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Andrea DettiView profile

Professor

• Computer Networks
• Information-Centric Networking (ICN)
• Cloud Computing
• +3 more

Andrea Detti is a Professor at the Department of Electronic Engineering, University of Rome Tor Vergata. His research focuses on computer networks, particularly Information-Centric Networking (ICN), Cloud Computing, and Software Defined Networks (SDN). He has coordinated major EU projects like Fed4IoT and BONVOYAGE, addressing IoT and Intelligent Transport Systems. He serves as Associate Editor for IEEE Transaction on Network and Service Management and has guest-edited special issues on ICN. His teaching includes courses on Internet Technologies, Mobile Wireless Networks, and Cloud Computing, emphasizing hands-on labs with Linux, Cisco routers, and OpenStack. Key projects include leadership roles in EU initiatives such as ICN2020, GreenICN (energy-efficient ICN), and OFELIA (ICN over SDN). He coordinates industrial projects with Telecom Italia and SSI/Finmeccanica on publish-subscribe paradigms in MANET and DTN. His research spans ICN scalability, adaptive video streaming, and satellite communication optimizations. Publications (80+) cover ICN architecture, SDN integration, and network performance modeling. He actively participates in conferences and standardization efforts, contributing to the evolution of future Internet architectures.

• Operations Research
• Scheduling
• Machine Learning
• +6 more

BEZOUI Madani is a Researcher-Lecturer at CESI, affiliated with the 'Engineering and Numerical Tools' research team. He holds a PhD in Operational Research from the University of Science and Technology Houari Boumediène (2019), with a focus on multi-objective programming in portfolio optimization. His academic roles include serving as a pedagogical tutor for FISA training courses and heading the 'Data Sciences' program for 5th-year Computer Science Engineers at CESI. His research interests center on Industry 4.0/5.0, optimization of complex systems, machine learning, IoT/BIM technologies, and scheduling. Notable work includes integrating human-centricity and sustainability into digital twin models and advancing hybrid metaheuristics for multi-objective manufacturing optimization. Recent publications (2021–2024) address preference-driven optimization methods, tabu search algorithms, and IoT network vulnerability detection. He has authored a book on Euclidean graph boundaries and contributed to frameworks for flexible job shop scheduling. His ongoing research focuses on decision-maker preference integration in dynamic scheduling under Industry 5.0 contexts. Advising and grants: No specific advising roles or grants mentioned in the CV. His educational activities emphasize pedagogical leadership in data science and operational research. Labs/teams: Active member of CESI’s Engineering and Numerical Tools group, collaborating on IoT, digital twins, and optimization projects.

• Electromagnetic Compatibility (EMC)
• Electrical Engineering
• Embedded Systems
• +3 more

Fabrice Duval is a Researcher-Lecturer and Head of the Technical Research and Transfer Platform at CESI. He holds a Habilitation to supervise research from Rouen University (2016) and a PhD in Electrical Engineering from Université Paris-Saclay (2007). His research focuses on Industrial Performance Optimization, Electromagnetic Compatibility (EMC), and robotics-driven manufacturing systems. He leads the 'Engineering and Numerical Tools' research team and manages the CESI FabLab. His educational activities include teaching Electromagnetism, Electricity, and Embedded Systems to engineering students (1st/2nd years and masters). He has supervised numerous PhD theses, including those on EMC in electric vehicles, motor impedance modeling, and PEEC-based EMI analysis. His work emphasizes practical applications, such as the CoRoT project (2016-2021) improving flexible manufacturing systems with autonomous/collaborative robots. Key research themes include robotics task allocation (e.g., auction-based optimization), digital twin integration for resilient systems, and synthetic data for industrial object detection. His publications span peer-reviewed journals and conferences, addressing topics like magnetic shielding effectiveness in automotive applications and modular mobile manipulator coordination. Awards: While no specific honors are listed, his extensive supervision record and participation in high-impact projects reflect his academic standing. He actively organizes scientific events and contributes to industry-research partnerships. Lab involvement: As FabLab manager, he bridges academic research with hands-on innovation, fostering experimental prototyping in electromechanical systems and smart manufacturing technologies.

