Chessa Massimo is a Professor at Università Vita-Salute San Raffaele, specializing in Cardiovascular Diseases within the field of Congenital Heart Disease. His work spans clinical research, interventional cardiology, and medical education, with a particular focus on adult congenital heart disease and transition care for adolescents. Research Interests Dr. Chessa's research explores: Interventional catheterization techniques for congenital heart defects Transition strategies for adolescent CHD patients 3D printing and mixed reality applications in cardiac anatomy Heart failure management in CHD populations Hypertension in pediatric and adult CHD patients Scientific Awards Fellow, European Society of Cardiology (2015-2018) Fellow, Association for European Paediatric and Congenital Cardiology (2014-2017) Fellow, ERN GUARD-Heart European Reference Network Teaching Activities Current teaching roles include: Cardiovascular System Diseases 3 (International MD Program, 2025) Keep Calm and Be Systematic: Practical Approach to Cardiology (2025)
Risto Rajala is a Professor of Service Engineering and Management at the Department of Industrial Engineering and Management, School of Engineering, Aalto University. His research explores system-level changes in technology industries toward service-based value creation, focusing on sustainability, digital transformation, and business models in the circular economy. Research Interests: Management of service systems, digital transformation, service innovation, circular economy, product-service hybridity, healthcare integration. Education: Ph.D. in Information Systems Science. Recent Publications (2019–2025) highlight trends in servitization, IoT-enabled ecosystems, and B2B value creation. Key themes include modularity, stakeholder engagement, and sustainable practices. Scientific Awards include multiple best paper and dissertation honors (e.g., IJOPM 2020 Best Paper Award, Yrjö and Senja Koivunen Awards for supervised theses). He has coordinated research teams and contributed to strategic frameworks in healthcare and industrial settings.
Maurizio Zamboni is a Full Professor at the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin, where he also serves as Student Ombudsman. His academic career spans over three decades with continuous teaching and research contributions in electronics and computing fields. Professor Zamboni's research interests focus on cutting-edge areas including CMOS integrated circuits, computer architecture, quantum computing, semiconductor devices, and VLSI design. His work particularly emphasizes emerging nanotechnologies for digital microelectronic architectures and the design of high-performance or low-consumption processing systems. He has developed expertise in circuit architectures for probabilistic computing, logic-in-memory computing, magnetic devices, and quantum architectures. His recent publications (2021-2025) reveal a strong trend toward quantum computing applications, in-memory processing architectures, and novel approaches to overcoming the memory wall problem. These works span both theoretical algorithm development and practical hardware implementations, with significant focus on quantum annealing, FPGA-based quantum emulation, and memory-mapped processing architectures. Professor Zamboni has been actively supervising PhD students working on quantum computing algorithms, hardware AI accelerators for automotive applications, and quantum-related optimization approaches. He leads research within the VLSILAB Group at DET, focusing on the intersection of nanoelectronics, quantum computing, and advanced computer architectures. His work bridges theoretical computer science with practical electronic design, creating novel solutions for next-generation computing challenges.
Peter Kazanzides is a Research Professor in the Department of Computer Science at the Whiting School of Engineering, Johns Hopkins University, where he joined the faculty in 2002. His research focuses on robotics, medical robotics, augmented reality, and computer-assisted interventions with primary applications in computer-integrated surgery. His educational background includes multiple degrees from Brown University: ScB (1983) in Electrical Engineering AB (1983) in Computer Science ScM (1985) in Electrical Engineering ScM (1987) in Applied Mathematics PhD (1988) in Electrical Engineering Kazanzides is a member of the Robotics, Vision, and Graphics research group and directs the Sensing, Manipulation, and Real-Time Systems (SMARTS) laboratory. His work spans surgical robotics, mixed reality, and systems engineering, with emphasis on computer-assisted surgery in extreme environments including minimally invasive surgery, microsurgery, and space teleoperation. The SMARTS lab develops real-time sensing systems, augmented/mixed reality interfaces using head-mounted displays, high-performance motor control, and sensor fusion technologies, with strong focus on system integration and open-source platforms like the da Vinci Research Kit (dVRK). Analysis of his recent publications (2024-2025) reveals dominant trends in surgical robotics autonomy, augmented reality navigation, force estimation, and digital twin technologies. Key themes include AI-driven task automation, haptic feedback enhancement, real-time instrument segmentation, and simulation environments for surgical training, primarily leveraging the da Vinci Research Kit framework. As director of the SMARTS lab within the Laboratory for Computational Sensing and Robotics (LCSR), Kazanzides leads a collaborative ecosystem including the Computer Integrated Interventional Systems (CIIS) Lab, Advanced Medical Instrumentation and Robotics (AMIRO) Lab, Dynamical Systems and Controls Lab (DSCL), Computer Aided Medical Procedures (CAMP) Lab, Medical UltraSound Imaging & Intervention Collaboration (MUSiiC) Lab, and Photoacoustic & ULtrasonic Systems Engineering (PULSE) Lab. His lab maintains responsibility for the development and support of the open-source da Vinci Research Kit, a critical resource for surgical robotics research worldwide.
