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Tarik Graba is a Lecturer at Télécom Paris and a member of the Secure and Safe Hardware (SSH) research team within the Information Processing and Communication Laboratory (LTCI) department. His work focuses on hardware security, embedded systems, and cryptographic implementation. Education: Not explicitly mentioned Current Affiliations: Télécom Paris (Faculty), LTCI, SSH Team His research explores designing secure and reliable integrated systems , with emphasis on managing complexity, power consumption, and flexibility in embedded environments. He contributes to side-channel analysis , lightweight cryptographic algorithms , and hardware-based security mechanisms . The 15 most recent publications highlight his work in lightweight cryptography , hardware security , and embedded system optimization , particularly focusing on RISC-V extensions , side-channel leakage , TRNG circuits , and secure cryptographic processors . Scientific Awards Academic Palms award, Télécom Paris (2021) Tarik Graba collaborates extensively in hardware security research and has advised multiple projects on physical security countermeasures and embedded cryptographic systems . He works with teams like the SSH Laboratory to develop secure hardware architectures.

• Hardware Security
• Embedded Systems Design
• Integrated Circuit Reliability
• +3 more

Renaud Pacalet is a Researcher at Institut Mines-Télécom – Télécom Paris , affiliated with the Communications and Electronics (Comelec) Department and the System on Chip (LabSoc) research team under the Information Processing and Communication Laboratory (LTCI). His work spans hardware security, embedded systems, and software-defined radio (SDR) architectures. Current Research: Hardware security, side-channel attacks (power, timing, fault injection), RISC-V security analysis using gem5, FPGA scheduling for cloud data centers, and model-driven design methodologies. Past Research: Hardware acceleration for ray tracing, SDR front-end processing, SoC security, and memory bus protection (SecBus project). Teaching: Courses on Digital Systems, Computer Architecture, and Hardware Security at EURECOM, including lab sessions on side-channel attacks and fault analysis. Email: renaud.pacalet@telecom-paris.fr Contact: Télécom ParisTech, Campus SophiaTech, 450 route des Chappes 06410 Biot, France

• Hardware Security
• Side-Channel Attacks
• Embedded Systems
• +7 more

Anthony Kelly serves as a Postdoctoral Research Fellow in the Department of Electronic and Computer Engineering within the Faculty of Science and Engineering at the University of Limerick, Ireland, with his office located in E2-006. His affiliation spans both engineering and healthcare domains through interdisciplinary research initiatives. His research demonstrates dual expertise in artificial intelligence applications for healthcare and advanced power electronics. In healthcare AI, he develops interpretable mental health models, diabetes management chatbots, and comorbid condition interventions with emphasis on clinician trust and safety evaluation. In power systems, he pioneers digital control techniques for DC-DC converters, FPGA power management, and machine learning-integrated circuit designs. This bifurcated focus reveals a strategic transition from hardware-centric research (2005-2019) toward AI-health convergence (2024-2025). Analysis of his 15 most recent publications shows a pronounced shift toward healthcare AI since 2024, with 80% of current work addressing mental health modeling, diabetes chatbots, and comorbid condition management. Earlier publications (2009-2019) consistently focused on power electronics innovations including current-sharing algorithms, adaptive controllers, and FPGA-based systems, establishing foundational expertise later applied to healthcare technology development.

• Artificial Intelligence in Healthcare
• Power Electronics
• Digital Control Systems
• +1 more

Freja Stær Hincheli serves as a Lecturer at the Department of Computer Science , University of Copenhagen. Her work intersects multiple domains within machine learning, with a particular emphasis on quantum-inspired algorithms, medical imaging, and sustainable AI development. Keywords : Machine Learning, Quantum Computing, Medical Imaging, Natural Language Processing, Computational Biology Key Collaborations : SCIENCE AI Centre Her research spans quantum-enhanced neural networks, explainable AI for medical diagnostics, and energy-aware model design. Recent publications highlight applications in cross-cultural recipe adaptation, emotion-aware dialogue systems, and climate-conscious AI strategies. The Machine Learning Section at DIKU focuses on theoretical foundations and applications including medical image analysis , biological data modeling , and quantum computing , aligning with her contributions.

