Iain Bate is a Lecturer in Real-Time Systems and Head of the Department of Computer Science at the University of York. His research focuses on scheduling and timing analysis, systems engineering with optimization of design trade-offs, design assurance, component-based engineering, and managing emergent behavior, particularly in critical systems. University of York, Department of Computer Science Research areas: Real-Time Systems, Mixed-Criticality Scheduling, Multi-Core Architecture Departmental Roles: Head of Department, Research Group Lead (Real-Time Systems) His recent research explores cache-aware scheduling, fault tolerance, and resource stress management in multi-core environments. He has contributed to journals like Microprocessors and Microsystems as an editor and collaborated on projects funded by EPSRC and industry partners such as Rolls Royce. He actively supervises PhD students and leads research initiatives related to wireless sensor networks, task allocation, and system certification for critical applications.
Dr. Anthony McGarry is a Senior Teaching Fellow in Biomedical Engineering at the University of Strathclyde's Faculty of Engineering. With over 50 research outputs spanning two decades, his work focuses on prosthetics, orthotics, biomechanics, and rehabilitation engineering. His research has significantly contributed to understanding prosthetic socket design, gait analysis, measurement reliability, and physical activity in amputees. His research interests encompass a wide range of topics including prosthetics and orthotics, biomechanics, gait analysis, CAD/CAM systems, measurement reliability, physical activity in amputees, rehabilitation engineering, lower limb amputation, microprocessor prosthetics, and 3D printing applications. His work often bridges clinical practice with engineering solutions, focusing on improving patient outcomes through technological innovation. Dr. McGarry's recent publications (2023-2025) demonstrate continued innovation in the field, with work on 3D-printed cranial helmets, vision-based motion capture for gait analysis, and service quality assessment in prosthetics and orthotics. His research shows a consistent trend toward improving measurement techniques, enhancing prosthetic design, and understanding patient experiences. His scientific achievements include: Converge Challenge Competition runner up (2024) PCAD Prosthetic CAD shape capture in a weight bearing environment award (2022) FIA Foundation Research Award Dr. McGarry has been actively involved in research projects including the PCAD project (2023-2025) focusing on prosthetic CAD shape capture in weight-bearing environments, and has supervised three research students. His work on the reliability of measurement systems, particularly goniometers and activity monitors, has been widely cited and has influenced clinical practice. His research group at Strathclyde focuses on developing innovative solutions for prosthetic and orthotic challenges, with particular emphasis on measurement systems, CAD/CAM applications, and patient-centered outcomes. Current projects are exploring how weight-bearing environments affect prosthetic socket design and how emerging technologies can improve clinical outcomes.
Donald Yeung is a Professor and Associate Chair for Undergraduate Education in the Department of Electrical and Computer Engineering at the University of Maryland , with an additional appointment as Affiliate Professor in the Department of Computer Science . His research focuses on Computer Architecture , particularly in memory systems , 3D integration , energy-efficient processors , and parallel processing . He leads projects like Monolithic 3D Integration of CPU and Main Memory and Approximate Computing . Recent work emphasizes ReRAM-based memory architectures , extreme-scale processor design , and micro-fluidic cooling solutions for 3D CPUs. His teaching includes courses like ENE 646: Computer Architecture and ENE 150: Intermediate Programming Concepts . Key achievements include the Best Paper Award at MULTIPROG-2017 and contributions to IEEE Micro and ACM Transactions . His research spans cache optimization , reuse distance analysis , and directory coherence protocols . Current grants include funding for heterogeneous microprocessor parallelism and low-power system design . Advises graduate students Yinuo Wang and Hung-Yu Yeh, and collaborates with teams like the UMIACS Technical Report Group . His lab focuses on memory-centric computing and scalable multicore systems .
Dr. Feras Dayoub is a Senior Lecturer and Chief Investigator at the QUT Centre for Robotics (QCR) , where he co-leads the Visual Learning and Understanding program. He previously served as Chief Investigator at the ARC Centre of Excellence for Robotic Vision (2016-2020) and holds a PhD in Robotics and Computer Vision from the University of Lincoln. Research Focus: Deploying computer vision and machine learning for real-world mobile robotics applications, including autonomous weed control (CRC-P), vision-enabled underwater robots for reef protection (COTSbot/RangerBot), and UAV-based infrastructure inspection. Teaching: Coordinates advanced robotics topics (EGB439) and teaches microprocessor systems (CAB202). His recent publications focus on uncertainty quantification in robotic vision, open-set recognition, and performance monitoring of deployed models. His work has been recognized with multiple awards from the Australian Centre for Robotic Vision and a Google Impact Challenge popular vote award. 2023: Hyperdimensional Feature Fusion for Out-of-Distribution Detection 2023: Class Distribution Shift Prediction for Domain Adaptation 2022: Uncertainty for Open-Set Error Identification 2022: FSNet for Semantic Segmentation Failure Detection Awards include: 2020: ACRV Best-Profile Raising Event 2019: QUT STEM Camp Certificate of Appreciation 2016: Google Impact Challenge People's Choice Award 2015: QUT Vice Chancellor's Performance Award As supervisor, he guides projects on robotic object detection, cross-view localization, and continues to advance visual learning methodologies for real-world autonomous systems.