Andrea D'AmbrogioView profile

Associate Professor

• Software and Systems Engineering
• Systems and Software Performance Engineering
• Model-Driven Systems Engineering
• +3 more

Prof. Andrea D'Ambrogio is an Associate Professor of Software and Systems Engineering at the Department of Enterprise Engineering, University of Roma 'Tor Vergata' (Italy). He previously held roles such as Assistant Professor of Computer Science and Research Associate at the same university, and contributed to projects in Europe and internationally. His research focuses on software/systems performance, model-driven engineering, business process management, and distributed simulation. He has led over 20 international conferences and initiated workshops like CoMetS and Mod4Sim. He currently serves as President of the Society for Modeling & Simulation International (SCS), and is a member of IEEE, ACM, and INCOSE. Research Contributions: Prof. D'Ambrogio has authored over 150 publications in journals and conferences. His work emphasizes simulation engineering processes, MSaaS (Modeling & Simulation as a Service), and the integration of IoT with business processes. Recent studies address distributed simulation interoperability, pandemic impact analysis on healthcare systems, and low-code simulation frameworks. Leadership & Editorial Roles: He has served as General Chair for major events like SpringSim'19 and SummerSim'18. He is an Associate Editor of the SIMULATION journal and editorial board member of IAENG International Journal of Computer Science. His leadership in SCS advances global standards in modeling and simulation practices. Teaching: Teaches courses such as Service-Oriented Software Engineering, Software Systems, and Internet-Based Distributed Simulation. His academic contributions span both theoretical advancements and practical applications in enterprise systems engineering.

• Constrained Statistical Inference
• GARCH Models
• Extreme Value Theory
• +4 more

Mervyn J. Silvapulle is a Professor in the Department of Econometrics and Business Statistics at Monash University. He holds a B.Sc.(Honours) in Mathematics and a Ph.D. in Statistics from the Australian National University (ANU), awarded in 1982. His research focuses on econometric and statistical methodology, with current interests in constrained statistical inference, GARCH models, and extreme value theory. Past research includes robust statistics, generalized linear models, ridge regression, and minimum distance methods of inference. Education: B.Sc. (Honours) in Mathematics, Ph.D. in Statistics (ANU). Editorial Roles: Editor (Theory and Methods) of the Australian and New Zealand Journal of Statistics, guest editor for special issues on constrained statistical inference, and associate editor for multiple journals, including the Journal of Statistical Planning and Inference and Sankhya. His research spans collaborations with institutions like the Australian Research Council (ARC), Universität St. Gallen, and the European Centre for Advanced Research in Economics and Statistics. He has led or co-investigated projects such as 'Robust methods for heteroscedastic regression models for time series' (2015–2022) and 'Non-parametric estimation of forecast distributions in non-Gaussian state space models' (2009–2012). Grants & Advising: Accepting PhD students since 1995, with a history of securing ARC-funded projects.

• Software Engineering
• Formal Methods
• Model-Driven Development
• +3 more

Alexander Raschke is a Professor at the University of Ulm, affiliated with the Institute of Software Engineering and Compiler Construction. His research focuses on formal methods, model-driven engineering, software safety and security, and abstract state machines. He has authored/co-authored over 50 publications, including works on collaborative modeling frameworks, security analysis techniques, and programming by demonstration. He holds a PhD in Computer Science from the University of Ulm (2009). As an academic, he has organized and chaired conferences such as ABZ (2020, 2021), demonstrating leadership in the formal methods community. His work bridges theoretical foundations with practical applications in software systems, emphasizing safety-critical and self-adaptive systems. Notable contributions include the development of EditQL—a textual query language for evolving models—and frameworks for attack-tree generation in cybersecurity.

