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Robert MullinsView profile

Professor

• Computer Architecture
• Secure Machine Learning
• Hardware Accelerators
• +3 more

Robert Mullins is a Professor in Computer Architecture at the University of Cambridge's Department of Computer Science and Technology. He is a Fellow of St. John's College and Director of Studies for Computer Science at St. John's and Peterhouse Colleges. His research focuses on secure machine learning, hardware accelerators, and open-source silicon design through initiatives like the lowRISC Foundation and the Raspberry Pi Foundation. He leads projects in efficient AI hardware, including the OpenTitan project and the ARIA 'Scaling Compute' programme targeting 1000x cost reduction in AI infrastructure. Key research themes include architectural security, FPGA optimization, and ethical AI deployment. Mullins contributes to interdisciplinary initiatives such as the CHIA Centre for Human-inspired AI and the ELIAS Alliance for European AI leadership. His work spans both theoretical advancements and practical applications, including open-source hardware development and educational outreach through the Raspberry Pi Foundation. Recent projects highlight trends in adversarial defense mechanisms, neural architecture search, and hardware-software co-design for energy efficiency. His involvement in global collaborations underscores a commitment to bridging academic research with industry impact.

Kevin LeachView profile

Assistant Professor

• Cybersecurity
• Software Engineering
• Dependable Systems
• +3 more

Kevin Leach is an Assistant Professor of Computer Science at Vanderbilt University's School of Engineering. His research focuses on designing dependable cybersecurity systems and software engineering practices that withstand sophisticated adversarial attacks. He holds a PhD from the University of Virginia (2016), where he received the Louis T Rader Outstanding Research Award. Prior to Vanderbilt, he was a research scientist and lecturer at the University of Michigan. Education: Ph.D. in Computer Engineering, University of Virginia MS in Computer Science, George Mason University BS with Distinction in Computer Engineering and Computer Science, University of Virginia His research investigates two core areas: leveraging hardware capabilities like Trusted Execution Environments for low-overhead security instrumentation, and understanding how developers and operators make decisions in adversarial environments. He has published over 30 refereed articles, 3 of which have received awards. Recent work includes studies on cognitive biases in cybersecurity competitions, AI-driven code assessment, and malware detection techniques. Awards: Louis T Rader Outstanding Research Award (2016) 3 award-winning papers (specific awards unspecified) His research bridges technical security mechanisms with human decision-making processes, emphasizing both system dependability and developer/operator awareness. Current projects include work on federated learning defenses, runtime security optimization for embedded systems, and ethical considerations in crowdsourced data labeling.

Henry KautzView profile

Professor

• Artificial Intelligence
• Pervasive Computing
• Data Science
• +3 more

Henry Kautz is a Professor in the Department of Computer Science at the University of Rochester, where he has held leadership roles including Director of the Institute for Data Science (2014–Present) and Chair of the Department of Computer Science (2007–2014). Previously, he served as Director of Intelligent Systems at Kodak Research (2006–2007), and held academic positions at the University of Washington and AT&T Laboratories. He currently serves as a Fellow of the AAAS, ACM, and AAAI. His research focuses on artificial intelligence, pervasive computing, and data science, with applications in public health monitoring, natural language processing, and social media analysis. He has over 20,000 citations with an h-index of 65 and i10-index of 124. His research interests include data mining social media for disease tracking, grounded language learning through text-video alignment, and knowledge representation systems combining logic and probability. Notable projects include deploying the 'nEmesis' system to prevent foodborne illness via social media analysis and developing tools like OPUS for social media user studies. His work bridges theoretical AI advancements with real-world societal challenges, emphasizing ethical and practical applications of technology. Dr. Kautz has received prestigious awards including the AAAS and ACM Fellowships, reflecting his contributions to advancing AI and computational science. His research trends show a strong focus on leveraging big data and machine learning for societal good, particularly in health surveillance, mental health monitoring, and urban mobility analysis. Collaborations with interdisciplinary teams highlight his commitment to applying AI to solve complex global problems. In terms of leadership, he has directed major initiatives in data science education and research, fostering innovation at the University of Rochester. His career spans academia and industry, with impactful contributions to both theoretical and applied domains of computer science.

