Professor Dave Cliff is a faculty member at the University of Bristol , affiliated with the School of Engineering Mathematics and Technology and the Intelligent Systems Laboratory . His career spans academia and industry, including roles at MIT, University of Sussex, and Deutsche Bank. He specializes in complex adaptive systems and automated trading systems , with significant contributions to evolutionary robotics , market mechanism design , and large-scale socio-technical systems . Academic Director for TQC at University of Bristol (since 2007) Director of LSCITS Initiative (2005-2014) Consulting for UK Government Foresight unit and Futurelab His research explores the intersection of artificial intelligence , complex systems , and computational modeling , focusing on evolutionary dynamics in biological systems and algorithmic trading in financial markets. Recent publications analyze species coexistence stability through spatial cyclic games and develop multi-agent stock exchange simulators for arbitrage studies. Scientific Recognition : Delivered Isambard Kingdom Brunel Award Lecture (1993) BBC documentary 'The Joy of Logic' (2013, Grierson Award-nominated) Cliff actively engages in public science communication , working with GCSE Science Live and Maths Inspiration to promote STEM to students. His expertise in automated trading was validated by IBM researchers in 2001 when his 'ZIP' algorithm outperformed human traders.
Maria Letizia Marchegiani is an Assistant Professor at the University of Parma , affiliated with the Department of Engineering and Architecture . Previously, she held academic positions at Aalborg University (2019) and Oxford Robotics Institute (2014-2018). Education: PhD in Computer Science and Engineering from Sapienza - University of Rome , MSc/BEng in Computer Engineering Her research interests span signal processing , machine learning , and their applications to robotics , autonomous systems , intelligent transportation , and intelligent healthcare . She explores intersections between auditory perception , cognitive modeling , and energy-efficient wearable systems . Recent publications demonstrate expertise in acoustic event localization , ML-SDWSN architectures , thermal camera integration for vehicles, and privacy-preserving wearable systems . Her work addresses challenges in network reliability , urban soundscapes , and human-robot collaboration .
Luciano Castillo is a Professor at the School of Mechanical Engineering within the College of Engineering at Purdue University . His research spans turbulent boundary layers, wind energy, renewable energy integration, and bio-inspired engineering, with a focus on societal impacts such as energy-water nexus and social equality. Turbulent Flow Modeling with emphasis on initial conditions and micro-surfaces Wind Energy optimization and boundary layer interactions Renewable Energy Integration with water and thermal storage Biomedical Engineering applications in respiratory flow studies His recent publications explore robotics for classroom safety, mangrove-inspired erosion prevention, and renewable-powered desalination. Awards include the Alumni Distinguished Career Award (2023), ASME Fellow (2013), and multiple best paper awards. He leads initiatives like the US-Mexico Energy Corridor and contributes to interdisciplinary labs focusing on energy and societal challenges.