Giovanni Squillero is a Full Professor in the Department of Control and Computer Engineering (DAUIN) at Politecnico di Torino, Italy. He leads the CAD group (Electronic CAD & Reliability) and serves on Politecnico's Joint Committee for Teaching and Ph.D. Steering Committee (Pure and Applied Mathematics).
David H. Albonesi is a Professor in the Computer Systems Laboratory at Cornell University's School of Electrical and Computer Engineering. His research focuses on power-efficient computer architectures, including reconfigurable systems, accelerator design for deep learning, smart buildings, and silicon nanophotonics interconnects. He has held leadership roles in major conferences like ISCA and MICRO, and serves on editorial boards for IEEE Computer and IEEE Micro. Research interests span adaptive architectures for dynamic power management, sparse matrix/tensor accelerators, and energy-efficient smart building systems. His work bridges hardware-software co-design, emphasizing phase-aware resource allocation and energy minimization. Awards include the IEEE Fellow distinction, NSF CAREER Award, and multiple teaching accolades from Cornell. Over 30 years of industry-academic collaboration has led to innovations in GALS microarchitectures, clustered multi-threaded processors, and thermal-aware scheduling. Key contributions include the CuttleSys reconfigurable multicore framework, MatRaptor sparse matrix accelerator, and foundational work in silicon photonics for on-chip interconnects. Patents cover dynamic core power management and adaptive microprocessor designs.
Răzvan-Virgil Bogdan is an Assistant Professor at the Faculty of Automation and Computer Science, Politehnica University of Timisoara (PUT), with expertise in Embedded Systems , Automotive Software Testing , and Dependability of Computer Systems . His research bridges Internet-of-Things and e-Learning , focusing on reliability, testing, and intelligent environments. University: Politehnica University of Timisoara School: Faculty of Automation and Computer Science Contact: razvan.bogdan@cs.upt.ro | Room B413A Research Focus: Bogdan's work emphasizes system reliability , embedded software quality , and automotive electronics , with projects like GEMSCLAIM (energy-efficient mobile systems) and HURO JCBICS (cross-border educational infrastructure). He also drives industrial collaborations (e.g., AC_G_xBU_Academy with Continental Automotive Romania). Teaching Career: Bogdan has taught courses such as Embedded Systems , Microprocessor Systems , and Advanced Embedded Systems at PUT, blending theoretical rigor with hands-on lab work in the Vector Lab . His pedagogical approach integrates software testing methodologies and energy-aware system design . Scientific Contributions: He has contributed to embedded systems validation, security frameworks for distributed systems (e.g., TD/54 project ), and automotive software tools. His publications span ACTA POLYTECHNICA HUNGARICA , BRAIN: Broad Research in Artificial Intelligence and Neuroscience , and conference proceedings like IEEE Sustainability and SACI. Awards: Mercy Diplomas 2021 Mercy Diplomas 2020 Memberships: IEEE ACM Prospective Students: Bogdan actively seeks undergrad, Masters, and PhD candidates, emphasizing practical research in automotive embedded systems and IoT . His lab provides direct access for project collaboration and discussions.