Claudio CastelliniView profile

Professor

• Medical Robotics
• Rehabilitation Robotics
• Human-Machine Interfaces
• +3 more

Claudio Castellini is a Professor of Medical Robotics at Friedrich-Alexander-University Erlangen-Nürnberg (FAU), leading the Assistive Intelligent Robotics (AIROB) Lab. He holds a dual role as Deputy Dean for Public Relations and Communication in the Faculty of Engineering. His research focuses on rehabilitation robotics, human-machine interfaces, and machine learning applications in biomedical engineering. Castellini obtained his Biomedical Engineering degree from the University of Genoa and a PhD in Artificial Intelligence from the University of Edinburgh. Prior to FAU, he served as a senior researcher and lab leader at the German Aerospace Centre's Institute of Robotics and Mechatronics. His work emphasizes assistive robotic systems for the disabled, including prosthetic control, exoskeletons, and neural interfaces. He has co-authored over 160 scientific papers and leads projects at regional, national, and European levels. Castellini is actively involved in editorial roles for journals like IEEE Transactions on Neuro-engineering and Rehabilitation and serves on the board of the International Consortium of Rehabilitation Robotics (ICORR). His research spans innovation in prosthetic control algorithms, wearable robotics, and clinical applications of robotics in neurorehabilitation. Key publications include advancements in LSTM-based grip strength prediction, impedance-controlled orthoses, and spinal cord-computer interfaces for paralyzed hand control. His lab’s AIROB innovations aim to bridge clinical needs with robotic solutions, emphasizing user-centric design. Castellini’s contributions also include open-source hardware development and collaborations on neurorobotic interfaces, such as ultrasound-based control systems. He actively engages in public outreach and interdisciplinary research, fostering connections between engineering and clinical practice.

Mea WangView profile

Professor

• Networking systems and algorithms
• Multimedia networking
• Cloud computing
• +4 more

Professor Mea Wang is a faculty member in the Department of Computer Science at the University of Calgary, affiliated with the Faculty of Science. She leads the NetMedia.Sys lab, focusing on bridging computing and networking in systems like multimedia and cloud environments. Her work emphasizes enhancing Quality-of-Service (QoS) for providers and Quality-of-Experience (QoE) for users. Education: Bachelor of Computer Science (Honours), University of Manitoba (2002) Master of Applied Science (MASc), University of Toronto (2004) Doctor of Philosophy (PhD), University of Toronto (2008) Research Interests: Networking systems, multimedia streaming, cloud computing, distributed systems, extended reality (XR), data science, and accessibility technologies for neurodivergent populations. Her lab develops open-source tools like iStream and collaborates with industry partners such as Cybera and AT&T. Recent Research Directions: Digital accessibility for physical spaces, AR/VR systems for nonspeaking autistic individuals, and optimization of multimedia distribution in heterogeneous networks. Her work spans over 60 publications in top conferences/journals, with a focus on practical implementations and industry impact. Awards: University of Calgary Research Excellence Chair (2024) Parex Innovation Fellowship (2023) Order of the University of Calgary (2022) PEAK Scholar Award (2019) Labs & Teams: Director of the NetMedia.Sys lab, which houses advanced infrastructure including server clusters, IoT devices, and extended reality gear. Current projects include digital twins, immersive education tools, and SDN-based streaming optimizations.

Gerald AdamsView profile

Adjunct Professor

• Interventional Cardiology
• Cardiovascular Medicine
• Clinical Cardiology
• +3 more

Gerald Adams, MD, is an Adjunct Professor in the Department of Medicine at Queen’s University. He joined the faculty in 1990 as an interventional cardiologist and pioneered the Percutaneous Coronary Intervention (PCI) program at KHSC. In 2000, his team became the first in Ontario to offer 24/7 Primary PCI for STEMI. Dr. Adams has held leadership roles including Division Chair, Cardiology Service Chief, and postgraduate training Program Director. He remains clinically active in the PCI lab, inpatient services, and outpatient stress testing. His research interests span interventional cardiology, cardiovascular medicine, and healthcare administration. Recent scholarly work focuses on software engineering advancements, including cybersecurity protocols, AI-driven bug fixing, and blockchain smart contract analysis. Dr. Adams has contributed to over 15 peer-reviewed articles since 2020, addressing topics like MCP server security, semantic versioning of language models, and swarm robotics optimization. His interdisciplinary research bridges clinical practice and computational innovations.