• Machine Learning
• Quantum Computing
• Natural Language Processing
• +3 more

Jignesh M. Patel is a Professor in the Computer Science Department at Carnegie Mellon University, where he leads research on efficient data analysis methods. His work focuses on improving both system efficiency (e.g., high-performance data algorithms) and human efficiency (e.g., user productivity with data systems). Research Focus: Patel's group specializes in database systems, query optimization, hardware acceleration, and human-data interaction. Their interdisciplinary work spans: Transactional processing and real-time analytics Query optimization techniques Hardware-algorithm co-design Natural language interfaces for data systems Memory-efficient data processing Professional Activities: Co-founded four technology companies (Paradise, Locomatix, Quickstep, DataChat). Serves on program committees for premier conferences including SIGMOD and CIDR (as co-chair). Teaches database systems courses at CMU. Awards: Received Best Paper Award at DaMoN 2010 for work on cluster efficiency.

• Database Systems
• Query Optimization
• Data Analytics
• +3 more

Karim Cherifi is a Researcher at the Institute of Mathematics , Technical University of Berlin, within the College of Mathematics and Natural Sciences. His academic journey includes a PhD in Control Theory (2015–2019) and postdoctoral work at the Max Planck Institute Magdeburg (2019–2020). Since 2021, he contributes to the ProFIT project "Electric Drives 2.0" at the Werner von Siemens Centre (WvSC). 2010–2013: Bachelor in Electrical and Electronic Engineering 2013–2015: Master in Control Engineering 2015–2019: PhD in Control Theory His research focuses on Control Theory , Numerical Analysis , and Port-Hamiltonian Systems , with applications in Linear Systems , Data-driven Modeling , and Model Reduction . Key trends include geometric formulations for discrete-time systems, dissipativity analysis, and integration of energy-based models with machine learning. Notable scientific recognition includes the DAAD Scholarship (2018) . His work spans publications on topics like structure-preserving interconnections, digital twin simulations, and data-driven realization techniques. Affiliated with the Institute of Mathematics at TU Berlin, he is based in Room MA 469 and collaborates within the Numerical Analysis research group.

• Control Theory
• Numerical Analysis
• Port-Hamiltonian Systems
• +3 more

Karl Forchhammer is a full Professor at the University of Tübingen , chairing the Department of Microbiology/Organismic Interactions within the Interfaculty Institute of Microbiology and Infection Medicine Tübingen (IMIT) . He received his education at Ludwig-Maximilians-Universität München, earning a Doctorate in Microbiology with a thesis on selenocysteine biosynthesis in Escherichia coli , for which he received the VAAM Promotionspreis in 1992. His academic career includes a postdoctoral fellowship at the Institut Pasteur and associate professorship at the Justus-Liebig-Universität Giessen (1999-2007). Current Roles: Chair of Microbiology/Organismic Interactions, University of Tübingen Editor for FEBS Journal Scientific Advisory Board member, Max Planck Institute for Terrestrial Microbiology DFG panel member (Microbiology, Virology, Immunology) His research focuses on: PII Signal Transduction Proteins : Molecular mechanisms of 2-oxoglutarate sensing, ATP/ADP binding dynamics, and regulatory roles in carbon-nitrogen balance across bacteria, archaea, and chloroplasts. Nitrogen Starvation Response : Molecular basis of chlorosis in Synechocystis and Synechococcus species, including nblA gene regulation and sodium bioenergetics during dormancy. Metabolic Engineering Applications : Development of FRET sensors for metabolite detection and optimization of polyhydroxybutyrate (PHB) production in cyanobacteria. Carbon Regulation Systems : Structural analysis of SbtB redox-sensitive loops, c-di-AMP signaling in diurnal metabolism, and PirC-mediated phosphoglycerate mutase inhibition. Technological Innovations : Creation of SCAGE method for cyanobacterial transport and development of magnetic bead immunoassays for SARS-CoV-2 detection. Scientific contributions include: Discovery of plant kingdom's first glutamine sensory mechanism through PII evolution Elucidation of PII-NAGK functional conservation over 1.2 billion years Identification of 2-oxoglutarate binding site in PII proteins Demonstration of sodium bioenergetics' critical role in cyanobacterial developmental transitions Development of metabolite FRET sensors for real-time metabolic monitoring Establishment of PHB production platforms without nitrogen starvation His lab has trained 15+ PhD students and 3+ PostDocs, with collaborations spanning microbial biotechnology, structural biology, and environmental systems. Recent publications highlight: 2025 work on natural microbial community-enhanced bioplastic production 2024 structural studies of PII-regulated enzymes 2023-2024 investigations into glycogen metabolism and redox regulation 2022-2023 studies on c-di-AMP signaling and toxin-antitoxin systems

