, and XAI usability for non-specialists. 2023 IEEE Region 8 Outstanding Women in Engineering Volunteer Award 2019 IEEE Region 8 Outstanding Women in Engineering Affinity Group of the Year 2018 Outstanding Peer Reviewer, Elsevier: Computers & Education Senior Member IEEE (2018) FHEA (2015) Teaching and Supervision includes undergraduate Databases, postgraduate units in Information Systems and AI Ethics. She supervises MSc and PhD students in areas like explainability-aware machine learning, data responsibility, and AI trustworthiness. Her grants involve collaborations with international funding bodies such as NAFOSTED (Vietnam) and Croatia’s National Council for Science. Labs and Groups include the Computational Intelligence Lab, Machine Intelligence research group, and the Data and AI Ethics research group, where she co-leads initiatives on ethical AI in education.
Prof. Sumit Kumar Jha is a Professor in the Department of Computer Science at Florida International University (FIU), specializing in artificial intelligence, formal methods, and computer architecture. His research focuses on AI-driven system design, in-memory computing, and robust machine learning systems. He leads over $17 million in active research projects from agencies like DARPA, AFRL, NSF, and DOE. Research interests include: Adversarial machine learning and model robustness Neuro-symbolic systems and program synthesis Analog/digital in-memory computing architectures Formal verification and safety-critical systems Explainable AI and model interpretability Recent work emphasizes secure LLM code generation, quantum computing applications, and fault-tolerant in-memory systems. His publications span top venues like ICML, ICLR, and DAC. Awarded FIU's Top Scholar Award (2024-25) and multiple best paper nominations. Active in NSF-funded initiatives including SPX (extreme-scale computing) and FMitF (formal methods in in-memory systems).
Ahmad Salman is an Associate Professor at James Madison University (JMU) in the College of Integrated Science and Engineering (CISE), specializing in Cybersecurity, Hardware Security, and the Security of the Internet of Things (IoT). He holds a Ph.D. in Computer Engineering from George Mason University (2017) and an M.S. in Computer Engineering from the same institution (2011), with a B.Sc. in Computer Engineering from the University of Arab Academy for Science and Technology (2002). Education: Ph.D. in Computer Engineering, George Mason University (2017) M.S. in Computer Engineering, George Mason University (2011) B.Sc. Computer Engineering, University of Arab Academy for Science and Technology (2002) Research Interests: His work focuses on securing emerging technologies, including IoT systems, UAVs, and cyber-physical infrastructure. Key areas include AI-driven cybersecurity solutions, hardware-based security mechanisms, and privacy preservation in smart environments. Recent projects involve real-time emotion detection for companion robots, secure UAV surveillance systems, and automated vulnerability inspection tools like SAVI. Grants and Contributions: Salman has secured multiple grants and published widely in high-impact venues. He advocates integrating ethical reasoning into applied science curricula and emphasizes practical applications of security technologies. His work often bridges theoretical research and real-world deployments, such as the SAWBRID smart whiteboard system and transit monitoring frameworks. Labs and Collaborations: While specific lab affiliations are not detailed, his research collaborations involve interdisciplinary teams focusing on IoT, AI, and cybersecurity. He actively participates in IEEE and ACM initiatives, driving advancements in hardware-software co-design for secure systems.
