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Fei Chen is a Research Fellow in the School of Mathematics at Trinity College Dublin. Their work focuses on interdisciplinary research at the intersection of mathematics, neuroscience, and biomedical engineering. Current research interests include predictive coding models in auditory perception, Bayesian inference frameworks for phantom perception, and applications of machine learning in diagnosing hearing-related disorders. Fei's recent publications explore topics such as auditory illusion modeling, chronic pain mechanisms through predictive processing lenses, and systematic reviews of autoimmune-related hearing loss. Their work combines advanced mathematical modeling with clinical data analysis to advance understanding of sensory perception disorders. Advisees/PhD students: None listed at this time. No scientific awards mentioned in available records. Research activities include collaboration with clinical teams to investigate neural networks involved in auditory processing anomalies and developing computational tools for hearing diagnostics.

• Mathematics
• Applied Mathematics
• Computational Neuroscience
• +3 more

Luca Spalazzi is an Associate Professor at the Department of Information Engineering , Università Politecnica delle Marche , Italy. His research spans multiple domains including cybersecurity , blockchain technology , machine learning , and telerehabilitation systems for Parkinson's disease. He applies formal methods to software verification and security analysis, with a focus on real-time systems and distributed architectures . Key research areas: Cybersecurity, Blockchain, Machine Learning, IoT, Formal Verification Recent work: Blockchain-based sustainable supply chains, Zero-Knowledge Proofs, Smartphone health monitoring His publications (2013-2025) demonstrate expertise in malware detection , smart contract verification , and AI-driven health solutions . Articles include BRAIN 2024 workshop organization and RAPIDO system for Parkinson's telerehabilitation.

• Computer Science
• Cybersecurity
• Blockchain Technology
• +5 more

Sérgio Filipe Carvalho Ramos serves as Coordinator Professor at the School of Engineering (ISEP) of the Polytechnic Institute of Porto (IPP), where he has held academic positions since 2001. Since 2021, he directs the Bachelor Program in Electrical Engineering - Electrical Power Systems and previously served as deputy director of the Electrical Engineering Department (2018-2020). He maintains active research collaborations with international institutions including Universidade de Vigo and Universidade da Coruña in Spain, and UNESP in Brazil. His educational background includes a PhD (2015) and MSc (2006) in Electrical and Computer Engineering from the University of Lisbon - IST. His research focuses on smart grids, energy communities, data mining applications in power systems, and renewable energy optimization . He has pioneered work in smart buildings optimization, shared PV generation, and flexible power contracts through significant R&D projects. The analysis of his recent publications reveals strong trends in energy community modeling , with 8 of the 15 most recent papers addressing peer-to-peer energy sharing, community optimization, and local market design. His work increasingly integrates machine learning for forecasting (particularly for EV integration and PV generation) and employs advanced optimization techniques including game theory and MBNLP methods. The research consistently targets practical implementation in smart grid contexts with emphasis on real-world applicability. Premio REN 2008 Scientific Publication Merit from IPP (2011, 2015, 2023) Ramos has supervised 2 PhD students (ongoing), 29 MSc, 6 ERASMUS, and 116 BSc students. His grant portfolio demonstrates exceptional success in securing competitive funding, including FCT projects BENEFICE and SPET as PI/Co-PI, the EU-funded SATCOMM project coordinating Atlantic energy pilots, and multiple Honda Research Institute consultancies. His research group has successfully coordinated over 20 national and international R&D projects with total funding exceeding €5M. As a core researcher in the GECAD research group, he leads initiatives in smart buildings and energy communities. He serves as General Secretary for IPP at ATHENA European University and participates in the CARPE Network's Sustainable and Smart Cities working group, demonstrating institutional leadership beyond his departmental responsibilities.

• Smart Grids
• Energy Communities
• Data Mining Applications in Power Systems
• +7 more

Tianlong Chen is an Assistant Professor in the Department of Computer Science at The University of North Carolina at Chapel Hill , starting in Fall 2024. His research focuses on AI trustworthiness, efficiency, and scientific applications , particularly through sparsity, multimodal learning, and large language model (LLM) innovations. Research Interests include: Sparsity techniques for LLM optimization Multimodal learning and graph neural networks AI safety and privacy preservation Quantum computing applications Biological-informed AI systems Recent Trends in his publications emphasize Mixture-of-Experts (MoE) , LLM safety mechanisms , and lifelong learning architectures . Awards highlight recognition from Amazon, UNC Provost, NAIRR, and AAAI. Scientific Awards : Amazon Research Award (2025) UNC Accelerating AI Awards (2025) NAIRR Pilot Award (2025) CPAL/KAUST Rising Star Awards (2025) AAAI New Faculty Highlights (2025) Advising : Mentors 19 Ph.D. students across UNC Chapel Hill and remote collaborations, focusing on AI4Science, LLMs, and quantum computing. Grants include Cisco Research funding and UNC Provost AI support.

