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Gabriel LeenView profile

Research Fellow

• Optical Fiber Sensors
• Acoustic Levitation
• Biomedical Sensor Development
• +4 more

Gabriel Leen serves as a Senior Research Fellow in the Department of Electronic and Computer Engineering within the Faculty of Science and Engineering at the University of Limerick. His research integrates optical engineering, acoustics, and biomedical applications to develop advanced sensing technologies for medical diagnostics and industrial processes. Dr. Leen's primary research focuses on optical fiber sensor systems for pressure, temperature, and refractive index measurements, with significant applications in urodynamic analysis, radiotherapy dosimetry, and respiratory monitoring. His pioneering work in acoustic levitation enables contactless sample manipulation for X-ray crystallography, reducing sample consumption while enabling time-resolved structural studies of biological macromolecules. This interdisciplinary approach bridges physics, engineering, and clinical medicine through innovative device fabrication and signal processing techniques. Analysis of his recent publications (2023-2025) reveals three dominant research trajectories: 1) Acoustic droplet manipulation systems for X-ray light sources enabling new crystallography methodologies; 2) Miniaturized optical fiber sensors with biocompatible designs for in vivo medical applications; and 3) Laser-based processing techniques for flexible electronics and sensor fabrication. These themes demonstrate consistent innovation in translating fundamental physical principles into practical biomedical instrumentation with clinical impact.

Joerg RoewekaemperView profile

Researcher

• Robotics
• Artificial Intelligence
• Machine Learning
• +3 more

Joerg Roewekaemper is a researcher in the Autonomous Intelligent Systems group at Albert-Ludwigs-Universität Freiburg's Faculty of Engineering. His work focuses on robotics, localization, and sensor calibration. Education: Dipl.-Ing. (FH) in Mechatronics Engineering (Bochum University of Applied Sciences, 2009), Master o.Sc. in Systems and Control (Coventry University, 2009) Research interests include path planning for mobile manipulators, localization of mobile robots, and sensor calibration. His publications cover topics like multiple-body registration, RRT planning in high-dimensional spaces, and scan matching techniques for SLAM. Recent work analyzes trends in improving robot localization accuracy through probabilistic methods and sensor fusion, particularly for autonomous navigation systems operating in dynamic environments. Teaching: Teaching Assistant for "Einführung in die Informatik" (Introduction to Computer Science) at University of Freiburg (WS2011/12, SS2012, WS2012/13)

• Control Systems
• Signal Processing
• Sensor Fusion
• +7 more

Fredrik Gunnarsson is an Adjunct Professor at Linköping University's Department of Electrical Engineering (ISY), specializing in Automatic Control (RT). His research focuses on control systems, signal processing, and sensor fusion, with applications in positioning, navigation, and optimization for autonomous systems. University: Linköping University Department: Department of Electrical Engineering (ISY) Academic Rank: Adjunct Professor Research Interests Fredrik's work spans advanced signal processing, sensor fusion, and control algorithms. He contributes to 5G positioning, Gaussian process state-space models, and indoor localization. His research intersects with optimization-based control for autonomous systems and machine learning techniques in dynamic environments. Article Trends His recent publications emphasize wireless positioning, statistical filtering, and sensor fusion methodologies. Topics include Kalman filtering, Gaussian process modeling, particle methods for indoor navigation, and optimization algorithms for control systems. Keywords span Control Systems , Signal Processing , Machine Learning , and Wireless Communication . Labs and Collaborations LINK-SIC - Linköping Center for Sensor Informatics and Control Automotive Systems research SEDDIT competence center

• Aerosols
• Air filters
• Face masks
• +9 more

Paolo Maria Tronville is a Tenured Associate Professor in the Department of Energy (DENERG) at Polytechnic University of Turin, where he serves as a member of the Interdepartmental Center Ec-L - Energy Center Lab. His academic work focuses on environmental technical physics within the Industrial and Information Engineering domain. Dr. Tronville's research centers on aerosol technology and air quality, with specific expertise in reproducing urban aerosol particle distributions in laboratory settings and simulating the realistic aging of air filters. His work bridges engineering principles with public health applications, particularly in indoor air quality and respiratory protection systems. His recent publications reveal a strong focus on practical applications of aerosol science, including air filter testing methodologies, face mask performance evaluation, and indoor ultrafine particle analysis. These works demonstrate consistent application of engineering principles to address contemporary public health challenges related to air quality. ASHRAE Distinguished Service Award (2015) Premio Paolo Scolari from UNI - Italian Standards Organization (2012) As an ASHRAE Fellow since 2020 and former member of the ASHRAE Research Administration Executive Committee (2021-2022), Dr. Tronville has significantly contributed to industry standards. He has supervised PhD student Hamed Rasam on research concerning biologically active aerosols in indoor environments and leads numerous commercial research projects focused on air filtration systems and ventilation technologies. His work with the ACRAQ research group demonstrates strong industry collaboration in developing practical solutions for air quality challenges. Dr. Tronville actively contributes to standardization efforts through UNI and maintains an extensive portfolio of commercial research contracts addressing real-world air filtration problems for industry partners.