Hala ElAarag is a Professor of Computer Science at Stetson University, located in Deland, Florida. She holds a PhD from the University of Central Florida (2001) and MS/BS degrees from Alexandria University (1991/1989). Her research focuses on computer networks, machine learning, cybersecurity, and computer science education. She has authored over 70 publications and 11 edited books, including her notable work Web Proxy Cache Replacement Strategies Simulation, Implementation, and Performance Evaluation . ElAarag has served in leadership roles, such as President of the Consortium of Computing Sciences in Colleges (2016-2018) and Vice President (2014-2016). She has also been active in organizing conferences, including co-chairing the Communication and Networking Simulation Symposium and Spring Simulation Multiconference. Her teaching philosophy emphasizes hands-on learning, reflected in her development of 15 computer science courses, including core and specialized subjects like Computer Networks and Algorithms Analysis. Her research trends span algorithm optimization, network security, and autonomous systems, with recent work in AI-driven password cracking and quadrotor modeling. Awards include the IEEE Region 3 Biedenbach Award (2022) and multiple teaching and service recognitions. She has mentored numerous students and contributed to STEM outreach through initiatives like the Tech Trek Coordinator for middle school girls (2021-2023). ElAarag’s contributions extend to editorial roles in journals like Journal of Computing Sciences in Colleges and Simulation: Transactions of SCS . Her work bridges academic research and practical application, emphasizing pedagogical innovation and interdisciplinary collaboration.
Nicola Anselmi is a Researcher (RTD-A) at the University of Trento, affiliated with the Department of Civil, Environmental and Mechanical Engineering. He also contributes to the Department of Physics through teaching and research. His work focuses on advanced antenna array design, quantum computing applications in electromagnetics, and modular phased array architectures. Key research areas include tolerance analysis of reconfigurable systems, compressive sensing techniques for antenna characterization, and optimization strategies for next-generation wireless communication systems. He teaches courses such as Antenna Theory and Synthesis Methods (Civil Engineering) and Quantum Electromagnetics (Physics), emphasizing theoretical foundations and practical software applications. His research leverages quantum computing for solving complex electromagnetic problems and explores novel array configurations for low Earth orbit (LEO) satellite communications and urban wireless networks. Anselmi’s recent work highlights advancements in interval arithmetic for robust array tolerance analysis, Bayesian compressive sensing for microwave imaging, and self-replicating tiling techniques for modular array design. His publications span IEEE journals and conferences, addressing topics like electromagnetic environment optimization, sparse array synthesis, and AI-driven antenna optimization. Though no scientific awards are explicitly mentioned, his contributions reflect cutting-edge innovations in electromagnetics and quantum engineering. His research also involves collaborations with the ELEDIA Research Center, focusing on task-oriented reflectarrays and system-by-design methodologies for multi-scale applications. Current interests include overcoming electromagnetic challenges in smart cities and next-generation radar systems.
Olga Saukh is an Associate Professor at TU Graz's Institute of Computer Engineering, leading the Embedded Learning and Sensing Systems (ELSS) group. Her research focuses on resource-efficient AI, on-device learning, and robust sensing systems for IoT and environmental monitoring applications. She holds a Dr.rer.nat. and MSc in Computer Science, with expertise in embedded systems and wireless sensor networks. Her work integrates machine learning with hardware constraints, addressing challenges in energy efficiency, real-time adaptation, and adversarial robustness. Notable projects include PCDCNet for air quality forecasting and SensorFormer for sensor calibration. She has contributed to OpenSense Zurich's air pollution monitoring and automated pollen sensing systems. Her research spans over 50 publications since 2006, emphasizing practical deployments in structural health monitoring, smart agriculture, and urban environmental sensing. She leads interdisciplinary projects combining AI, embedded hardware, and data-driven decision-making.
Stefano Salsano is an Assistant Professor at the Department of Electronic Engineering at the University of Rome Tor Vergata since 2000. He holds a Laurea degree (1994) and PhD (1998) from the University of Rome. His research focuses on advanced networking technologies including Information-Centric Networking, SDN, Segment Routing (SRv6), 5G, and Network Function Virtualization (NFV). He has contributed to numerous EU-funded projects (e.g., INSIGNIA, ELISA, AQUILA) and led research in telecommunications at CoRiTeL until 2000. His work emphasizes scalable network architectures, performance measurement, and programmable data planes. Key projects include the OFELIA testbed, SRv6 implementation, and contributions to standards like RFC 9779. He has authored over 100 publications with an h-index of 17, addressing topics such as network programmability, cloud-native solutions, and hybrid SDN/IP systems. Research highlights include developing the DIDA framework for distributed machine learning, optimizing SRv6 for SD-WANs, and exploring 5G Superfluid Networks for dynamic service deployment. Collaborations include CNIT, Netgroup, and initiatives like the GEANT SDX project.