Dr. Lydia Ray is a Professor at the TSYS School of Computer Science , Columbus State University, with a Ph.D. in Computer Science from Louisiana State University (2005) and an M.Stat in Statistics from Indian Statistical Institute (1998). She specializes in Wireless Sensor Networks , Wireless Network Security , RFID Systems , and Computer Science Education . Research Interests: Secure energy-efficient data transmission in Wireless Sensor Networks RFID security and privacy mechanisms Virtual network labs for online education Teaching: Graduate courses: Advanced System Security, Computer Forensics, Wireless Security Undergraduate courses: Data Structures, Introduction to Programming, Information Technology Education Outreach: Active8 Summer Camps (Scratch, Pico Cricket, Alice, Lego Robotics) Future Teachers’ Academy (Cybersecurity, Computer Networks) Computer Science Academy workshops Contact: ray_lydia@columbusstate.edu | Office: CCT Building Room 429
Carlo Alberto Avizzano serves as Associate Professor in Robotics and Automation at the University of Pisa's School of Engineering, Department of Information Engineering. He coordinates the Department of Excellence in Robotics & Artificial Intelligence (MUR) and leads the Intelligent Automation System Research Group. Research spans robotics, human-robot interaction, computer vision, and control systems Specializes in creating intelligent automation systems with cognitive capabilities Integrates AI, machine learning, and mechatronics for robust autonomous systems His research focuses on developing robots that learn from human examples, adapt to changing environments, and interact through advanced perception systems. Current work emphasizes wearable robotics, UAVs, and industrial automation solutions with applications in medical rehabilitation, firefighting, and manufacturing. He employs distributed computing architectures integrating sensors, real-time control, and knowledge transfer algorithms. Publications reveal strong emphasis on practical implementations: 15 recent works cover exoskeleton design (2024), UAV firefighting systems (2024), industrial bin-picking datasets (2024), and haptic interfaces (2012-2023). Key trends show progression from virtual reality systems (2006-2008) toward modern AI-integrated robotics with industrial and medical applications. Teaching responsibilities include PhD courses in Sensors for Construction, Python Programming for HealthScience, and Digital Perception; plus undergraduate Mechatronics and Computer Vision labs. He serves on PhD boards for Emerging Digital Technologies and Health Science Technology. Extensive patent portfolio including haptic interfaces (2012), sailing simulators (2006), and UAV systems (2024) Research directly translated to commercial products and spin-off companies
Berta María Guijarro Berdiñas is a Researcher in the Department of Computer Science and Artificial Intelligence at the University of A Coruña , Spain. She is affiliated with the Laboratory for Research and Development in Artificial Intelligence and teaches courses like Machine Learning , Development of Intelligent Systems , and Programming at both undergraduate and postgraduate levels. Research Focus: Her work lies at the intersection of Artificial Intelligence , Machine Learning , and Knowledge-Based Systems . Key contributions include frugal learning (limited data), anomaly explanation , and distributed learning for edge devices. She applies these to areas like health informatics , forest fire management , and human-robot interaction . Recent Publications span explainable AI , anomaly detection , multi-agent systems , and low-power machine learning . Her articles appear in top venues like Expert Systems with Applications and IEEE Transactions on Neural Networks and Learning Systems . Grants & Projects include EU-funded initiatives, Spanish Ministry of Science grants, and regional collaborations. She focuses on AI for healthcare , smart systems , and distributed learning .
Paul Kotyczka is a Professor at the Technical University of Munich (TUM) in the School of Engineering and Design , Department of Automatic Control Engineering. He leads the Energy-based Modeling and Control Working Group and focuses on modeling, geometric discretization, and control of multi-physical systems, with expertise in nonlinear and passivity-based control. His work spans applications in robotics, mechatronics, and process engineering. Education : Dipl.-Ing. in Electrical Engineering (TUM, 2005), Dr.-Ing. (TUM, 2010), Habilitation (Dr.-Ing. habil., TUM, 2019). Research : Core areas include port-Hamiltonian systems, predictive control of active chassis, structural mechanics modeling, and numerical methods for control. His projects address autonomous driving, distributed parametric systems, and passivity-based control of switching nonlinear systems. Awards : Held a Marie Sklodowska-Curie Fellowship (2015–2017). Grants : Leads DFG projects (e.g., HermInE, INFIDHEM), MSCA-IF, and Franco-German Doctoral Program on port-Hamiltonian systems. Labs : Head of the Energy-based Modeling and Control group at TUM, collaborating internationally (e.g., IIT Bombay, Grenoble INP, LCIS France).