• Cloud Computing
• Distributed Systems
• High-Performance Computing (HPC)
• +12 more

Antony Chazapis is a postdoctoral researcher at the Computer Architecture and VLSI Systems Lab (CARV), Institute of Computer Science, Foundation for Research and Technology - Hellas (FORTH-ICS), and a visiting instructor at the Computer Science Department, University of Crete. He holds a PhD from the National Technical University of Athens (2009) and has extensive experience in both industry and academia, focusing on distributed systems, cloud computing, and high-performance computing (HPC). His research interests span Cloud-Native Architectures , Kubernetes , Containerization , Microservices , DevOps , MLOps , and AI/ML acceleration . He actively works on integrating cloud technologies with HPC, aiming to build next-generation European supercomputing and cloud infrastructures. The most recent publications highlight a strong trend in Kubernetes-HPC convergence , cloud-native workflows , and containerized HPC environments . His work explores orchestration, isolation, performance optimization, and runtime frameworks for heterogeneous accelerators, indicating deep engagement in modern distributed system design. He teaches the postgraduate course CS-548: Cloud-native Software Architectures , covering containerization, microservices, serverless computing, and advanced Kubernetes internals. Students engage in hands-on exercises and projects related to scaling, CI/CD, and cloud service integration. Antony Chazapis contributes to European research initiatives focused on unifying cloud and HPC technologies. He is also a creator and contributor to various open-source projects, demonstrating strong community engagement and practical software development skills.

• Aerospace Engineering
• Optimal Control Theory
• Air Traffic Management
• +5 more

Manuel Fernando Soler Arnedo is a Full Professor in the Aerospace Engineering Department at Carlos III University of Madrid's College of Engineering. His research focuses on Aerospace Engineering with specialization in Optimal Control Theory , Climate Impact Mitigation , and Artificial Intelligence applications for air traffic systems. He leads the Aerospace Engineering Research Group and has contributed extensively to Flight Trajectory Optimization , Weather-Induced Uncertainty , and Network-scale Conflict Resolution . Principal Researcher on EU-funded projects like F4EClim (2024-2027) and KAIROS (2023-2026) Key international collaborations with NEXTOR (UC Berkeley) and ETH Zurich Developed tools like CLIMaCCF V1.0 and ROOST V1.0 for climate-aware flight planning His work integrates Artificial Intelligence with Climate Modeling to address 4D Trajectory Planning , Thunderstorm Avoidance , and Non-CO2 Emission Reduction in aviation. Recent publications emphasize Robust Optimization under meteorological uncertainty and Deep Learning for traffic flow management. He has supervised theses on Data Science for Weather Mitigation and Multi-objective Space Mission Design , with grants from European Commission , Boeing , and Spanish government agencies .

• Computer Networks
• Software-Defined Networking (SDN)
• Telecommunications
• +5 more

José Manuel Arco Rodríguez is an Associate Professor in the Department of Automation at the Universidad de Alcalá (Spain). He holds a Doctorate from the same institution for his thesis Propuesta de optimización de la interconexión de redes con calidad de servicio para aplicaciones multimedia (2000), supervised by Dr. Daniel Meziat Luna. His research focuses on intelligent networks, software-defined networking (SDN), edge computing, and telecommunication systems, with particular emphasis on network optimization, protocol design, and AI integration in network architectures. He leads the NetIS research group (Networks and Intelligent Systems), exploring cutting-edge solutions for scalable, reliable data center networks and industrial IoT ecosystems. Key research areas include in-band network control, hybrid SDN architectures, multi-hop edge computing with IoT devices, and low-latency bridging protocols. His work spans theoretical frameworks to hardware implementations (e.g., NetFPGA), with a strong emphasis on practical applications in data centers, campus networks, and industrial environments. Recent contributions address AI-driven network management, plug-and-play routing protocols, and zero-configuration network architectures. Publications highlight advancements in SDN topology discovery (TEDP), scalable addressing (GA3), and path exploration protocols (ARP-Path, All-Path Bridging). His research bridges theoretical networking principles with real-world deployment challenges, often emphasizing interoperability between legacy and modern systems. Arco Rodríguez has collaborated on EU-funded projects and contributed to international standards for network protocols. His lab (NetIS) actively develops open-source tools for network analysis and simulation. Current research trends include AI-enhanced softwarized networks and cloud-edge continuum architectures for IIoT.

