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Theresa NoegelView profile

Researcher

• Radar Imaging Systems
• Radar Signal Processing
• Automotive Radar

Theresa Noegel is a Doctoral Candidate and Researcher at the Institute of Microwaves and Photonics (LHFT) within the Department of Electrical-Electronic-Communication Engineering at Friedrich-Alexander University Erlangen-Nuremberg (FAU). She has been with LHFT since March 2023, contributing to cutting-edge radar research for automotive applications. Her educational background includes: B.Sc. in Electrical Engineering and Information Technology (EEI) from 2016 to 2020 M.Sc. in Electrical Engineering and Information Technology (EEI) from 2020 to 2023 Theresa's research focuses on Radar Imaging Systems , Radar Signal Processing , and Automotive Radar , with emphasis on Synthetic Aperture Radar (SAR) techniques. Her work spans 3D imaging implementation, real-time processing algorithms, and joint communication-sensing integration using OFDM waveforms, addressing critical challenges in autonomous vehicle perception systems. Analysis of her 2022-2024 publications reveals a clear progression from foundational SAR image segmentation toward advanced 3D imaging and forward-looking accumulation methods, demonstrating increasing technical sophistication in automotive radar applications through both simulation and hardware implementation. As an active member of the Institute of Microwaves and Photonics research team, she collaborates on developing next-generation radar technologies for automotive safety systems, working closely with senior researchers including M. Hoffmann and M. Vossiek on real-world implementation challenges.

Yucheng XieView profile

Assistant Professor

• Security in Machine Learning
• Smart and Mobile Healthcare
• Mobile Computing and Sensing
• +3 more

Yucheng Xie is a Tenure-track Assistant Professor in the Graduate Department of Computer Science and Engineering at Yeshiva University, affiliated with the Katz School of Science and Health. He holds a Ph.D. in Electrical and Computer Engineering from Purdue University and a Master’s in Computer Science from Stevens Institute of Technology. His research focuses on Security in Machine Learning/AI Systems , Smart and Mobile Healthcare , and Mobile Computing and Sensing . Notable contributions include non-invasive wireless sensing via mmWave and Wi-Fi signals for health monitoring, adversarial attacks on activity recognition systems, and secure mobile deep learning. His recent articles explore topics like contactless human concentration monitoring, palm-based authentication, and environment-invariant eating behavior tracking. These works highlight innovations in mmWave technology, cybersecurity for AI systems, and healthcare applications. Awards : Best Paper Runner-up (IEEE Conference on Communications and Network Security, 2024) Best Paper Runner-up (IEEE International Conference on Computer Communications and Networks, 2022) Best Paper Award (EAI International Conference on IoT Technologies for HealthCare, 2019) While no advising or grant details are provided, his work emphasizes practical applications of wireless sensing and secure AI systems. No specific lab affiliations are mentioned, though his research often involves interdisciplinary collaboration.

Oskar MencerView profile

Professor

• Numerical methods and simulations
• Imaging
• Discretization of space, time and value
• +7 more

Oskar Mencer is a Professor in the Department of Computing at Imperial College London , where he has been a member of academic staff since 2000. He was also a Consulting Professor at Center for Computational Earth and Environmental Science , Stanford University (2009-2010). His research focuses on Multiscale Dataflow Computing , exploring the interaction of hardware and software systems through domain-specific representations, parallel programming, VLSI design, and compiler methodologies. He has contributed to fields including high-performance computing, FPGA optimization, and computational finance. Dr. Mencer's work has been recognized with a Special Award from Com.sult (2012), Imperial College Research Excellence Award (2007), and a Top EPSRC Advanced Fellowship (2001). He has received multiple best paper awards, including at ICFPT'08 and ASAP 2008, and his 2000 paper on stream architectures was recognized as historically significant in 2015. His publications demonstrate a strong emphasis on FPGA acceleration , custom architectures , and parallel processing across geophysics, finance, and neuroscience applications. Special Award for Dataflow Innovation (2012) Best Paper Award - ICFPT'08 Best Paper Award - ASAP 2008 He has served on technical committees for conferences such as FPL , DATE , and FPT , and leads the Computer Architecture Research Group (currently inactive).