Chipp Jansen is a researcher at the Materials Science Research Centre within the School of Design at the Royal College of Art. His work focuses on interdisciplinary robotics and AI applications for sustainability, particularly in textile circular economies. He holds a PhD in Robotics from King’s College London and has taught at institutions including King’s College London, Brunel University, City University of New York, Pratt Institute, Cornell University, and the University of Michigan. His research bridges robotics/computer science with art/design through platforms enabling collaborative creation. Key projects include AiLoupe , a material recognition app for designers, and studies on circular supply chains for biomaterials. He advocates for sustainable practices in consumer electronics through hardware re-use and reverse engineering. Dr. Jansen has received funding from the EPSRC for his doctoral work on collaborative drawing systems. Recent publications address textile robotic interaction and designer-robot collaboration, contributing to human-robot interaction research. His work emphasizes practical workflows for artists and circular economy applications.
Raluca Lefticaru is an Associate Professor in Computer Science at the University of Bradford's School of Computing, Software and Artificial Intelligence & Engineering (CSAI&E), within the Faculty of Engineering & Digital Technologies. She leads the BEng Software Engineering programme and holds a visiting researcher position at the University of Sheffield's Testing group. A Fellow of the Higher Education Academy (FHEA), she specializes in software testing methodologies, particularly model-based testing using evolutionary approaches, formal specification, and P systems verification. Her research interests span software testing, model-based testing, search-based software engineering, membrane computing, and formal verification. Recent professional activities include organizing conferences such as YISEC 2023, AIERC 2022, and A-MOST 2021, serving as a program committee member for SEFM 2025, ICTSS 2023, and ICSE 2022, and reviewing for WCCI 2022. She has held roles including Co-chair of YISEC 2023 and Communication Chair of CMC18 (2017). Raluca's work emphasizes interdisciplinary applications, from IoT security to medical imaging analysis. Her publications reflect contributions to testing frameworks for P systems, fault tree analysis, and AI-driven solutions for cyberbullying detection and industrial fire prevention. She actively contributes to academic journals in membrane computing, optimization, and software engineering. Awards: Fellow of the Higher Education Academy (FHEA) Key Projects: IoT safety-security integration, robotic system testing, and COPD self-management systems Conference Leadership: Organized over 10 international conferences since 2017
Wesley Da Silva Costa is a Lecturer-Researcher at the Research Centre Biobased Economy, University of Groningen. His research focuses on Visible Light Communication (VLC), IoT systems, and optimization techniques such as genetic algorithms. He holds a PhD in Electrical and Electronic Engineering from the Federal University of Espirito Santo (2023). Key research areas include improving spectral and power efficiencies in VLC systems, optimizing mesh networks, and applying AI to communication frameworks. His work addresses challenges in low-power wireless networks, handover protocols, and hybrid IoT resource allocation. Recent publications (2021–2025) emphasize VLC system enhancements, IoT integration, and AI-driven solutions for industrial and healthcare applications. Collaborations span topics like chronobiological monitoring in extreme environments and sustainable communication technologies aligned with UN SDGs. Notable contributions include low-cost IoT diagnostic tools for tropical/Antarctic environments and optimized OFDM-VLC systems using multi-objective algorithms. His research bridges theoretical advancements with practical implementation in smart grids and medical monitoring.