• Artificial Intelligence
• Machine Learning
• Large Language Models
• +5 more

Morten Bech Kramer is an Associate Professor in the Department of the Built Environment at Aalborg University, part of The Faculty of Engineering and Science. His research focuses on wave energy converters, numerical modeling of ocean energy systems, computational fluid dynamics (CFD), and hydrodynamic interactions in marine environments. He leads the Ocean and Coastal Engineering Research Group and contributes to the BLUE – Marine & Maritime Research initiative. Key projects include the Competitive Renewable Energy Platforms Based on Shipbuilding Methods (2023–2026) as PI, and collaborations on the Wavestar and AquaBuOY wave energy converters. His work spans experimental testing, numerical validation, and optimization of renewable energy systems. Kramer has supervised 2 PhD students and contributed to over 117 publications since 2001, including high-impact studies on CFD optimization and wave energy modeling standards. His research has been highlighted in media such as North Sea Region funds ocean energy pilots scale-up (2018) and Danskere bygger verdens største testfacilitet til bølgekraft (2020). Kramer is actively involved in international initiatives like the IEA Ocean Energy Systems Task 10, advancing global standards for wave energy modeling and validation. His technical expertise includes hydrodynamic analysis, power take-off system design, and reliability assessment of offshore energy infrastructure. Kramer’s work bridges theoretical models with practical applications, driving innovation in marine renewable energy technologies.

• Wave Energy Engineering
• Renewable Energy
• Computational Fluid Dynamics
• +5 more

Felipe Werndl Trevizan is a Senior Lecturer in the School of Computing at the Australian National University (ANU), where he conducts research at the intersection of Artificial Intelligence, Operations Research, and Machine Learning. His work focuses on automated planning and scheduling, reasoning under uncertainty, heuristic search, and machine learning for planning. He is actively involved in research projects related to uncertainty-centric pilot assistance systems and probabilistic planning. His research interests include: Automated Planning and Scheduling Probabilistic and Multi-Objective Planning Heuristic Search and Admissible Heuristics Deep Learning for Generalized Planning Constraint-Based and Risk-Aware Planning Learning Heuristics from Data His recent publications demonstrate a strong trend toward integrating machine learning with classical planning techniques, particularly in learning reliable, domain-independent heuristics using both deep and classical machine learning methods. He has developed novel algorithms for constrained and stochastic shortest path problems, multi-objective probabilistic planning, and generalized planning using neural networks. His scientific awards include: Best Paper Award at ICAPS 2016 Best Paper Award at ICAPS 2017 2016 Kikuchi-Karlaftis Best Paper Award from the Transport Research Board Felipe Werndl Trevizan is registered to supervise research students and has advised several successful projects in AI planning. He has secured research grants for projects such as 'Integrated Planning for Uncertainty-Centric Pilot Assistance Systems' and 'Chance-Constrained POMDP for Pilot Assistance Systems' at ANU. He is also organizing key community events including the 'Reliability In Planning and Learning (RIPL)' workshop and a tutorial on 'Learning for Planning' at ICAPS 2025. He is affiliated with the School of Computing at ANU and previously worked as a Senior Research Scientist at NICTA and Data61/CSIRO. His research is supported by active collaborations with leading researchers such as Sylvie Thiébaux, Hanna Kurniawati, and others.

• Artificial Intelligence
• Automated Planning and Scheduling
• Reasoning under Uncertainty
• +9 more

Dr. Neelakshi Majumdar is an Assistant Professor in the Department of Mechanical Engineering at the University of Arkansas, where she leads the Aerospace Systems Engineering and Transportation (ASYST) Lab. Her research focuses on enhancing aerospace and transportation safety through aerospace systems engineering, data analysis, machine learning, and human-subjects research. Ph.D. in Aeronautical and Astronautical Engineering, Purdue University (2023) M.S. in Aeronautical and Astronautical Engineering, Purdue University (2018) B.E. in Electronics and Communication Engineering, Chitkara University, India (2014) Dr. Majumdar's research integrates systems engineering principles with human factors and machine learning to address challenges in aviation safety, including inflight loss of control, stall/spin accidents, and maintenance-related incidents. Her lab develops predictive models using NTSB data and conducts experiments with flight simulators to assess pilot proficiency. Her recent publications in the Journal of Air Transportation and AIAA Scitech Forum highlight trends in machine learning applications for aviation safety , human factors in accident prevention , and emerging risks in Advanced Air Mobility (AAM) . She collaborates with institutions like the FAA and Advanced Air Mobility Institute, translating research into pilot training and regulatory improvements. Finalist, Stanley N. Roscoe Best Student Paper Competition (2023) 2nd Place Winner, Purdue University Research Symposium (2023) Rising Stars in Aerospace, University of Colorado Boulder (2022) Teaching Fellowship, Purdue University (2022) Outstanding Graduate Student Researcher Award, FAA PEGASAS (2021) Autodesk Design and Innovation Award (2019) At the ASYST Lab, Dr. Majumdar supervises graduate and undergraduate researchers, including Sydney Sommers , Mehedi Hasan , and Toluwalase Olatunji , while securing grants from the University of Arkansas Honors College. She also promotes STEM education through initiatives like youth workshops with flight simulators.