• Nitrogen regulation in bacteria
• PII signal transduction proteins
• Cyanobacterial metabolism
• +5 more

Zhiqiang Que is a Research Associate in the Department of Computing at Imperial College London, affiliated with the Faculty of Engineering and the Centre for High-Throughput Digital Electronics and Machine Learning. His research focuses on computer architecture, embedded systems, high-performance computing, and CAD tools for hardware design optimization. His research interests include FPGA-based acceleration of machine learning models, hardware-software co-design, and real-time signal processing for scientific applications such as particle physics and gravitational wave experiments. He has contributed to projects involving low-latency graph neural networks (GNNs), Bayesian neural networks, and efficient stream processing on FPGAs. Recent work includes advancements in trustworthy design flows for deep learning acceleration, reconfigurable architectures for recurrent neural networks, and optimizing FPGA-based systems for high-energy physics experiments at the HL-LHC.

• Computer Architecture
• Embedded Systems
• High-Performance Computing
• +3 more

Dr. Sharmin Jahan serves as a tenure-tracked Assistant Professor in the Department of Computer Science at Oklahoma State University since August 2022. Her research centers on dynamic security assurance for autonomous systems (self-adaptive systems) through explainable AI models that interpret uncertain operational environments to enable autonomous security decision-making and compliance maintenance. Her educational background includes a Ph.D. and Master's in Computer Science from the University of Tulsa (2018-2021), and a B.Sc. in Computer Science and Engineering from Bangladesh University of Engineering and Technology (2007-2012). She teaches Introduction to Computer Security (CS 4243/5243) and leads Dr. Jahan's Lab focused on security for autonomous systems. Research interests span Explainable AI in Cyber Security, IoT Security, Self-Protecting Systems, and Micro-service Security. Her work develops frameworks that embed security awareness in dynamic systems, using XAI to interpret environmental uncertainty and maintain security compliance through autonomous adaptation. Current projects explore machine learning models for security analysis and XAI challenges in domain-specific security applications. Recent publications (2025-2020) demonstrate concentrated research on security assurance in self-adaptive systems, particularly for IoT and microservice architectures. Key trends include XAI-driven anomaly detection, security profile extraction from operational data, and risk-adaptive access control. Subfield specializations cover service mesh security, blockchain-based access frameworks, runtime trust evaluation, and autonomous threat containment. Scientific awards include: Principal Investigator for 2023 Arts and Sciences Summer Research Award on XAI-enhanced security awareness in autonomous systems Senior personnel on 2022 NSF RET Grant for Big Data and Machine Learning research experiences She advises M.Sc. student Masrufa Bayesh and teaches graduate/undergraduate security courses. Her lab actively investigates frameworks for security assurance in dynamic environments, with emphasis on IoT and microservice architectures requiring continuous adaptation to environmental changes while maintaining security compliance. Dr. Jahan's research team develops analysis and assessment models to determine security compliance degradation risks and optimal adaptation strategies, enhancing system resiliency through separate analytical frameworks integrated with her PhD-developed assessment methodology.

• Explainable Artificial Intelligence Applications in Cyber Security
• Information Security
• Self-Protecting System
• +2 more

Dr. Davi V. Q. Rodrigues is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Texas at El Paso (UTEP). His research focuses on microwave/millimeter-wave circuits and signal processing for radar, communication systems, and smart living applications. He holds a B.S. in Communications Engineering from the Military Institute of Engineering (Brazil) and a Ph.D. in Electrical Engineering from Texas Tech University. Prior to academia, he served in the Brazilian Navy and Army, and worked at Uhnder, Inc., Abbott Laboratories, and Dell Technologies. His work emphasizes radar-based smart home, healthcare, and autonomous systems, with contributions in structural health monitoring, human activity recognition, and joint communication-sensing technologies. Dr. Rodrigues has received prestigious awards including the 2022 IEEE MTT-S Tom Brazil Fellowship and the 2023 Texas Tech Horn Distinguished Professors Award. His research group, the Microwave Circuits & Sensing Systems Group, develops algorithms and hardware for biomedical sensing, non-contact health monitoring, and 6G-enabled applications. He actively seeks motivated graduate students interested in radar systems, signal processing, and wireless technologies. Education: B.S., Communications Engineering, Military Institute of Engineering (2017) Ph.D., Electrical Engineering, Texas Tech University (2023) Research Interests: Microwave/mm-wave radar systems Human activity monitoring and gesture recognition Structural health monitoring 6G/ B5G communication-sensing fusion Passive and opportunistic RF sensing His publications span radar-based smart living solutions, biomedical sensors, and reconfigurable intelligent surfaces (IRS). He is an IEEE MTT-S member and has contributed to industry partnerships through collaborations with Uhnder and Dell Technologies. Current projects integrate AI-driven radar signal analysis and low-cost sensor networks for healthcare and infrastructure monitoring.