Abdul-Akeem SadiqView profile

Professor

• Disaster Management
• Emergency Management
• Public Policy
• +5 more

Abdul-Akeem Sadiq is a Professor and Public Policy Academic Program Coordinator at the School of Public Administration within the College of Community Innovation and Education at the University of Central Florida. His research focuses on disaster management, emergency management, and community resilience, with particular emphasis on equity and human trafficking in disaster contexts. Dr. Sadiq's educational background includes: Joint Ph.D. in Public Policy from Georgia Institute of Technology and Georgia State University (2009) Albany State University (degree not specified) His research interests span disaster management, emergency management, public policy, community resilience, flood risk management, mass fatality management, and human trafficking in disasters. He has conducted significant work on equity in disaster response, including FEMA's COVID-19 funeral assistance funds and flood mitigation funding distribution. His studies often employ network analysis and collaborative governance frameworks to enhance community resilience, with fieldwork in Haiti, Nigeria, and Zimbabwe. Analysis of Dr. Sadiq's recent publications reveals a dominant focus on disaster-related human trafficking patterns linked to major events like hurricanes and the Super Bowl, alongside critical examinations of infrastructure vulnerability (particularly Florida hospitals during floods) and equity gaps in disaster policies. His work consistently integrates network governance perspectives to address systemic resilience challenges. Scientific awards and recognitions: National Science Foundation Enabling the Next Generation of Hazards and Disasters Researchers Fellowship (2014) Dr. Sadiq has secured significant research funding including a National Science Foundation grant (2016) as Principal Investigator studying community flood resilience, and NSF-funded mass fatality management research after the 2010 Haiti earthquake. His collaborative projects frequently involve cross-sector partnerships examining organizational preparedness, policy diffusion, and intergovernmental coordination in crisis contexts. While specific laboratory structures aren't detailed, his research methodology emphasizes network analysis of collaborative governance arrangements, suggesting active engagement with interdisciplinary teams involving emergency managers, floodplain coordinators, and community stakeholders across multiple countries.

Abouzar EstebsariView profile

Associate Professor

• Sustainable Energy Systems
• Smart Grids
• Power System Security
• +4 more

Abouzar Estebsari is an Associate Professor in Civil and Building Services Engineering at London South Bank University (LSBU). He holds roles as Course Director of the MSc Building Services Engineering program and Timetabling Lead of the department. His expertise spans sustainable energy systems, smart grids, and power system security, with a focus on multi-vector energy systems and real-time simulations using tools like Opal-RT. Estebsari has contributed to EU-funded projects (FP7/H2020) and secured grants including £1.03M from Innovate UK as Co-Investigator. Educated at Politecnico di Torino (PhD, 2015), he held postdoctoral and faculty roles there before joining LSBU. He has also been a Visiting Scholar at RWTH-Aachen University (2016) and a Research Scholar at The George Washington University (2019). His research emphasizes low-carbon energy solutions, collaborating with BSRIA LSBU Net Zero Building Centre and the Centre for Civil and Building Services Engineering (CCiBSE). Estebsari's work addresses UN SDGs related to affordable and clean energy and sustainable cities. His 60+ peer-reviewed publications (H-index 21) cover topics like non-intrusive load monitoring (NILM), IoT-enabled smart grids, and energy policy analysis. He has received the 2020 Manby Prize for contributions to ICT/BIM in civil engineering. He advises PhD students and serves on international examination boards, reviews EPSRC proposals, and evaluates EU Marie Sklodowska Curie Actions. His current projects focus on nanogrids, seaport energy resilience, and decision tools for power systems in developing nations.