Dr. Abdulaleem Al-Othmani is a Senior Lecturer in Computer Science at De Montfort University (DMU), serving as Programme Manager for APU/DMU dual award computing programmes. He holds a PhD in Computer Science from Universiti Teknologi Malaysia (UTM) and has held academic roles at University Kuala Lumpur (UniKL) and Asia Pacific University (APU) in Malaysia. His research focuses on cybersecurity, including steganography, digital watermarking, data leak prevention, and machine learning applications in security. Education: BSc in Computer Engineering, University of Baghdad (2002) Master of Computer Science (Information Security), UTM (2010) PhD in Computer Science, UTM (2016) Research Interests: Data Leak Prevention frameworks for educational institutions Cybersecurity in IoT and telemedicine systems Machine learning-driven threat detection E-learning security during pandemics Biometric authentication systems for healthcare Awards & Grants: Principal Investigator: RM99,380 FRGS grant for data leak prevention (2020–2022) UTM International Doctoral Fellowship (2011–2012) Certificate of Excellence for PhD thesis (2016) Advising & Professional Roles: Supervised over 20 PhD/Master students and 50+ bachelor dissertations Current PhD supervision: Safari Ismail Mussa (web app vulnerability scanners) External Examiner for MSc programmes at Birmingham City University (2021) Member of IEEE, BCS, ACM, and AIS professional bodies He is affiliated with the Cyber Technology Institute (CTI) at DMU and contributes to editorial boards of journals/conferences.
Peter Denning is a Distinguished Professor of Computer Science at the Naval Postgraduate School (NPS) in Monterey, CA, serving as Department Chair. He has held prominent roles including Professor and Department Chair at George Mason University, Director of NASA's Research Institute for Advanced Computer Science (RIACS), and faculty positions at Purdue University, Princeton University, and MIT. His research focuses on computational thinking, great principles of computing, operating systems, security, performance modeling, and innovation adoption. Denning has contributed to foundational work in virtual memory, working set theory, and queueing networks. He has authored influential books such as The Innovator's Way and Computational Thinking . His honors include IEEE Fellow (1982), ACM Distinguished Service Award (1989), ACM Karlstrom Educator Award (1996), and the IEEE Computer Society Pioneer Award (2021). He has received eight best paper awards across his career. Denning has led NSF-funded initiatives like the 'Resparking Innovation' project and pioneered interdisciplinary education in computing principles. His work bridges theoretical computing foundations with real-world applications in education and innovation leadership.
Dr. Jaime Boal Martín-Larrauri is an Associate Professor at the School of Engineering (ICAI) of Comillas Pontifical University, affiliated with the Electronics, Control and Communications Department. He holds a PhD in Engineering Systems Modeling (2014) and coordinates the M.Eng. in Intelligent Industry since 2019. His research focuses on robotics, computer vision, reinforcement learning, IoT, energy efficiency, and Industry 4.0 applications. He co-founded Stemy Energy (2018–2024) as CTO, developing energy efficiency solutions. Education: PhD in Research in Engineering Systems Modelling, Comillas Pontifical University (2014) M.Sc. in Research in Engineering Systems Modelling, Comillas Pontifical University (2012) Industrial Engineer (Electronics), Comillas Pontifical University (2010) Research Interests: His work integrates hardware-software systems, emphasizing robotic control, energy-efficient IoT platforms, and AI-driven solutions for industrial automation. Key projects include drone detection systems, smart energy grids, and reinforcement learning for industrial robots. Publications & Trends: Recent articles emphasize robotic learning, energy efficiency, and AI interpretability. Notable contributions include reinforcement learning robustness improvements and IoT energy platform architectures. Awards: Multiple Chair for Smart Industry Awards (2021–2024) for outstanding student projects under his supervision Extraordinary End-of-Degree Award (2011) Grants & Labs: Lead projects funded by ENDESA, Ferrovial, MIT, and the Madrid Regional Government. Active in the Institute for Research in Technology (IIT), collaborating on robotics and energy systems. Labs/Teams: Contributes to the IIT’s robotics and IoT research groups, focusing on autonomous systems and smart industry applications.