Spyros Reveliotis is a Professor at the Stewart School of Industrial & Systems Engineering within the College of Engineering at Georgia Institute of Technology. His work bridges theoretical advancements with practical applications in automation and control systems. Education : PhD in Industrial Engineering (University of Illinois at Urbana-Champaign), B.Sc. in Electrical Engineering (National Technical University of Athens), M.Sc. in Computer Systems Engineering (Northeastern University) Reveliotis focuses on discrete event systems theory , emphasizing control of flexible automation and traffic management for multi-agent systems. His research integrates machine learning and Markov decision processes to optimize scheduling and coordination in complex environments like robotics and manufacturing systems. Recent trends in his publications address deadlock avoidance , min-time coverage in constrained spaces, and liveness enforcement for transport systems. These works often leverage combinatorial optimization and graph theory for scalable solutions. Scientific Awards : IEEE Fellow As a core faculty member of the Institute for Robotics and Intelligent Machines (IRI) , Reveliotis contributes to interdisciplinary robotics research. His affiliations with professional societies like INFORMS reflect his impact on operations research and automation fields.
Michael M. Zavlanos is the Yoh Family Professor in the Thomas Lord Department of Mechanical Engineering and Materials Science at Duke University's Pratt School of Engineering. He also holds secondary appointments in the Department of Computer Science and the Department of Electrical and Computer Engineering. Currently serving as the Director of the Healthcare Systems Optimization program with Duke AI Health and as an Amazon Scholar with Amazon Robotics, his academic career spans control theory, optimization, and artificial intelligence with applications across multiple domains. Dr. Zavlanos received his educational foundation from prestigious institutions: Diploma in Mechanical Engineering from the National Technical University of Athens (NTUA), Greece (2002) M.S.E. in Electrical and Systems Engineering from the University of Pennsylvania (2005) Ph.D. in Electrical and Systems Engineering from the University of Pennsylvania (2008) His research program spans multiple interconnected domains, with a strong foundation in control theory, optimization, and learning methodologies . This theoretical work directly enables applications in robotics and autonomous systems , where his team develops algorithms for multi-robot coordination, motion planning under complex constraints, and network connectivity maintenance. A significant portion of his work addresses networked and distributed control systems , focusing on how multiple agents can coordinate effectively with limited communication. More recently, he has expanded his research into cyber-physical systems with healthcare applications, leveraging his expertise to optimize healthcare delivery systems through the Duke AI Health initiative. Dr. Zavlanos' work demonstrates a consistent trajectory from theoretical foundations to real-world applications. His early work established fundamental principles for maintaining connectivity in mobile robot networks, which evolved into more sophisticated approaches for temporal task planning and risk-averse decision making in uncertain environments. The most recent phase of his research integrates machine learning with traditional control theory to address complex healthcare system optimization problems. His significant contributions to the field have been recognized through prestigious awards: Office of Naval Research Young Investigator Program (YIP) Award (2014) National Science Foundation Faculty Early Career Development (CAREER) Award (2012) National Science Foundation Faculty Early Career Development (CAREER) Award (2011) Duke University Distinguished Faculty Rank (2019) Duke University Distinguished Professor designation (2018) As an educator, Dr. Zavlanos has taught courses including ME 627: Linear System Theory, ME 592: Research Independent Study, ECE 391/291: Projects in Electrical and Computer Engineering, and CEE 627: Linear System Theory. His research program has been supported by multiple grants from the National Science Foundation and the Office of Naval Research, enabling him to mentor numerous graduate students and postdoctoral researchers in the development of cutting-edge control and optimization algorithms. Dr. Zavlanos leads research efforts at the intersection of control theory, optimization, and artificial intelligence, with particular focus on translating theoretical advances into practical applications. His recent work with Duke AI Health represents a strategic expansion of his research portfolio into healthcare systems optimization, where he applies his expertise in algorithmic decision making to improve patient scheduling, resource allocation, and operational efficiency in medical settings. Through his Amazon Scholar role, he also contributes to advancing robotics technologies for real-world applications.