Jing FuView profile

Lecturer

• Artificial Intelligence
• Machine Learning
• Telecommunications
• +6 more

Dr. Jing Fu is a Lecturer at the School of Engineering, RMIT University in Australia. Her research focuses on applying optimization algorithms and machine learning to telecommunications, wireless networks, and edge computing. She specializes in restless bandit models for dynamic resource allocation, multi-agent coordination, and energy-efficient systems design. Key areas include satellite communications, radar systems, and distributed computing architectures. Her work bridges theoretical operations research with practical applications in 5G/6G networks, UAV communication platforms, and smart sensor networks. She has published extensively on topics like beam scheduling, edge computing offloading strategies, and adaptive wireless protocols. Current supervision interests span neural networks for sensor systems, IoT resource allocation, and next-generation mega satellite networks. Research Themes: AI-driven network optimization, distributed radar systems, energy-efficient edge computing Key Projects: Reinforcement learning-based IoT resource allocation 6G wireless communication with AI integration Optimal beam scheduling for phased array radars Collaborations: Active in multi-disciplinary projects involving telecommunications, aerospace engineering, and computer science Dr. Fu supervises research projects on neural networks for telecommunications, adaptive wireless techniques, and satellite formation flying. She is based at RMIT's City Campus and open to guiding postgraduate research in her areas of expertise.

• Cognitive Neuroscience
• Machine Learning
• Functional Brain Imaging
• +2 more

Geraint Rees is Vice-Provost (Research, Innovation and Global Engagement) at University College London (UCL), where he previously served as Dean of the Faculty of Life Sciences. His academic appointments include Professor of Cognitive Neurology and Director of the UCL Institute of Cognitive Neuroscience. His research focuses on understanding human cognition through advanced neuroimaging and machine learning techniques. Education: Doctor of Philosophy, University College London (1999) Master of Arts, University of Cambridge (1999) Bachelor of Medicine/Bachelor of Surgery, University of Oxford (1991) Bachelor of Arts, University of Cambridge (1988) Dr. Rees leads interdisciplinary research in cognitive neuroscience, investigating neural mechanisms of perception and decision-making using functional MRI and computational approaches. His work bridges clinical neurology with artificial intelligence to understand brain disorders. Research emphases include neuroplasticity, neurodegeneration biomarkers, and machine learning applications in healthcare. Recent publications (2023-2025) demonstrate strong research trends in computational neuroscience with applications to neurodegenerative diseases, particularly Huntington's and Alzheimer's. Key patterns include advanced neuroimaging techniques (7T MRI, fMRI), transformer-based deep learning models, and investigations into neuroplasticity and sensory system adaptations. Dr. Rees has extensive leadership experience in large-scale research initiatives, serving on the Executive Management Team of the Francis Crick Institute and as Non-Executive Director for UCL Business. He maintains active research collaborations with Google DeepMind and develops doctoral training programs.

Raul Sanchez-ReilloView profile

Professor

• Biometrics
• Information Security
• Smartcard Technology
• +6 more

Dr. Raul Sanchez-Reillo is a Full Professor at the Electronics Technology Department, University Carlos III of Madrid (UC3M). He holds a PhD in Telecommunication Engineering from the Polytechnic University of Madrid (2000). As Director of GUTI (University Group for Identification Technology) and founder of IDTestingLab, he specializes in biometrics, smartcards, and information security. His work since 1994 includes managing over 8 European projects (e.g., BioSec, MobilePass) and 12 national/regional projects. He chairs international standardization bodies like ISO/IEC JTC1 SC37 (Biometrics) and leads Spanish delegations in related standards committees. His research focuses on biometric systems (fingerprint, vein, ECG, gait), presentation attack detection, and mobile security. He has authored 36+ international journal papers, 18 book chapters, and contributed to 12 international standards. Awards include the IEEE Harry Rowe Mimno Award (2002) and the iBanesto.com Best PhD Thesis Award (Electronic Commerce). Teaching includes courses on microprocessors, digital systems, and biometrics. He has supervised over 130 final degree projects and directed 5 completed PhDs with 8 ongoing. His work integrates hardware-software co-design for biometric systems and emphasizes usability in mobile environments.