Riccardo Cantoro is an Associate Professor in the Department of Control and Computer Science (DAUIN) at Politecnico di Torino, where he is a member of the College of Computer, Film and Mechatronics Engineering and the College of Mechanical, Aerospace and Automotive Engineering. He is affiliated with the CAD - Electronic CAD & Reliability Group and the CARS@PoliTO Interdepartmental Center for Automotive Research and Sustainable Mobility. His work bridges academic research and industrial applications through multiple commercially funded projects. Scientific Disciplinary Sector: IINF-05/A - Information Processing Systems ERC Sectors: PE7_4, PE6_2, PE6_11, PE6_12 His research focuses on functional safety, functional testing, and microprocessor testing, with a strong emphasis on embedded systems and reliability. He applies machine learning and formal methods to enhance test efficiency and system robustness, particularly in automotive and safety-critical domains. His work integrates computer-aided design, fault modeling, and resilience assessment in both hardware and AI systems. The recent publications highlight a trend toward data-efficient and intelligent testing methodologies, combining machine learning (e.g., TabPFN, active learning) with traditional electronic design automation. Topics include microcontroller performance screening, CNN resiliency, FeFET device testing, and system-level test optimization, reflecting a cohesive research agenda in trustworthy computing and hardware reliability. Scientific Awards: No awards explicitly mentioned in the provided texts. Advising and Grants: Dr. Cantoro supervises numerous PhD students in Computer and Systems Engineering, focusing on functional safety, test methodologies, and AI for CAD. He leads multiple industry-funded research projects, including collaborations with Infineon Technologies and Dana-TM4 Italia, on topics such as ATPG tools, speed monitor modeling, and power module reliability. His role as Scientific Manager/Head underscores his leadership in applied research and technology transfer. Labs and Teams: He is a core member of the CAD - Electronic CAD & Reliability Group (DAUIN) and contributes to the CARS@PoliTO center, fostering interdisciplinary research in automotive systems and sustainable mobility.
Luciano Ost is a Senior Lecturer and Programme Director of the Computer and Electronic Engineering (CEE) Programme at the University of Leicester. He holds a Ph.D. in Computer Science from Pontifical Catholic University of Rio Grande do Sul (PUCRS), Brazil (2010). His research focuses on enhancing reliability, security, and performance of embedded and life-critical systems through innovative hardware/software co-design approaches. Key areas include fault tolerance in neural networks, radiation effects on embedded systems, and real-time control systems. Prior to Leicester, he worked at the University of Montpellier II (France) as an assistant professor and research assistant. He has authored/co-authored over 100 papers and two books, with notable contributions to soft error reliability assessment frameworks (e.g., SOFIA, gem5-FIM) and embedded system security solutions like BIDS for in-vehicle networks. His research spans topics like FPGA-accelerated intrusion detection (BNN-based), radiation resilience in IoT edge devices, and compiler optimization impacts on multicore reliability. He has conducted extensive studies using Geant4 simulations and virtual platforms for fault injection analysis.
Oana AMĂRICĂI-BONCALO is a Professor at the Computer and Information Technology Department of University Politehnica Timisoara. She holds a Dr. Habil. Eng. degree and has served as Assistant Professor, Lecturer, and Associate Professor since 2009. Her research focuses on reconfigurable systems, system reliability, embedded systems, and forward error correction with FPGA applications. Education: Engineering Degree (2006) and PhD in Computer Engineering (2009), both from University Politehnica Timisoara. She was an invited researcher at University College Cork (2012) and University of Cergy-Pontoise (2016). Since 2017, she has been an Editor for Microprocessor and Microsystems (Elsevier). Research projects include GEMSCLAIM (green energy management in mobile systems). She supervises PhD student Andrei-Bogdan MIHĂILESCU. Recent publications emphasize LDPC decoding architectures, FPGA-based solutions, and reliability assessment in quantum circuits. Notable contributions include innovations in layered decoding algorithms, memory optimization for LDPC decoders, and one-hot data representation techniques. Her work intersects VLSI design, digital signal processing, and embedded systems reliability. Event organization includes a 2024 workshop on audio-video technical solutions and participation in IEEE symposiums. She contributes to academic events like the Mobile Applications Student Contest (SCMUPT).
Joanna F. Defranco is an Associate Professor of Engineering at the Engineering Division (Great Valley) of Pennsylvania State University. Her research focuses on software development, internet of things (IoT), blockchain, and artificial intelligence, with a particular emphasis on quality assurance, security, and practical implementations in engineering and healthcare. Research Interests Defranco's work addresses critical challenges in IoT security, digital twins for manufacturing, and AI-driven software quality analysis. She explores secure data sharing frameworks, blockchain applications in healthcare, and the evolution of low-code/no-code platforms. Her recent publications highlight interdisciplinary approaches to telemedicine, smart agriculture, and urban infrastructure. Publication Trends Her 2023-2025 publications show increasing focus on IoT integration with AI, secure healthcare data systems, and the societal implications of emerging technologies. Key themes include digital twin adoption in SMEs, generative AI's impact on software development, and cybersecurity resilience. Collaborations She collaborates with institutions like IEEE and researchers such as Paul Laplante, Joseph Voas, and Thrasyvoulos Speicher. Her work bridges engineering education with real-world applications in manufacturing, agriculture, and healthcare.