Abdelkader Mekhalef Benhafssa serves as a Teacher-Researcher at CESI Engineering School within the Engineering and Digital Tools research team. His work spans industrial engineering, robotics, and sustainable manufacturing systems. Education: Doctorate in Electrical Engineering (2017) Master's degree in Electrical Engineering specializing in Electrical Networks and High Voltage Techniques (2013) His research focuses on optimizing production systems through multi-agent simulations, human-robot collaboration in Industry 5.0 contexts, and energy-efficient manufacturing. Key areas include flow simulation, autonomous vehicle scheduling in logistics, and electrostatic separation techniques for plastic waste recycling. His experimental work examines tribocharging mechanisms and particle behavior in recycling processes. Publications reveal a strong trend toward human-centric manufacturing systems, with recent work (2023-2025) emphasizing collision avoidance algorithms, dynamic scheduling for autonomous vehicles, and energy-conscious production planning. Earlier research (2014-2018) established expertise in electrostatic separation for plastic waste recycling. Supervision & Projects: Supervised Kader Sanogo's 2024 thesis on optimizing transport tasks for collaborative robots in Industry 5.0 Currently supervising Nesrine Hebbadj's research (2024-2027) on human-centered production planning Leading DYNALOG project (2025-2027) on robotic intra-logistics systems His work integrates industrial engineering with environmental sustainability, particularly through advanced recycling technologies for plastic waste and energy-efficient production systems.
Kevin De Pauw is a postdoctoral researcher at the Department of Physiotherapy, Human Physiology and Anatomy at Vrije Universiteit Brussel (VUB). He actively contributes to 12 research projects with a focus on robotics, mental fatigue, brain physiology, and sports physiotherapy. Current projects include Brubotics, APEX, and TBrainBoost Collaboration network spans Belgium, Germany, and Netherlands Key research themes: Mental Fatigue (100%), Robotics (100%), and Prosthetics (52%) Research Interests: His work explores the intersection of brain physiology, fatigue mechanisms, and robotics applications in rehabilitation. He develops predictive musculoskeletal simulations and investigates inter-limb asymmetry in athletes. Article Trends: Recent publications show increasing focus on robot-assisted rehabilitation , brain neuroplasticity , and mental fatigue quantification . Research combines AI-driven wearable robotics with neurophysiological monitoring . Student Supervision: He mentors Master's students in topics related to Lower limb asymmetry analysis Adolescent cognition-fitness relationships Exoskeleton interface design Laboratory Affiliation: Member of Brubotics and TBrainBoost teams at VUB, working on sustainable human-centered robotics and neurocirculation enhancement technologies.
Dr. Savio Fabretti is a Professor at the University of Bielefeld within the Faculty of Physics . He is affiliated with the Ultrafast Science Group and has contributed extensively to terahertz spectroscopy , nanostructured materials , and spintronics . His interdisciplinary work bridges physics and biology education , particularly in giftedness research through roles like Head of the Osthushenrich Center for Giftedness Research at the Faculty of Biology. Research Focus: Terahertz spectroscopy, plasmonic metamaterials, quantum transport in nanostructures, and giftedness diagnostics in science education. Teaching: Active in teacher training, curriculum design, and student laboratory supervision across biology, psychology, and technical disciplines. Labs & Teams: Collaborates with the Ultrafast Science Group and leads initiatives at the Osthushenrich Center for Giftedness Research . Publications highlight trends in terahertz photonics , nanoscale electronics , and interdisciplinary education . Notable projects include teutolab-robotics and Kolumbus-Kids for science outreach.