• Business Analytics
• Information Systems Management
• Digital Transformation
• +5 more

Dr. Adi Prananto is a Senior Lecturer in the Information Systems discipline at Swinburne University of Technology's School of Business, Law and Entrepreneurship. Specializing in business analytics, information systems management, and IT security management, he has served as Course Director for the Bachelor of Business Analytics & Analysis and the Bachelor of Business Analytics while previously holding roles as Discipline Leader for Information Systems and Academic Director, International & Pathways. His work bridges academic leadership with applied innovation through AI-powered tools for education optimization, cybersecurity, and social impact. Dr. Prananto's research focuses on digital transformation, business analytics, emerging technologies, and their organizational applications. He has supervised multiple PhD projects on topics like AI in Alzheimer's disease prediction, start-up growth, and enterprise systems implementation. His publications span IS governance, e-business maturity, dashboard design, and technology-driven value creation, with an emphasis on qualitative methods and case study approaches. Industry partnerships include IBM Cybersecurity Analyst and AWS Certified Cloud Practitioner certifications, enhancing his practical contributions to education and organizational strategy. IBM Cybersecurity Analyst Professional AWS Certified Cloud Practitioner His scholarly output includes 23 publications with over 89 Mendeley readers, covering themes from pandemic-era digital transformation (2024) to early frameworks for e-business maturity (2000). Research keywords include business analytics, information systems, and strategic management, with field citation ratios reflecting ongoing relevance.

Daniel Pizarro PérezView profile

Professor

• Computer Vision
• Medical Imaging
• Smart Grids
• +3 more

Dr. Daniel Pizarro Pérez is a Professor in the Department of Electronics at the University of Alcalá, Spain. He is a member of the GEINTRA research group, which focuses on Electronic Engineering applied to Intelligent Spaces and Transport. He holds a doctoral degree from the University of Alcalá, completing his thesis on 'Localización de robots móviles en espacios inteligentes utilizando cámaras externas y marcas naturales' (2008), supervised by Dr. Manuel Ramón Mazo Quintas and Dr. Enrique Santiso Gómez. His research interests span computer vision, medical imaging, smart grid technologies, acoustic signal processing, and control systems. Notable projects include augmented reality applications in laparoscopic surgery, non-intrusive load monitoring using smart meters, and advanced control methodologies for power electronics. His work bridges theoretical advancements with practical applications in healthcare, energy systems, and robotics. Recent publications highlight contributions to neural radiance fields for minimally-invasive surgery, distributed acoustic sensing in submarine environments, and deep learning-based activity recognition via energy consumption. His research frequently integrates interdisciplinary approaches, such as combining computer vision with medical robotics and leveraging machine learning for real-time control systems. Dr. Pizarro’s work has been supported by grants and collaborations within the GEINTRA group, with applications in intelligent spaces, robotic navigation, and sensor fusion. He has also contributed to educational initiatives like the GEMS Erasmus+ project, emphasizing sensory module development for robotics education.

Ziad KobtiView profile

Professor

• Artificial Intelligence
• Machine Learning
• Data Science
• +6 more

Ziad Kobti is a Professor and Director of the School of Computer Science at the University of Windsor. His work focuses on advancing artificial intelligence, machine learning, and data science with applications in healthcare, cybersecurity, and social network analysis. He leads initiatives such as the Graph Neural Network Lab and collaborates with industry partners like Sterling Information Technologies to foster cybersecurity talent. Kobti has organized programming competitions, co-op education programs, and research workshops, emphasizing experiential learning for students. His research spans recommendation systems, graph neural networks, pandemic modeling, and medical diagnostics, with a focus on impactful real-world solutions. He is involved in academic leadership, program development, and community outreach through events like Computer Science Demo Day. Research interests include: Graph Neural Networks and Dynamic Link Prediction Recommender Systems and Anomaly Detection Social Network Analysis and Team Formation Healthcare Informatics and Medical Imaging Cybersecurity and Privacy Risk Analysis Machine Learning for Public Health and Pandemic Preparedness Recent projects include collaborations on AI-driven crop disease detection, electric vehicle research, and palliative care simulation frameworks. He has developed frameworks like UDIS and BeComE, and contributes to open-source tools for social network analysis and anomaly detection. His work integrates multi-disciplinary approaches, combining computational models with domain-specific expertise in healthcare, agriculture, and social systems.