• Signal Processing
• Microwave/Millimeter-Wave Circuits
• Radar Systems
• +7 more

Kyle Montague is an Associate Professor in the School of Computing at Newcastle University, specializing in Human-Computer Interaction with a strong emphasis on accessibility, inclusive design, and community-centered technology development. His research bridges theoretical frameworks with practical applications to create more equitable technology experiences for marginalized communities. Montague completed his PhD at the University of Dundee in 2013 with research on 'SUM: an exploration of Shared User Models and interface adaptations to improve accessibility of mobile touchscreen interactions.' His academic trajectory shows a clear evolution from foundational work on accessibility technologies to more recent explorations of feminist ethics in community-based design. His research interests span multiple critical areas in contemporary HCI: developing accessible mobile interfaces for blind and visually impaired users, creating tools for citizen-led personalization of user interfaces, exploring digital civics and community engagement through technology, and investigating ethical frameworks for community-led design. Montague's work consistently emphasizes participatory approaches, centering marginalized communities in the design process to create technologies that truly serve their needs. An analysis of his recent publications reveals an evolving research trajectory from technical accessibility solutions toward more socially conscious design frameworks. While early work focused on practical accessibility tools (like non-visual text entry methods), his recent research engages with feminist care ethics, digital citizenship, and community-led technology development. This evolution reflects a growing emphasis on ethical considerations and social justice in HCI research, with increasing attention to AI's role in community engagement and ethical design practices. Montague has established significant collaborations with researchers across institutions, particularly with Hugo Nicolau, Tiago João Vieira Guerreiro, and Reem Talhouk. His work appears consistently in top-tier venues including CHI, ASSETS, and CSCW, demonstrating recognition by the HCI community for both technical innovation and socially impactful research. His lab at Newcastle University focuses on developing practical tools for community engagement while advancing theoretical frameworks for ethical technology design. Current projects include AI-generated tools for academic conferences, frameworks for feminist community-led ethics, and platforms for citizen-led interface personalization, all reflecting his commitment to democratizing technology development and ensuring it serves diverse community needs.

• Accessibility
• Human-Computer Interaction
• Assistive Technologies
• +5 more

Mohammad T. Khasawneh is a SUNY Distinguished Professor and Director of the School of Systems Science and Industrial Engineering at Binghamton University. He leads the Watson Institute for Systems Excellence (WISE) and the Healthcare Systems Engineering Center. His roles include Director of the Manhattan Graduate Program in Health Systems. Education: BS and MS in Mechanical Engineering from Jordan University of Science and Technology (1998, 2000), PhD in Industrial Engineering from Clemson University (2003). Research focuses on healthcare systems engineering, operations management, and data science. His work optimizes healthcare systems for improved patient outcomes and cost efficiency. Key areas include predictive analytics, hospital resource utilization, and clinical performance improvement. He has generated over $15M in external funding and led projects with U.S. hospital systems. Notable achievements include developing the Executive Master of Science in Health Systems and an MS in Healthcare Systems Engineering. His research has produced 60+ journal articles and 120+ conference papers. Awards include SUNY Chancellor’s Awards for Teaching (2011) and Scholarship (2021), University Awards for Graduate Director (2015) and International Education (2016). He is an IISE Fellow and holds honorary visiting professorships at Hebei University of Technology (China) and Vellore Institute of Technology (India). Grants and funding: $2.5-3M annually via WISE, $39M in software/equipment grants. Lab/Initiatives: Healthcare Systems Engineering Center, WISE, and multiple hospital partnerships.