Umar RazaView profile

Senior Lecturer

• Internet of Things
• Machine Learning
• Wireless Sensor Networks
• +9 more

Dr. Umar Raza serves as a Senior Lecturer in Networking, IoT and Smart Systems at Manchester Metropolitan University's Department of Engineering, where he concurrently manages the Cisco Network Academy. His academic career includes prior lecturing roles in Robotics and Computing at Staffordshire University, with research spanning industrial applications of emerging technologies. His educational credentials include a PhD in Wireless Sensor Networks from the University of Bradford (2014), Postgraduate Certificates in Research Methods and Professional Higher Education from Staffordshire University (2005, 2007), an MSc in Electronics and Computer Systems from Huddersfield University (1995), and a BSc in Engineering Electronics from DeMontfort University Leicester. Dr. Raza's research centers on Internet of Things applications integrated with Machine Learning across industrial, agricultural, and healthcare domains. Current projects address IoT/ML solutions for domicile care monitoring, cognitive impairment assistance, natural disaster early warning systems, and smart farming in Pakistan, with emphasis on practical implementations in real-world environments. His recent publications demonstrate a pronounced interdisciplinary trajectory, particularly at the IoT-Machine Learning nexus for healthcare innovation (cardiac diagnostics, autism support wearables) and agricultural technology. Significant contributions also appear in blockchain scalability, vehicular network security, and 5G propagation modeling, reflecting both theoretical rigor and industry-relevant problem solving. Professional recognition includes: Fellow of the Higher Education Academy (FHEA) Dr. Raza actively supervises two MSc and two PhD candidates while leading multiple funded projects: Principal Investigator for KTP projects with Kindus Solutions (completed) and Trumeter Ltd Project Advisor for KTP with RAIT Ltd Lead researcher on NATO Science for Peace Security grant for natural disaster warning systems Principal Investigator for Ignite National Technology Fund smart farming initiative in Pakistan As Cisco Network Academy Manager, he drives industry-academia collaboration in networking education, developing curricula that integrate cutting-edge IoT and cybersecurity concepts while maintaining strong professional engagement through IEEE, IET, and BCS memberships.

Raúl OrdóñezView profile

Professor

• Nonlinear Control
• Adaptive Control
• Extremum-Seeking Control
• +4 more

Raúl Ordóñez is a full professor and Director of Graduate Programs in the Department of Electrical and Computer Engineering at the University of Dayton’s School of Engineering. He holds a Ph.D. and M.S. in Electrical Engineering from The Ohio State University (2001 and 1996) and a B.E. from Monterrey Institute of Technology. His research focuses on nonlinear control, adaptive systems, extremum-seeking control, and applications in aerospace, robotics, and power systems. Professional highlights include serving as Associate Editor for Automatica since 2006, co-authoring textbooks on adaptive control and extremum-seeking techniques, and holding editorial roles for IEEE conferences. Awards include the Boeing Welliver Faculty Fellowship (2008) and AFRL Summer Faculty Fellowship (2014). He has conducted research collaborations at institutions like Université de Picardie Jules Verne (France) and TU Wien (Austria). Key research areas include control of hypersonic vehicles, industrial robots, scramjets, and power generators. His work integrates advanced control methodologies with practical systems, emphasizing real-time optimization and robustness. Courses taught span control systems, nonlinear dynamics, and adaptive control. Education: Ph.D./M.S. (Ohio State), B.E. (Monterrey Tech) Professional Activities: IEEE Control Systems Society, CCCS Collaborative Center Recent Awards: AFRL (2014), Boeing (2008) Labs/Teams: Collaborates with robotics and aerospace teams at UD and international institutions

Pedro HenriquesView profile

Professor

• Programming Languages
• Compiler Design
• Software Analysis
• +2 more

Pedro Henriques is Professor of Computer Science at University of Minho, where he coordinates the Language Processing group at Algoritmi Research Center. With a PhD in Formal Languages and Attribute Grammars, he teaches compiler design and programming language engineering. His research develops: Formal methods for software analysis Educational tools for programming pedagogy Ontology-driven computational thinking frameworks AI applications in agriculture and healthcare Recent work includes neuroeducation-informed frameworks (OntoCnE) and Programming Cocktails methodology for optimizing cognitive load in code instruction. He has supervised 14 PhD dissertations and authored the foundational text "XML & XSL: da teoria a prática". Current EU projects explore VR cognitive rehabilitation and olive cultivar identification using deep learning.