Shubhendu Mukherjee is a Distinguished Engineer at Cavium Networks and Adjunct Professor at the Indian Institute of Technology Kanpur. He is a Fellow of IEEE and ACM, and recipient of the 2009 Maurice-Wilkes Award for outstanding contributions to computer architecture. His career spans leadership roles at Intel and Compaq, where he pioneered fault-tolerant microarchitectures and performance modeling innovations. Education: PhD (1998) and MS (1993) in Computer Science from University of Wisconsin-Madison; B.Tech (1991) in Computer Science and Engineering from IIT Kanpur. Research Interests Mukherjee specializes in computer architecture , soft error modeling , and fault-tolerant design . His work includes Redundant Multithreading (RMT), architectural vulnerability modeling, and on-chip interconnect optimization. Recent publications focus on cache soft error anomalies, quantized AVF analysis, and architectural core salvaging for hard error tolerance. Scientific Awards Maurice-Wilkes Award (2009) IEEE Fellow (2009) ACM Fellow (2011) IEEE Top Picks Awards (2003, 2004) Intel Divisional Recognition Awards (2002–2009) Professional Activities Mukherjee served as General Chair of ASPLOS 2004 , Program Chair of HPCA 2011 , and editorial board member for IEEE Micro, IEEE Computer Architecture Letters, and IEEE Transactions on Dependable and Secure Computing. He also led Intel's SPEARS group (2001–2010), driving architectural innovations in enterprise processors.
Aitor Morillo Rascon is a professional with dual roles in industry and academia. He currently serves as Team Leader at Med-El, leading a 5-member team to develop a Vestibular Processor for US market approval. His work focuses on medical device hardware/firmware design, adhering to standards like Safety, EMC, and Software Lifecycle Management. Since 2024, he has been a Guest Lecturer at Management Center Innsbruck teaching usability and user experience. Earlier, he held teaching roles at UNED (2008-2010), instructing subjects like Algebra, Discrete Mathematics, and Informatics Engineering. Education includes a Dipl.-Ing in Telecommunication (2001-2008) and an MSc in Advanced Electronic Systems (2008-2010) from the University of the Basque Country. Professional certifications include Signal Integrity training (Oxford University, 2023), Requirements Engineering (IREB, 2017), and Medical Device Project Management (Gantus, 2014). Research interests span medical device development, FPGA-based system design, and usability engineering. His publications address topics like vestibular implant systems and fault-tolerant microprocessor architectures in FPGAs. Current projects include a first-in-human clinical trial for vestibular implants.
Gianfranco Michele Maria Politano is an Associate Professor at the Department of Control and Computer Science (DAUIN) at Polytechnic University of Turin, with affiliations to the College of Computer, Film and Mechatronics Engineering and College of Biomedical Engineering. His research focuses on Bioinformatics, Systems Biology, and Deep Learning applications in health. Research trends span computational modeling of biological systems, protein function prediction using machine learning, and public health analysis of disease burdens (influenza, rectal cancer, and COVID-19). He also investigates gene regulatory networks and microRNA roles in inflammation. His teaching includes Bioinformatics and Internship courses for Computer Engineering and Aerospace Engineering students since 2019. He supervises PhD student Sofia Ostellino on computational solutions for disease monitoring and has secured research grants for biostatistics projects like DIDES (exotic animal diagnostics) and rectal cancer ultrasound staging. Notable projects : DIDES (2020), Feasibility study for rectal cancer diagnostics (2021) Patents : Computerized culture protocols for biomanufacturing, Simulation of biological ontogeny
Joel Grodstein is a Lecturer in the Department of Electrical Engineering at Tufts University's College of Engineering. He holds a BSEE from Case Western Reserve University (1981) and an MSCS from the University of Utah (1986). His research spans VLSI design, computer architecture, and interdisciplinary bioelectricity studies, focusing on the intersection of hardware-software systems and biological applications. He teaches courses on real-time embedded systems, parallel computing, bioelectricity, and digital design verification. His career includes roles at Digital Equipment Corporation, Compaq, Intel, and now academia. His recent work bridges computational modeling of bioelectric networks with traditional hardware design, as seen in collaborations with Mike Levin's lab at Tufts. Courses like EE 123 (Bioelectricity) and new offerings like EE 152 (Real-Time Embedded Systems) reflect this dual focus. Publications emphasize symbolic timing analysis, CAD tools for VLSI, and bioelectric systems. He has advised no listed students but collaborates actively with industry partners (e.g., NVIDIA for EE 165). His lab work involves biophysical modeling and synthetic biology projects, as detailed in his recent bioelectricity-related papers.