Paul P. Maglio is a Professor of Management and Cognitive Science at the University of California, Merced, where he is affiliated with the School of Engineering and the Department of Management of Complex Systems. As one of the founders of the field of service science, he has established himself as a leading researcher at the intersection of management, cognitive science, and information systems. His work spans from theoretical foundations of service systems to practical applications of service innovation. Maglio received his bachelor's degree in computer science and engineering from MIT and earned his Ph.D. in cognitive science from the University of California, San Diego. His academic journey reflects his interdisciplinary approach that bridges technical and social sciences. His research interests focus on human-computer interaction, distributed cognition, and service science, with particular emphasis on how technology enables service innovation and value creation. Maglio's work explores how cognitive principles can inform the design of service systems and how service systems can be understood through the lens of complex adaptive systems. His research has practical applications in digital service transformation, service design, and the integration of artificial intelligence in service contexts. Analysis of his recent publications reveals a clear trajectory toward understanding service systems in the age of AI. His work increasingly examines how autonomous technologies transform human-centered service systems, with particular attention to trust in AI systems, digital service transformation, and the ethical implications of data-driven business models. The publications show a consistent focus on service science as an interdisciplinary field that connects management, information systems, and cognitive science. Maglio served as Editor-in-Chief of INFORMS Service Science from 2013 to 2018 and is the lead editor of the Handbook of Service Science, Volumes I and II. He has published over 125 papers across computer science, cognitive science, and service science domains, establishing him as a prolific contributor to these fields. As an educator, Maglio teaches courses including Technology-enabled Service, Foundations of Management of Complex Systems, Service Science, and Service Innovation. His teaching reflects his research interests and commitment to developing the next generation of service science scholars and practitioners. His work with students likely focuses on the practical application of service science principles to real-world business challenges. Maglio directs research that examines the intersection of cognitive science and service systems, with particular attention to how people interact with and through service systems. His work on epistemic actions and distributed cognition provides theoretical foundations for understanding how humans and technology collaborate in service contexts.
Alice Haynes is a Digital Futures Postdoctoral Fellow at KTH Royal Institute of Technology, working on the Felt Connections project under the Division of Media Technology and Interaction Design . She collaborates with Prof. Kristina Höök and Associate Prof. Iolanda Leite to create shape-changing textile interfaces that foster meaningful bodily interactions for children and adults. Education PhD in Engineering Mathematics, University of Bristol (2022) Specialization in Soft Robotics and Haptic Interfaces Her research blends soft robotics, e-textiles, and soma design to develop tactile technologies that prioritize bodily engagement over traditional visual/auditory interfaces. Current work explores: first-person design for scoliosis, symmetry-asymmetry dynamics in bodily interactions, and soma-driven methods that emphasize felt experiences. Key article trends include shape-changing textiles (SMA-actuated smocking, machine embroidery), emotional/therapeutic applications (anxiety relief, social touch), and multisensory integration (audio-tactile mappings, biosignal interaction). Scientific Contributions Recipient of Digital Futures Postdoctoral Fellowship Co-design methodologies for child-centered technology Material-driven evaluation frameworks for e-textiles Embodied interaction paradigms through haptic cushions Alice teaches Human-Computer Interaction Research Seminars (DH2632) and Media Technology and Interaction Design (DM2601) , while actively seeking Master's students for collaborative thesis work.
Francisco Santibanez is a Research Assistant Professor in the Department of Biomedical Engineering at the University of North Carolina. He holds a Ph.D. in Physics from Universidad de Santiago de Chile (2010). His research focuses on experimental physics, biomedical imaging, and non-linear wave propagation in complex media. Since joining the Pinton Lab in 2018, he has investigated ultrasound super-resolution, functional imaging, and shear wave dynamics in soft tissues. His work spans advanced ultrasound techniques, including transcranial imaging, volumetric imaging, and real-time monitoring of neurovascular responses. Key projects include developing sparse ultrasound arrays and addressing image-degrading effects in clinical settings. His contributions extend to interdisciplinary areas like granular dynamics and acoustic sensing for pest control. Notable research trends include advancing super-resolution imaging capabilities and exploring shock wave behavior in biological tissues. His publications reflect expertise in medical imaging modalities, wave propagation modeling, and hardware innovations for diagnostic applications. Labs/Teams: Active member of the Pinton Lab, collaborating on biomedical engineering and medical imaging projects. His work emphasizes translational research with potential for clinical impact in neuroimaging and oncology monitoring.