• Renewable Energy Technologies
• Building-Integrated Photovoltaics (BIPV)
• Smart Cities
• +4 more

Prof. Momir Tabakovic is a Senior Lecturer/Researcher at Technikum Wien, serving as Head of the Competence Area for Renewable Energy Technologies. He specializes in integrating renewable energy systems into urban environments and educational frameworks. His work focuses on building-integrated photovoltaics (BIPV), smart cities, and sustainable energy solutions. He has contributed to projects like the 'Zukunftsquartier' initiative in Vienna, advancing plus-energy neighborhoods and net-zero building standards. His educational background includes a PhD and MSc, with expertise in engineering and renewable energy systems. He has developed BIPV courseware for higher education and professionals, emphasizing practical applications and industry collaboration. Key research areas include smart grid technologies, energy storage, and digital transition strategies in engineering education. His work bridges academic research with real-world implementation, particularly in South Africa and Austria. Notable projects include the Dem4BIPV initiative for educational materials in photovoltaics and participation in the EU-ASCIN Smart Cities Network. He advocates for open labs and mobile labs to enhance postgraduate education and industry partnerships. Current efforts prioritize urban energy systems, renewable integration, and achieving the 2050 energy scenario goals.

Ulaş BELDEKView profile

Assistant Professor

• Control Theory and Applications
• Mechatronics
• Artificial Intelligence
• +3 more

Dr. Ulaş BELDEK is an Assistant Professor at the Department of Mechatronics Engineering, Faculty of Engineering, Çankaya Üniversitesi. He holds a Ph.D. in Electrical and Electronics Engineering from Middle East Technical University (2009) and has been a full-time faculty member since 2002. His research focuses on control theory, mechatronics, artificial intelligence, and renewable energy systems. He has advised 14 master’s theses and contributed to numerous projects, including the development of a central control unit for renewable energy systems. Education: Ph.D., Electrical and Electronics Engineering, Middle East Technical University (2004–2009) M.Sc., Electrical and Electronics Engineering, Middle East Technical University (1999–2001) B.Sc., Electrical and Electronics Engineering, Middle East Technical University (1995–1999) Research Interests: Control systems design and optimization Robotics and autonomous navigation Machine learning applications in energy systems Evolutionary algorithms and optimization techniques Renewable energy systems integration Projects: Development of a Central Control Unit for Renewable Energy Systems Trios Car Electric Vehicle Production

Joseph TimoneyView profile

Professor

• Audio Signal Processing
• Musical Sound Synthesis
• Digital Audio Watermarking
• +3 more

Joseph Timoney is a professor at the Department of Computer Science , Maynooth International Engineering College , Maynooth University. He teaches undergraduate programs in Computer Science and Music Technology, with expertise in audio signal processing, musical sound synthesis, and digital modeling of analog subtractive synthesis. His research spans sound synthesis algorithms, audio watermarking, and ubiquitous music ecosystems.

Dmitry BerensonView profile

Associate Professor

• Robotics
• Motion Planning
• Machine Learning
• +3 more

Dmitry Berenson is an Associate Professor in the Robotics Department and Electrical Engineering and Computer Science Department at the University of Michigan. He holds a B.S. from Cornell University (2005) and a Ph.D. from Carnegie Mellon University (2011). His research focuses on algorithms for robotic manipulation, motion planning, and control, emphasizing integration with real-world systems and open-source distribution. He has received the IEEE RAS Early Career Award and NSF CAREER Award. His academic journey includes postdoctoral work at UC Berkeley (2012) and faculty positions at Worcester Polytechnic Institute (2012-2016). He leads the ARM Lab, exploring topics such as deformable object manipulation, tactile control, and learning-based planning. Teaching responsibilities include courses like ROB 502 (Programming for Robotics), EECS 465 (Algorithmic Robotics), and ROB 520 (Motion Planning). Education: B.S., Electrical and Computer Engineering, Cornell University (2005) Ph.D., Robotics Institute, Carnegie Mellon University (2011) Postdoctoral Research, UC Berkeley (2012) Research Interests: Learning and motion planning for manipulation Control theory and optimization Deformable object interaction Robot perception and tactile systems Key Contributions: Development of algorithms for manipulation under uncertainty Advances in motion planning with contact feedback Integration of learning with classical robotics methods Recent publications emphasize probabilistic modeling, tactile-driven control, and generalization in learned dynamics. His work addresses challenges in cluttered environments, deformable objects, and safe human-robot collaboration.