Dr. Mingfeng Wang is a Senior Lecturer in Robotics and Autonomous Systems at Brunel University London, affiliated with the Department of Mechanical and Aerospace Engineering within the College of Engineering, Design and Physical Sciences. His research focuses on specialized robotic systems including continuum, legged, soft, precision farming, and miniaturized robots. Chartered Engineer (CEng) with Engineering Council UK Fellow of the Higher Education Academy (FHEA) Member of IEEE, IEEE-RAS, IMechE, and IFToMM Editorial roles: Associate Editor of International Journal of Advanced Robotic Systems (JCR-Q3); Associate Editor of Frontiers in Robotics and AI (JCR-Q2); Editor of Information Processing in Agriculture (JCR-Q1), Biomimetic Intelligence and Robotics (JCR-Q1), and STEM Education Research expertise includes: Continuum Robotics : Design of extra-slender continuum robots (diameter-to-length ratio Legged Robotics : Parallel mechanism-based biped and hexapod robots for extreme environments Miniaturized Robotics : Active locomotion and drug delivery in capsule endoscopes Soft Robotics : Compliant end-effectors and bio-inspired designs Precision Farming : Laser weeding systems and agricultural automation Key scientific awards: BRIEF award (2022) TAROS Best Paper Post Nomination (2022) IFToMM Asian-MMS Best Paper Award (2014) Recent publications focus on: Cochlear implant surgery robotics Passive compliance in train fluid servicing Snake-biomimetic sealing surfaces Parallel kinematic manipulators Capsule endoscope image enhancement Professional services include conference organization (TAROS 2023/2024 Steering Committee; TAROS 2024 Programme Chair) and journal refereeing for IEEE-ASME Transactions on Mechatronics and Scientific Reports.
Kyle T Spikes is an Associate Professor in the Department of Earth and Planetary Sciences at the Jackson School of Geosciences, The University of Texas at Austin. His research focuses on integrating geologic data with quantitative tools for seismic reservoir characterization, emphasizing forward and inverse problems in rock physics, stochastic modeling, and seismic inversion. He works across scales from sub-micron rock samples to surface seismic data, developing effective medium models and numerical techniques to estimate heterogeneous and anisotropic rock properties. His work spans applications in carbonates, shales, and fractured reservoirs, with a strong emphasis on Bayesian methods, stochastic inversion, and machine learning for data analysis. Recent studies include fluid flow effects in porous media, distributed acoustic sensing (DAS), and rock physics modeling of unconventional reservoirs like the Haynesville Shale. He has contributed to CO2 sequestration monitoring through inversion of 3D VSP data at the Cranfield site. Notable trends in his publications include advancements in Bayesian-based rock physics modeling, integration of multi-scale data (laboratory to field scale), and innovative applications of DAS technology for seismic monitoring. His research bridges geophysics, petrophysics, and reservoir engineering, addressing challenges in reservoir characterization and monitoring under varying fluid and stress conditions. Dr. Spikes advises postdoctoral researchers and graduate students in the Jackson School, though specific advisee names are not listed. His work is supported by collaborative projects with industry and academic partners, focusing on practical solutions for subsurface reservoir challenges.