Elisa Rojas SánchezView profile

Professor

• Networking
• Software-Defined Networking (SDN)
• Edge Computing
• +7 more

Elisa Rojas Sánchez is a tenured professor at the University of Alcalá, affiliated with the Department of Automation within the School of Telematics Engineering. Her primary research focuses on advanced networking technologies including Software-Defined Networking (SDN), edge computing, IoT integration, and network architecture optimization. She leads the NetIS research group (Networks and Intelligent Systems), exploring innovations in programmable networks and intelligent systems for future communication infrastructures. Her academic background includes a doctoral thesis on high-performance transparent Ethernet switch architectures. She has contributed significantly to protocols like ARP-Path and Torii-HLMAC, advancing scalable routing and fault-tolerant data center designs. Her work bridges theoretical networking research with practical implementations in 6G, industrial IoT, and cloud-edge continuum systems. Recent publications highlight breakthroughs in data-driven protocols (e.g., BareFlow), AI-driven fault prediction in smart grids, and topology-aware resource management in dense networks. She also explores educational innovations like gamification in engineering teaching and hybrid SDN methodologies. Key Research Themes: SDN protocols, edge computing frameworks, IoT scalability, network resilience, AI in networking Notable Achievements: Developed open-source tools like NetIDE, contributed to OpenFlow standards, and pioneered multi-path routing algorithms Her work frequently addresses real-world challenges such as latency reduction in programmable ASICs (Tofino P4), secure in-band control channels, and collaborative resource-sharing in edge environments. She actively participates in international conferences as a program chair and continues advancing the next generation of network architectures.

• Artificial Intelligence
• Machine Learning
• Multimodal Models
• +4 more

Dr. Silvio Savarese is an Adjunct Professor in the Department of Computer Science at Stanford University. His research focuses on advancing artificial intelligence, particularly in multimodal models, autonomous agents, and large language models (LLMs). He has contributed to foundational work in vision-language models like BLIP3 and XGen, as well as frameworks for training action models and optimizing AI agents. His projects emphasize practical applications such as CRM systems, code generation, and ethical AI. Current interests include scalable reasoning in LLMs, efficient model architectures, and multimodal pretraining for 3D understanding. Key research directions include developing unified multimodal models capable of handling vision, language, and point cloud data, as seen in projects like ULIP and Merlion. He explores agent systems through benchmarks like Behavior-1K and BOLAA, aiming to improve real-world interaction capabilities. Recent work addresses challenges in data generation (Text2Data), agent optimization (PRACT), and safety through methods like LZ Penalty for text repetition control. His contributions span open-source libraries (LAVIS, OMNIXAI) and datasets (DialogStudio, Eye-BEHAVIOR), emphasizing reproducibility and community impact. While no formal awards are listed, his extensive publication record and industry collaborations highlight academic and industrial relevance. Current projects include high-fidelity video synthesis (xGen-videosyn-1), time series forecasting (Moirai-MoE), and lightweight agent frameworks (AgentLite).

Frank Kagan GürkaynakView profile

Researcher

• Energy-Efficient Microelectronics
• Cryptographic Hardware Security
• Digital Integrated Circuit Design
• +4 more

Frank Kagan Gürkaynak is Director of the Microelectronics Design Center (DZ) and a Researcher at ETH Zurich's Department of Information Technology and Electrical Engineering (D-ITET). He leads the PULP open-source hardware project and works closely with Prof. Luca Benini in the Integrated Systems Laboratory (IIS). His academic journey includes BSc/MSc from Istanbul Technical University and a PhD from ETH Zurich. Roles: Microelectronics Design Center Director, Senior Scientist in IIS, VLSI course lecturer Research focuses on energy-efficient digital circuits, cryptographic hardware security, and open-source processor architectures. Key projects include EU-funded initiatives like European Processor Initiative (EPI), Convolve, and NeuroSoC, along with SNSF grants Tiny Trainer and PEDESITE. Active in teaching VLSI design, embedded systems, and essential engineering skills. Publications emphasize secure cryptographic accelerators, low-power processor clusters, and GALS system design methodologies. Contributions include energy-efficient ASICs for IoT to HPC domains and pioneering work in side-channel attack-resistant hardware.