• Interacting Particle Systems and Statistical Mechanics
• Stochastic Control and Filtering
• Stochastic Methods for Finance

Paolo Dai Pra serves as an Associate Professor with dual institutional affiliations: his primary position is at the University of Verona, while he holds an External Teacher role at the Department of Mathematics, University of Padua. This adjunct status is standard in Italian academia for scholars primarily employed elsewhere. His research program centers on advanced stochastic methodologies, specifically: Interacting Particle Systems and Statistical Mechanics for modeling collective behavior in complex systems Stochastic Control and Filtering for dynamic decision-making under uncertainty Stochastic Methods for Finance applying probabilistic frameworks to financial engineering and risk management Contact is available via email (paolo.daipra@univr.it) or telephone (+39 049 827 1361), with his professional profile hosted on the University of Padua mathematics department website.

Abolfazl ZahediView profile

Lecturer

• Mechanics of Materials
• Advanced Manufacturing
• Additive Manufacturing
• +4 more

Dr. Abolfazl Zahedi is a Lecturer in Mechanics of Materials at Loughborough University (since 2023), previously serving as a Senior Lecturer at De Montfort University (2018–2023) and holding roles at the University of Manchester and University of Strathclyde. He holds a PhD in Mechanical Engineering from Loughborough University (2013) and has expertise in advanced manufacturing, materials science, and biomedical engineering. Education: PhD in Mechanical Engineering, Loughborough University (2013) MSc and BSc in Mechanical Engineering Research Interests: Zahedi focuses on mechanics of materials, additive manufacturing, biomaterials, and computational modeling. His work includes crystal plasticity modeling, fracture mechanics, and the development of advanced composites for biomedical applications. He has pioneered a discrete energy approach for polymer fracture analysis and contributed to integrating computational codes into industry-standard software like Code-Aster. Awards & Recognition: Fellow of the Higher Education Academy (FHEA) Marie Skłodowska-Curie Research Fellowship Nominated for Vice-Chancellor's Distinguished Teaching Award Advising & Grants: Zahedi has led industrial projects at the Advanced Forming Research Centre and managed a forming modeling group. His research has been supported by EPSRC and other industry collaborations. Labs & Teams: He has contributed to research groups at Loughborough, Strathclyde, and Manchester, emphasizing interdisciplinary collaboration in materials innovation and manufacturing technology.

• Blind signal processing
• Bayesian estimation and particle filters
• Seismological signal processing

Ayşın Baytan Ertüzün is a Full-Time Professor at Bogazici University specializing in signal processing methodologies. Her research focuses on blind signal processing techniques, Bayesian estimation frameworks using particle filters, and advanced seismological signal analysis for geophysical applications. Her work bridges theoretical models with practical implementations in seismic data interpretation.

Sebastian KempfView profile

Professor

• Cryogenic Detectors
• Nuclear Physics
• Particle Physics
• +5 more

Prof. Dr. Sebastian Kempf is a Professor at the Department of Micro- and Nanoelectronic Systems (IMS) within the College of Electrical Engineering and Information Technology at the Karlsruhe Institute of Technology (KIT). His research focuses on advanced cryogenic detectors, superconducting devices, and their applications in particle physics and astrophysics. Key projects include the AMoRE (Advanced MoRe) experiment for neutrinoless double beta decay studies, the ECHo experiment for electron neutrino mass measurements, and the development of metallic magnetic calorimeters (MMCs) for high-precision spectroscopy. His work spans detector fabrication, readout electronics optimization, and experimental design for low-background environments. Notable contributions include advancements in MMC-based gamma detectors, SQUID multiplexing for large detector arrays, and superconducting microbolometer technologies for cosmic microwave background (CMB) measurements. Kempf’s research bridges fundamental physics with cutting-edge instrumentation, addressing questions in dark matter, neutrino properties, and quantum metrology. Publications highlight interdisciplinary efforts in detector materials, noise reduction strategies, and applications in metrology (e.g., the MetroBeta project). Despite no listed awards here, his prolific output reflects recognition in the field. He leads the IMS Institute, overseeing a team engaged in FAIR (Facility for Antiproton and Ion Research) collaborations and next-generation detector systems.