Greg Stitt is a Professor in the Department of Electrical and Computer Engineering at the University of Florida, affiliated with the College of Engineering. His research focuses on reconfigurable computing, FPGA acceleration, embedded systems, and compiler design. He has received notable awards including the NSF CAREER Award (2012-2017) and the Undergraduate Teacher of the Year Award (2014). His work emphasizes elastic computing frameworks, intermediate fabrics for FPGA virtualization, and warp processors for dynamic hardware/software partitioning. Education: PhD, Computer Science, University of California-Riverside, 2007 BS, Computer Science, University of California-Riverside, 2000 Research Interests: Reconfigurable computing, FPGAs, GPUs, and their applications in high-performance computing Compiler optimization and synthesis techniques for embedded systems Elastic computing frameworks for heterogeneous systems Approximate computing and energy-efficient architectures Grants & Awards: National Science Foundation (NSF) grants for elastic computing (CNS-0914474) and intermediate fabrics (CNS-1149285) Recognition for contributions to FPGA-based scientific computing tools Teaching: Current courses include Reconfigurable Computing 2 and Digital Design Past course offerings span embedded systems, compiler design, and hardware architecture Labs & Teams: Active research in FPGA acceleration, novel architectures, and security for reconfigurable systems Contributions to the Novo-G scalable reconfigurable supercomputing project
Yashar Mehmani is an Assistant Professor in the Leone Family Department of Energy and Mineral Engineering at Pennsylvania State University. His research focuses on porous media flow and mechanics, with an emphasis on multiscale computing to bridge microscale physics and macroscale observations. Applications include subsurface energy systems, CO2 storage, and groundwater contamination. He holds a faculty position within the College of Earth and Mineral Sciences and is affiliated with the IEE (Institute for Energy and the Environment). His research interests span computational geomechanics, multiphase flow modeling, and pore-scale to continuum upscaling. Recent work includes developing machine learning-enhanced preconditioning methods for porous media simulations and kinetic theories for bubble dynamics in subsurface systems. He has received a NSF CAREER Award (2022) for integrating computational and experimental approaches in porous material studies. Key Projects: Impact of CO2 Mineralization on Microstructure Evolution, Multiscale Preconditioning Algorithms Grants: NSF CAREER Award (2022), IEE Seed Grants (2023) Dr. Mehmani collaborates with interdisciplinary teams on energy transition challenges. His lab develops advanced numerical tools for simulating subsurface processes at multiple scales, with applications in carbon sequestration and geothermal energy systems.
Abey Campbell is an Assistant Professor in Computer Science at the School of Computer Science, University College Dublin. He holds roles such as Deputy Programme Director for Computer Science, Director of UCD VR Lab, and 1st Year Stage Coordinator. His research focuses on Augmented Reality (AR), Virtual Reality (VR), Mixed Reality (MR), and Multi-Agent Systems with applications in education, healthcare, and human-computer interaction. Campbell has coordinated modules like Augmented and Virtual Reality, Computer Graphics, Game Development, and Mobile Computing. He earned his BSc and PhD in Computer Science from University College Dublin. His work explores touchless interaction technologies, machine learning agents in STEM education, and ethical implications of emerging technologies. Notable contributions include RenderKernel for real-time rendering systems and studies on AR's role in decision support systems. Campbell has secured a grant from Enterprise Ireland for collaborative design documentation and participates in professional activities like peer reviewing for Frontiers in Virtual Reality and IEEE conferences. His collaborative projects include developing AR tools for veterinary training and evaluating immersive VR experiences in nursing education. The UCD VR Lab under his direction focuses on applied research in spatial computing and interactive systems.
Evangelos Papapetrou is an Associate Professor in the Department of Computer Science and Engineering at the University of Ioannina, Greece. He holds a Diploma (1998) and PhD (2003) in Electrical and Computer Engineering from Aristotle University of Thessaloniki. His research focuses on wireless and mobile networks, including mobile ad-hoc networks, opportunistic networks, satellite networks, quality of service (QoS), and network coding. He has contributed to over 50 peer-reviewed publications and actively participates in EU/nationally funded projects. Research interests include: Wireless/Mobile Network Architectures Opportunistic and Social Mobile Networks Satellite Communication Systems Network Coding Techniques Routing Protocol Design His work emphasizes practical implementations of network protocols, with recent trends focusing on ultra-reliable low-latency communication, energy-efficient broadcasting, and protocol optimizations for 5G/IoT environments. He has developed simulation tools like Adyton for opportunistic networks and contributed to privacy-preserving routing solutions. Teaching responsibilities include courses on Computer Networks I and Wireless Networks (2024/25). He maintains active IEEE/ACM memberships and serves on conference review committees.
A. Erdem Sariyuce is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, part of the School of Engineering and Applied Sciences. His research focuses on graph mining, network science, and distributed computing. He holds a PhD from Ohio State University (2015) and a BS from Middle East Technical University (2010). His work explores temporal network analysis, social network dynamics, and algorithm design for large-scale systems. Notable contributions include methods for motif detection, core decomposition, and stream processing in bipartite networks. Sariyuce has received prestigious awards such as the NSF CAREER Award (2023) and the UB Exceptional Scholar—Young Investigator Award (2023). His research is supported by grants including the LDRD Project at Sandia National Laboratories (2016-2017). Education: PhD, Computer Science and Engineering, Ohio State University, 2015 BS, Computer Engineering, Middle East Technical University, 2010 Research interests emphasize graph algorithms, network resilience, and parallel computing. His recent projects include analyzing financial networks, identifying cohesive communities, and developing efficient algorithms for temporal data. His work bridges theoretical foundations with practical applications in social media, cybersecurity, and bioinformatics. Awards: UB Exceptional Scholar—Young Investigator Award (2023) NSF CAREER Award (2023) SEAS Early Career Researcher of the Year (2020) Advising and grants highlight his leadership in collaborative projects, including the NSF-funded Collaborative Research: OAC Core: Fast Tools for Complex Event Detection over Bipartite Graph Streams (2021). His research often involves industry partnerships and government labs, such as Sandia National Laboratories.