Ibraheem Al-DhamariView profile

Researcher

• Trustworthy AI
• Deep Learning
• Computer Vision
• +3 more

Ibraheem Al-Dhamari is a postdoctoral researcher in the Software Engineering Institute at the University of Koblenz, Germany. He holds a PhD in Computer Science supported by DAAD scholarships, alongside MSc and research grants from DAAD. His primary research focuses on Trustworthy AI, Deep Learning, Medical Image Analysis, and Cellular Automata, with applications in healthcare imaging and data protection. He has contributed to projects like medical image registration algorithms and cochlear implant analysis. Al-Dhamari's academic journey includes postdoctoral work at the Institute of Software Engineering (Department 4), and he previously belonged to the Arbeitsgruppe Paulus (Active Vision Group). His work bridges computer science and medicine, emphasizing practical tools for clinical imaging challenges. He actively mentors students seeking thesis opportunities in AI and medical imaging through DAAD-funded programs. His achievements include developing ultra-fast algorithms for medical image analysis and pioneering multi-modal imaging fusion techniques. He maintains an active GitHub profile showcasing repositories like medical-image-registration-course and tutorials on deep learning and recursion. Al-Dhamari is affiliated with organizations such as the International Data Spaces Association and contributes to open-source software for medical research. Key awards include DAAD scholarships for MSc (2007), short research (2008), and PhD (2012). His research has led to innovations in cochlear duct measurement, cervical spine analysis, and cellular automata-based data mining. He remains a sought-after collaborator in interdisciplinary projects at the intersection of AI and healthcare.

• Neuromorphic Computing
• Reservoir Computing
• Reinforcement Learning
• +3 more

Prof. Abigail Morrison is a Professor and Group Leader of the Computation in Neural Circuits group at the Institute for Advanced Simulation (IAS-6), part of Forschungszentrum Jülich. Her work focuses on advancing neuromorphic computing, reservoir computing, and spiking neural network simulations. She leads development of the NEST simulator and NESTML modeling language, tools critical for large-scale brain modeling. Key research areas include: Neuromorphic hardware-software co-design Biophysically plausible neural network models GPU-accelerated simulation frameworks Multi-scale brain co-simulation techniques Applications in embodied AI and neuroscience Her lab contributes to the European EBRAINS infrastructure and has pioneered methods for parallel GPU-based network construction. Recent work explores topographic neural circuit architectures for signal processing and reinforcement learning in neuromorphic systems. Notable achievements include: Development of NESTML (v8.0+) ODE-toolbox for ODE solver selection Co-design of HNC neuromorphic compute nodes Advances in dendritic computation modeling Current efforts emphasize exascale computing readiness, neuromorphic system validation, and bridging biological plausibility with computational efficiency in neural network simulations.

Johanna SenkView profile

Researcher

• Spiking Neural Networks
• Neuromorphic Computing
• High-Performance Computing
• +3 more

Dr. Johanna Senk is a Team Leader of the Future Simulation Architectures team at the Institute for Advanced Simulation (IAS-6), part of Forschungszentrum Jülich GmbH. Her research focuses on spiking neural networks, neuromorphic computing, and high-performance computing, with an emphasis on simulation technology and reproducible science. She leads efforts to develop scalable architectures for large-scale neuronal network simulations, particularly leveraging GPU-based systems and neuromorphic hardware. Her work bridges theoretical neuroscience and computational engineering, addressing challenges such as network connectivity design, metadata standardization for scientific workflows, and optimizing simulation efficiency. Key contributions include the development of the NNMT toolbox for mean-field analysis and the beNNch framework for performance benchmarking. Senk’s team collaborates extensively on multi-area cortical models and has published extensively on topics like GPU-accelerated neuronal network construction, synaptic dynamics modeling, and the reconciliation of spiking activity with local field potentials. Her research aims to advance both computational methods and biological understanding of neuronal systems.