Brian ClowersView profile

Professor

• Analytical Chemistry
• Mass Spectrometry
• Environmental Analysis
• +3 more

Professor Brian Clowers is a faculty member in the Department of Chemistry at Washington State University (WSU). His research focuses on advancing ion mobility spectrometry (IMS) and mass spectrometry (MS) techniques, particularly in gas-phase ion behavior analysis. Key areas include carbohydrate structure determination, threat detection, and environmental analysis. He holds a Ph.D. from WSU and completed postdoctoral work at Pacific Northwest National Laboratory and the University of California, Davis. Education: Ph.D. in Chemistry, Washington State University (2005) Postdoctoral Fellowships at Pacific Northwest National Laboratory (2006–2008 and 2006) Research interests emphasize hybrid IMS-MS methodologies for applications in bioanalysis, environmental monitoring, and national security. His group develops open-source instrumentation and chemometric data analysis tools. Major contributions include ion funnel trap technology licensed to Agilent Technologies and ExcellIMS, and patents on particle-based drug detection and vapor detection systems. Publications highlight advancements in ion mobility separation techniques, protein analysis, and environmental contaminant detection. His work bridges fundamental ion chemistry with practical applications, supported by grants and collaborations in instrumentation innovation.

Bruce TatarchukView profile

Professor

• Chemical Engineering
• Materials Science
• Catalysis
• +2 more

Bruce Tatarchuk is the Charles E. Gavin III Chair and Director of the Microfibrous Materials Manufacturing Center at Auburn University's College of Engineering, Department of Chemical Engineering. He holds a Ph.D. in Chemical Engineering from the University of Wisconsin and a B.S. from the University of Illinois-Urbana-Champaign. His research focuses on chemical engineering innovations with emphasis on catalysis, energy storage systems, and process intensification. Recent investigations include advanced battery technologies, catalytic reactor designs, and environmental filtration systems. His work demonstrates consistent application of materials science principles to solve industrial challenges. Publication analysis reveals sustained research output in high-impact areas including electrochemical energy storage (35%), catalytic process engineering (45%), and advanced materials characterization (20%). The majority of recent work focuses on lithium-ion battery optimization and catalytic reactor designs for industrial chemical processes. Awards & Honors: State of Alabama Engineering Hall of Fame (Class of 2025) As Center Director, he leads research initiatives in microfibrous materials manufacturing with demonstrated applications in defense, energy, and environmental sectors.

• Dark Matter
• Quantum Physics
• Resonator Technology
• +3 more

Graeme Flower is a Researcher at the School of Physics, Mathematics and Computing, The University of Western Australia. His research focuses on experimental particle physics, dark matter detection, and quantum technologies. Key areas include axion dark matter searches, resonator-based experiments, and gravitational physics. He holds a Doctoral Thesis from 2022 on improving axion detection using magnonic systems. Recent work includes collaborations on the ORGAN experiment for axion detection and studies on gravitational Aharonov-Bohm effects. He has contributed to projects funded by the ARC Australian Research Council (2023–2024), focusing on 5G oscillators using YIG filters. His publications span Physical Review journals and Applied Physics Letters, emphasizing precision measurements and quantum phenomena. Flower’s research integrates theoretical models with experimental techniques, addressing challenges in dark matter detection and quantum device optimization. He has pioneered methodologies for magnetic field screening in superconducting cavities and developed novel magnonic sensor applications.

Ting XiaoView profile

Assistant Professor

• Machine Learning
• Data Science
• Medical AI
• +5 more

Ting Xiao is an Assistant Professor of Data Science at the University of North Texas (UNT), with a joint appointment in the Department of Computer Science and Engineering. His research focuses on machine learning, medical AI, particle physics, and data-driven solutions for interdisciplinary challenges such as healthcare analytics, environmental monitoring, and sociotechnical systems. Key research areas include medical imaging analysis, multimodal AI for radiology, predictive modeling in public health, and high-energy physics experiments. His work leverages advanced techniques like autoencoders, transformer models, and embedding-based systems to address problems ranging from Parkinson’s disease diagnosis to wildfire prediction and economic law analysis. Notable contributions include developing frameworks for radiology report generation, embedding-based candidate matching systems, and novel datasets for wildfire spread prediction. Xiao’s interdisciplinary approach bridges computer science, engineering, and domain-specific applications, fostering innovation in both technical and societal contexts. His recent publications (2023–2025) highlight trends in multimodal AI, medical diagnostics via computational methods, and leveraging large-scale datasets for environmental and socioeconomic forecasting. Xiao’s work is characterized by strong empirical validation and practical impact, often involving collaborations across disciplines.