• Hypertrophic Cardiomyopathy
• Myocardial Disease
• Genetics of Heart Disease
• +3 more

Dr. Michelle Michels is a Researcher in the Department of Cardiology at Erasmus University Medical Center (Erasmus MC), Rotterdam, the Netherlands, specializing in inherited cardiac conditions with 191 research outputs including 181 articles. Her work centers on hypertrophic cardiomyopathy and related genetic heart diseases within Europe's leading cardiovascular research framework. Her research spans hypertrophic cardiomyopathy , genetic myocardial disorders , and cardiac imaging , investigating genotype-negative disease expression, arrhythmia risks in RBM20-associated cases, and physical activity impacts through accelerometry. Current projects include the ENERGY clinical trial on trimetazidine therapy and European Reference Network initiatives for rare cardiomyopathy management, emphasizing multidisciplinary collaboration across 12 international profiles. Recent publications reveal strong trends toward translational research integrating genetic profiling with clinical outcomes, particularly in pre-symptomatic disease stages and quality-of-life interventions. Her work consistently addresses therapeutic gaps in inherited heart conditions through multicenter cohort studies and randomized trials. Scientific awards: No specific awards were documented in the source material. Dr. Michels has supervised 4 students per institutional records and participates in major European collaborative networks including the European Reference Network for rare heart diseases. Her grant-funded work focuses on clinical trials like ENERGY and multinational studies on transition care for inherited cardiomyopathies. Embedded within Erasmus MC's Cardiology department—a hub for genetic heart disease research—she collaborates extensively across European institutions as evidenced by co-authorship in high-impact journals and network visualizations showing country-level research partnerships.

• Robotics
• Artificial Intelligence
• Medical Imaging
• +5 more

Dr Shahnewaz Ali is a Postdoctoral Fellow in the Faculty of Engineering's School of Electrical Engineering & Robotics at Queensland University of Technology (QUT). He is affiliated with the Centre for Robotics and holds a PhD from QUT and an MSc in Computer Engineering from Politecnico di Milano. His research focuses on the intersection of robotics, artificial intelligence, and biomedical applications, emphasizing wearable technology, surgical robotics, and sensor systems. Key research interests include AI-driven medical imaging, robotic surgery systems, and biomarker detection using wearable devices. His work spans sensor technologies for robotics, real-time surgical scene analysis, and predictive performance monitoring. Recent projects include developing a wearable monitoring system for stress biomarkers and advancing arthroscopic surgical techniques through 3D mapping and deep learning. Education: PhD, Queensland University of Technology MSc (Computer Engineering), Politecnico di Milano Dr Ali's publications cover topics like surgical scene restoration, microRNA-based performance prediction, and sensor development for medical robotics. His research bridges engineering and healthcare, aiming to enhance diagnostic accuracy and robotic surgical precision. Collaborations include multidisciplinary teams at QUT and international institutions.

• Optical Fibers
• Photonics
• Materials Science
• +7 more

Professor Heike Ebendorff-Heidepriem is a Professor in the School of Physics, Chemistry and Earth Sciences at the University of Adelaide. She serves as Deputy Director of the Institute for Photonics and Advanced Sensing (IPAS) and Director of the Optofab Adelaide Hub within the Australian National Fabrication Facility (ANFF). Her research focuses on advanced optical fiber fabrication, materials science, and photonics applications, including high-precision glass extrusion, exposed-core fibers, and quantum sensing. She leads a multidisciplinary team of over 20 researchers and has secured >$20M in funding, collaborating with global industry and academic partners. Her work spans fiber lasers, mid-infrared photonics, and sensor technologies, with significant contributions to nanomaterial integration and plasmonic processes. She has supervised 12 PhD and 5 HDR students over 15 years, emphasizing mentorship in photonics and materials innovation. Research Interests: Professor Ebendorff-Heidepriem specializes in developing novel optical fibers and glasses for applications such as high-power laser delivery, nonlinear optics, and evanescent field sensing. Her team pioneers fabrication techniques like billet extrusion and ultrasonic milling, enabling structures like suspended nanowire-core fibers and diamond-doped sensors. Key areas include mid-infrared materials (tellurite, fluoride glasses), plasmonic nanoparticle embedded glasses, and portable sensing solutions for mining and biomedical fields. Labs/Teams: IPAS and Optofab Adelaide Hub provide advanced facilities for fiber fabrication, laser development, and materials characterization. Her collaborations include 82 university groups and 30 industry/defense partners, driving commercialization of technologies like gold nanoparticle-based colored glass and diamond-doped fiber sensors.