Kallol Sett is an Associate Professor in the Department of Civil, Structural and Environmental Engineering at the University at Buffalo (SUNY), within the School of Engineering and Applied Sciences. His research focuses on risk and reliability analysis of civil infrastructure under extreme events, with expertise in uncertainty quantification, multi-hazard resilience, and geomechanics. He leads the Risk and Reliability Research Group, which develops computational tools integrating physics-based and data-driven modeling, stochastic calculus, and high-performance computing. Education includes a PhD from the University of California, Davis (2007), an MS from the University of Houston (2003), and a BE from Jadavpur University (1997). His work is funded by NASA, NSF, USDOT, NIST, and industry partners. Key research themes include probabilistic geotechnical site characterization, stochastic simulation of seismic ground motion, and life-cycle cost-benefit analysis of infrastructure systems. Advising includes mentoring over 10 PhD and MS students, with notable alumni now in academia and industry roles such as Assistant Professors at Embry-Riddle Aeronautical University and Tianjin University. His lab’s recent studies address real-time decision support systems for hurricane-impacted infrastructure, resilience deficit indices, and multi-hazard financial risk assessment of integrated infrastructure systems.
Dr. Daniel Berio is a researcher at Goldsmiths, University of London, specializing in computational models for human-like movement in digital art and robotics. His work bridges computer graphics, cognitive psychology, and robotic manipulation, focusing on stylized stroke generation, graffiti analysis, and kinematic modeling. He collaborates with Frederic Fol Leymarie and Rejean Plamondon, utilizing the Sigma Lognormal model to simulate human handwriting dynamics. Education : Doctoral thesis on AutoGraff (2021), exploring computational understanding of graffiti and calligraphy. Research Themes : Human-like motion in digital art, kinematic reconstruction from static traces, robotic graffiti generation, and perceptual fluency in aesthetic evaluation. Publications : 15+ works since 2015, spanning ACM Transactions on Graphics, British Journal of Psychology, and conferences like MOCO and IROS. Applications : Font stylization tools, synthetic graffiti generation, compliant robot control, and semantic typography systems.
Dr. Kimberly Tam is an Associate Professor in Cybersecurity at the School of Engineering, Computing and Mathematics, University of Plymouth. She specializes in maritime cybersecurity, focusing on ship IT/OT/IoT security, port infrastructure protection, autonomous vessels, offshore renewable energy systems, and smartphone security. She is affiliated with the Alan Turing Institute as the Theme Lead for Marine and Maritime. Her research addresses critical challenges in maritime autonomy, cyber-physical systems, and regulatory frameworks (e.g., IMO MASS). She has supervised 7 PhD students and 7 research staff across multiple projects, contributing to cyber resilience training and risk assessment tools like CERP and MaCRA. Her work emphasizes practical applications, such as penetration testing frameworks (BridgeInsight) and cost-benefit analysis methods for energy infrastructure cybersecurity. Teaching responsibilities include leading modules like Security Operations & Incident Management , Cyber-Physical Systems Security , and unmanned maritime systems operations. She has developed specialized courses in Hong Kong and Sri Lanka, integrating industry-relevant training. Her recent publications (2023–2025) highlight advancements in adversarial AI defense, ransomware mitigation in maritime contexts, and digital twin technologies for port optimization. She collaborates internationally, hosting visiting researchers from China, Turkey, and Norway, and supports early-career professionals through work experience programs.
Peter Anderson is an Associate Professor at the School of Communication , Simon Fraser University . His work focuses on telecommunication policy , emergency communication , and disaster risk reduction using information and communication technologies (ICT) . Education : M.A. in Communication (1977, Simon Fraser University) B.G.S. in General Studies (1973, Simon Fraser University) Anderson’s research explores systemic approaches to emergency communication , including last-mile warning systems , next-generation public safety networks , and space-based communication for disaster resilience. His publications span ICT policy , critical infrastructure protection , and community crisis planning . Recent articles emphasize technology for disaster mitigation (e.g., tsunami alert systems, CAP message brokers for Sri Lanka) and emergency network design . He has collaborated on public safety broadband projects and satellite communication systems for remote areas. Anderson contributes to the Applied Communication and Technology Laboratory and Public Safety Deployable PSBNs research at SFU. His work bridges technology policy , disaster management , and rural communication strategies .