• Aerospace Systems Engineering
• Transportation and Systems Safety
• Human Factors
• +5 more

Yevheniya Volchko is an Associate Professor at Chalmers University of Technology's Department of Geology and Geotechnics, where she leads research in subsurface planning and soil remediation. She coordinates the Engineering Geology research group, focusing on sustainable development of underground resources. Research Interests: Her work integrates ecological risk assessment, economic valuation of remediation measures, and probabilistic modeling to advance sustainable soil management. Key areas include geosystem services, nature-based solutions for contaminated land, and stakeholder-driven frameworks for urban brownfield redevelopment. Project Leadership: Volchko directs multiple initiatives, including: RECOVER (2025-2026): Climate-smart agriculture on demined land in Ukraine SPADES (2024-2028): Spatial planning integrating soil science ISLANDR (2023-2026): Information-based land remediation strategies ECO-GRO (2019-2024): Gentle remediation for ecosystem services Collaboration: She partners with institutions like the Swedish Geotechnical Institute, European Commission, and multiple universities to translate research into practical environmental solutions.

• Subsurface Planning
• Soil Remediation
• Ecological Risk Assessment
• +4 more

Henri Gavin is a Professor in the Department of Civil and Environmental Engineering. His research focuses on developing innovative solutions for structural resilience, control systems, and earthquake engineering. He leads interdisciplinary projects integrating sensor technology, IoT systems, and machine learning for real-world applications such as earthquake early warning systems. Research Interests: Professor Gavin's work spans earthquake engineering, structural dynamics, vibration isolation, robotics, optimization, and machine learning applications in civil infrastructure. His signature project—Pilot Earthquake Early Warning in Kathmandu (Data+, 2022)—demonstrates his approach to combining AI models with geophone sensors and IoT networks for on-site seismic alerts. Publication Trends: His recent articles (2020-2024) emphasize structural reliability, decentralized control of robotic systems (UAVs/swarms), optimization algorithms, and seismic protection strategies. This reflects a consistent focus on theoretical rigor applied to practical engineering challenges, particularly in nonlinear dynamics and multi-agent coordination. Projects and Advising: He mentors students through Duke's Data+ program, guiding projects in energy data analytics and earthquake early warning systems. Notable funded initiatives include instrumentation and modeling of seismic isolation systems (EAGER, 2012) and performance analysis of base-isolated structures during seismic events.

• Earthquake Engineering
• Structural Control
• Vibration Isolation
• +5 more

Overview Brian D. Stemper, PhD, is a Professor in the Joint Department of Biomedical Engineering at the Medical College of Wisconsin and Marquette University, with a secondary appointment in Neurosurgery. He directs the Zablocki VA Medical Center Neuroscience and Biomechanics Research Labs. His research focuses on biomechanics of traumatic brain injury, spinal mechanics, and military trauma, utilizing experimental, imaging, and computational methods. Education PhD, Biomedical Engineering, Marquette University, 2004 BS, Biomedical Engineering, Milwaukee School of Engineering, 1998 Research Interests Dr. Stemper’s work integrates biomechanical analysis of head, neck, and spinal trauma, with applications in automotive safety, military protection, and clinical neurosurgery. He has published over 60 peer-reviewed articles and secured grants from agencies like the U.S. Air Force and NIH. His labs specialize in injury modeling and translational research. Awards & Leadership Recipient of the Best Paper by a Young Researcher (2004 IRCOBI) and multiple leadership roles in societies like the American Society of Mechanical Engineers. He chairs the Institutional Animal Care and Use Committee at Zablocki VA Medical Center. Grants & Labs Led projects on military blunt trauma, aviation biomechanics, and repetitive head injury. His labs collaborate with institutions like the VA, NASA, and the Department of Defense, focusing on injury prevention and clinical translation.