• Artificial Intelligence
• Machine Learning
• Internet of Things
• +13 more

Edoardo Patti is an Associate Professor in the Department of Control and Computer Engineering (DAUIN) at Politecnico di Torino, Italy. He is actively involved in research and teaching, focusing on artificial intelligence, machine learning, IoT, smart grids, energy communities, co-simulation, and digital twin technologies. He is a member of the EDA (Electronic Design Automation) research group and the Interdepartmental Center IAM@PoliTo for Integrated Additive Manufacturing. His research interests span Artificial Intelligence, Machine Learning, Internet of Things, Smart Grids, Energy Communities, Co-simulation, Distributed Software Infrastructure, Digital Twin, Physics-Informed Neural Networks, and Reinforcement Learning . His work is closely aligned with Sustainable Development Goals such as Affordable and Clean Energy (Goal 7), Sustainable Cities (Goal 11), and Climate Action (Goal 13). The latest publications reveal a strong trend in AI-driven modeling for energy systems, including digital twins for wave energy converters, urban electric mobility simulation, real-time battery health estimation, and co-simulation platforms for integrated energy systems. His work combines machine learning with physical models and large-scale distributed systems to address sustainability challenges. He supervises several PhD students, including Maria Adelaide Loffa, Matia Torlini, Rafael Natalio Fontana Crespo, Pietro Rando Mazzarino, Claudia De Vizia, and Marco Massano. He has led numerous research projects funded by EU (H2020), PNRR, regional initiatives, and corporate contracts, particularly in additive manufacturing, smart grids, and IoT platforms. He is involved in multiple research groups and centers: EDA - Electronic Design Automation (DAUIN) Interdepartmental Center IAM@PoliTo - Integrated Additive Manufacturing

Tadeusz WięckowskiView profile

Professor

• Electromagnetic Compatibility
• Antenna Theory
• Radio Wave Propagation
• +6 more

Tadeusz Więckowski is a Professor and Head of the Department of Telecommunications and Teleinformatics at the Faculty of Information and Communication Technology, Wrocław University of Science and Technology. His work bridges advanced electromagnetic theory with practical telecommunications systems. His research interests include: Electromagnetic Compatibility (EMC) of devices and systems Antenna theory and design Radio wave propagation Radiocommunication systems Gyrotron and microwave source technologies Testing methodologies for EMC infrastructure The recent publications highlight a strong focus on high-frequency electromagnetic systems, particularly gyrotrons for spectroscopy and electromagnetic compatibility testing. His work spans both theoretical modeling and experimental validation, with applications in telecommunications, broadcasting (e.g., DAB), and scientific instrumentation. There is also engagement with modern topics such as IoT testing, intrusion detection, and neural networks for document verification, indicating interdisciplinary reach. Tadeusz Więckowski leads the Department of Telecommunications and Teleinformatics, which is involved in the operation of the Laboratory for Electromagnetic Compatibility. This infrastructure supports advanced research in signal integrity and system compatibility.

Francesco PicarielloView profile

Researcher

• Electrical and Electronic Measurements
• Data Acquisition Systems
• Compressive Sampling
• +7 more

Francesco Picariello is a Researcher at the Department of Engineering (DING) at the University of Sannio, specializing in Electrical and Electronic Measurements (ING-INF/07). His academic profile shows extensive expertise in measurement systems, data acquisition, and signal processing with applications across multiple domains including biomedical engineering, structural health monitoring, and wireless communications. His research interests focus on the design, implementation, and metrological characterization of mobile measurement systems, wireless sensor networks, data acquisition systems based on compressed sensing, signal processing, and image processing. These research activities have been applied to intelligent transportation systems, aerial photogrammetry using UAVs, indoor navigation, motion tracking, power consumption analysis of processors, wideband data acquisition systems, and physiological monitoring applications. Dr. Picariello's work demonstrates significant trends in compressive sampling techniques, with numerous publications on ECG signal processing, RF emitter localization, and structural health monitoring systems. His research shows a clear progression toward IoT integration, wearable medical devices, and security applications for communication channels. His scientific collaborations include institutions such as the University of Naples 'Parthenope', Military University of Technology of Warsaw, National Institute of Standards and Technology (NIST), Keysight Laboratories, CERN Institute, and the University of Tokyo, reflecting the international recognition of his work. As an active researcher with publications spanning from 2016 to 2025, Dr. Picariello has made substantial contributions to measurement science, particularly in the development of novel techniques for data acquisition, signal processing, and system metrological characterization across multiple application domains.