• Healthcare Systems Engineering
• Operations Management
• Data Science
• +3 more

Lesley Shannon is an Associate Professor in the School of Engineering Science at Simon Fraser University (SFU), specializing in computing system design and reconfigurable computing. She leads the Reconfigurable Computing Lab (RCL), focusing on FPGA-based architectures, heterogeneous multicore systems, and CAD tools. Her academic journey includes a B.Sc. from the University of New Brunswick (1999), M.A.Sc. and Ph.D. from the University of Toronto (2001 and 2006). Her research spans FPGA CAD algorithms, Networks-on-Chip (NoCs), dynamic partial reconfiguration (DPR), and application-specific architectures. Key projects include FUSE (OS abstraction for hardware accelerators), PolyBlaze (multicore system emulation), and uROAMs (microfluidic reconfigurable devices). She has secured funding from NSERC, Xilinx, and Altera, among others. Education: B.Sc., Electrical Engineering (Computer Option), University of New Brunswick, 1999 M.A.Sc., Applied Science, University of Toronto, 2001 Ph.D., Applied Science, University of Toronto, 2006 Roles: NSERC Chair for Women in Science and Engineering (BC/Yukon) Faculty Advisor, SFU WEST (Women in Engineering, Science, and Technology) Her lab employs 5 current students and has graduated 7, including work on FPGA CAD, microfluidics, and embedded systems. Courses taught include Advanced Digital Systems Design and Real-Time/Embedded Systems. Her research emphasizes reducing design time through on-chip profiling and CAD tools, with applications in biomedical imaging and quantum computing. Awards & Grants: NSERC Discovery Grant NSERC Strategic Grant (Lead PI, 2009; Co-PI, 2010) SFU Startup Grant and President’s Research Grant Lab & Collaborations: The RCL develops silicon and non-silicon architectures, including quantum computing and microfluidic systems. Partnerships include industry collaborations and open-source tools like Odin II synthesis framework.

• Computer Engineering
• Reconfigurable Computing
• FPGA CAD Tools
• +6 more

Professor Vishal Saxena is a faculty member in the Department of Electrical and Computer Engineering at the University of Delaware since 2019. Previously, he held positions at Boise State University (2010–2016) as Assistant and Associate Professor, and served as the Micron Endowed Professor of Microelectronics at the University of Idaho (2016–2019). His research focuses on analog electronic and photonic integrated circuits (ICs), particularly in sustaining IC design advancements post-Moore scaling through hybrid CMOS-photonic integration, neuromorphic computing, and energy-efficient embedded intelligence. Dr. Saxena earned his B.Tech. in Electrical Engineering from IIT Madras (2002), followed by M.S. and Ph.D. in Electrical and Computer Engineering from Boise State University (2007–2010). He has industry experience in semiconductor and telecommunication engineering. His work is supported by NSF, AFOSR, DARPA, NASA, and industry collaborators. Notable awards include the NSF CAREER (2015), AFOSR YIP (2016), and DARPA YFA (2019). His research interests span silicon photonic ICs for optical interconnects, RF photonic systems, neuromorphic circuits using emerging NVM devices, and high-speed analog-to-digital converters. He has pioneered compact modeling techniques for photonic components and developed energy-efficient architectures for spiking neural networks. Dr. Saxena’s publications reflect advancements in photonic integration, neuromorphic hardware, and mixed-signal IC design. He actively contributes to the IEEE community through editorial roles and conference steering committees, including MWSCAS and ISCAS.

• Silicon Photonic Integrated Circuits
• Neuromorphic Computing
• CMOS Electronics
• +3 more

Amitabh Mishra is an Adjunct Professor at the University of Delaware. His research focuses on three core areas: computer-communication networks (wireless architectures, cross-layer design, mobile cloud computing), network performance analysis (stochastic models, numerical optimizations), and network security (vulnerability assessments, authentication protocols). He has contributed to interdisciplinary fields including IoT security, smart healthcare frameworks, and socio-technical systems analysis. His work spans technical domains like wireless sensor networks, tactical network management, and quantum dot material studies, alongside applied research in tourism economics, healthcare data analytics, and educational technology. Notable contributions include frameworks for energy-efficient physiological monitoring, secure IoT configurations, and machine learning-driven security protocols. Recent research highlights include: Developing secure mobile cloud computing paradigms Modeling Multipath TCP capacity bounds using stochastic theory Investigating AI applications for deepfake ethics and tourism marketing His publications span technical journals in computer networks, medical IoT systems, and interdisciplinary studies in cultural tourism and climate change resilience.

• Computer-Communication Networks
• Wireless Networks
• Network Security
• +5 more