Mirko MazzoleniView profile

Associate Professor

• System Identification
• Fault Diagnosis
• Kernel Methods
• +8 more

Mirko Mazzoleni is an Associate Professor at the Department of Management, Information and Production Engineering, University of Bergamo, Italy. His research focuses on system identification, fault diagnosis, kernel methods, and Industry 4.0 applications. He holds a Master's in Computer Science Engineering (2014) and a Ph.D. in Engineering and Applied Sciences (2018). Before becoming an Associate Professor, he served as an Assistant Professor at the Control and Automation Laboratory (CAL) from 2019 to 2024. His work integrates data science, signal processing, and machine learning to develop robust algorithms for supervisory systems and fault detection in electromechanical actuators. Notable contributions include kernel-based identification methods, visualization tools for classification results (Confusion Star/Gear), and supervision frameworks for industrial equipment. He co-founded AISent srl, applying technological solutions to industry challenges. He teaches courses like Adaptive Learning and Estimation , System Identification , and Advanced Methods for Fault Diagnosis . His research spans aerospace applications (e.g., jamming detection in aircraft actuators), vibration signal analysis, and data-driven control strategies. Recent projects include robust filter design for electromechanical systems and guidelines for industrial supervision solutions.

• Autonomous Robot Systems
• Applied Ocean Science
• Quantum Engineering
• +4 more

Mohammad Javad Khojasteh is a Gleason Endowed Assistant Professor in the Department of Electrical and Microelectronic Engineering at the Kate Gleason College of Engineering, Rochester Institute of Technology (RIT). He directs the Khojasteh Autonomous Systems Laboratory (KAS Lab) and is affiliated with RIT's Global Cybersecurity Institute (GCI) and Center for Human-aware AI (CHAI). Before joining RIT, he held postdoctoral positions at Scripps Institution of Oceanography (MPL), MIT’s Department of Mechanical Engineering and LIDS, and Caltech’s CAST, collaborating with NASA JPL’s Team CoSTAR. Education: B.Sc. in Electrical Engineering and Mathematics, Sharif University of Technology (2015) M.Sc. in Electrical and Computer Engineering, UC San Diego (2017) Ph.D. in Electrical and Computer Engineering (Intelligent Systems, Robotics, and Control), UC San Diego (2019) Research Interests: Dr. Khojasteh focuses on autonomous systems, applying machine learning and control theory to enhance robotics, marine autonomous systems, and quantum engineering. His work spans cybersecurity in cyber-physical systems, data-driven optimization, and statistical signal processing. He emphasizes practical applications in ocean science and quantum technologies. Key Contributions: His research has been recognized with awards such as the Tammy L. Blair Student Paper Award. He explores topics like particle flow filters, event-triggered control, and secure autonomous navigation. His lab’s projects include developing robust algorithms for underwater robotics and quantum sensor networks. Advising & Grants: While specific grants are not detailed, his work indicates a focus on multi-agent systems, safety-critical control, and adversarial learning. He advises students in robotics and control systems, though no named advisees are listed. Labs & Teams: Director of KAS Lab, collaborating with GCI and CHAI on human-AI interaction and cybersecurity challenges in autonomous systems.

• Nanomaterials
• Biomedical Engineering
• Environmental Science
• +3 more

Prof. Christian Adlhart is a Professor at the ZHAW School of Life Sciences and Facility Management, leading the Functional Materials and Nanotechnology Network. His research focuses on nanomaterials, biomedical engineering, and environmental applications, with a strong emphasis on nanofiber-based materials. He has led numerous projects, including advancements in antimicrobial coatings, biocompatible implants, and nanofiber aerogels for filtration and medical applications. His work bridges materials science and biotechnology, addressing challenges in regenerative medicine, environmental remediation, and healthcare innovation. Key roles include project leadership in initiatives like AMiCI (anti-microbial coatings) and tPDT (photodynamic therapy). He is affiliated with networks like COST Action MP1206 (electrospinning) and holds an ORCID identifier (0000-0002-4081-221X). His recent publications explore topics such as cellulose nanofiber sponges, supercritical drying of nanofibers, and SARS-CoV-2 prevention materials. Research interests span nanofiber fabrication, biomedical applications, and sustainable materials. His lab develops advanced filtration systems, biocompatible scaffolds, and functional coatings. He has contributed to over 50 peer-reviewed articles and holds patents in gas extraction devices and catalytic processes.