• Biomechanics of Head, Neck, and Spine
• Traumatic Brain Injury
• Spinal Biomechanics
• +5 more

Associate Professor Jose Almeida Da Silva holds a position at RMIT University's School of Engineering in Melbourne, Australia. With over 20 years of academic experience, he specializes in aviation safety, aerospace materials, and structural integrity. His work bridges academia with industry through collaborations on projects involving accident investigation and safety management systems. He earned a 5-year Aeronautical Engineering degree from the University of Beira Interior (1991–1996), where he was recognized as the top graduate. Later, he received the Santander Scientific Merit Prize (2010–2013) as the best researcher in aerospace sciences. Professional credentials include a Remote Pilot Licence from CASA and memberships in the Royal Aeronautical Society and AIAA. Research focuses on aviation safety systems, composite materials, and passenger anthropometry's impact on aircraft performance. Recent work explores augmented reality in accident analysis and Bayesian networks for unmanned aircraft safety assessments. He supervises PhD/Masters students on topics like safety culture in military aviation and composite material maintenance strategies. Awards: Santander Merit Prize, Portuguese Air Force Merit Award, University of Beira Interior's Top Graduate Professional Affiliations: AIAA Senior Member, Royal Aeronautical Society Member Key Projects: Aviation Safety Programs, UAV Risk Modeling, Structural Fatigue Monitoring

• Aviation Safety
• Safety Management Systems
• Aircraft Structural Integrity
• +7 more

Xiaofeng Liu is an Assistant Professor at Yale School of Medicine with joint appointments in Radiology & Biomedical Imaging and Biomedical Informatics & Data Science . He is an Associate Member at the Broad Institute of MIT and Harvard , and actively engaged in editorial roles as Associate Editor for IEEE Transactions on Neural Networks and Learning Systems and Journal of Medical Internet Research . His research spans trustworthy AI , medical imaging , and data science with applications in disease diagnosis and treatment monitoring. His research focuses on generalizable AI models for medical imaging, particularly in domain adaptation , diffusion models , and multimodal analysis . Recent work trends include AI-driven oncology (e.g., glioblastoma survival prediction), medical image enhancement (super-resolution, PET denoising), and clinical decision systems for Crohn's disease and depression detection. Collaborations with Georges El Fakhri and Jinsong Ouyang demonstrate cross-disciplinary approaches. 2025 Robert F. Wagner Best Student Paper Finalist Award 2024 Trailblazer R21 NIH Award 2024 NSF NAIRR Pilot Award 2024 Google Cloud Research Credits The Xiaofeng Liu Lab (Whisk Cup) develops AI methods for biomedical imaging, affiliated with the Yale Biomedical Imaging Institute and Center for Brain & Mind Health . The lab trains students in deep learning , medical image analysis , and health informatics .

• Trustworthy AI
• Medical Imaging
• Data Science
• +6 more

René van Paassen is an Associate Professor in the Control & Simulation department at the Faculty of Aerospace Engineering, Delft University of Technology. His work bridges human factors engineering and advanced flight simulation with significant contributions to aviation safety and pilot training methodologies. His research focuses on human-in-the-loop vehicle simulation , real-time distributed simulation systems , and aviation human factors . Key areas include motion cueing algorithms for aircraft upset recovery, pilot startle response mitigation, and decision-support interfaces for next-generation propulsion systems. His fingerprint analysis reveals dominant expertise in control systems (100%), human factors (86%), aircraft dynamics (46%), and simulation design (46%). Analysis of his 2025 publications shows consistent emphasis on human-machine interaction in high-stakes aviation scenarios , particularly how simulation fidelity affects pilot responses to unexpected events. Recent work integrates cognitive psychology with engineering to develop countermeasures for startle effects and optimize training under performance pressure. 2024 AIAA de Florez Award for Flight Simulation (for human-in-the-loop simulation contributions) 2022 IFAC HMS Best Paper Award (probabilistic estimation in manual control) 2019 Andrew P. Sage Best Transaction Paper (human-machine systems) 2013 AHS Best Paper Award (helicopter control systems) 2015 Conference Best Paper Award (conflict detection in air traffic) Van Paassen has supervised 21 graduate students and led development of the DUECA/DUSIME middleware for distributed real-time simulations. His work informs aviation safety protocols through partnerships with AIAA and IFAC, with recent press coverage highlighting applications for hydrogen-electric aircraft and startle-effect mitigation in commercial aviation.

• Control Systems
• Human Factors
• Aircraft Simulation
• +5 more

Dr. Atilla Dogan is a Professor in the Department of Mechanical and Aerospace Engineering at The University of Texas at Arlington (UTA) , part of the College of Engineering. He also serves as Executive Vice President of the Aircraft Division at TAI (Turkish Aerospace Industries, Inc.). Education : He holds a PhD (2000), MS (1998), and BS (1991) in Aerospace/Aeronautical Engineering from the University of Michigan and Istanbul Technical University. Research Interests : Focus on Flight Dynamics and Control, Unmanned Vehicle Systems, Autonomous Systems, and Aerial Refueling. His work emphasizes nonlinear flight simulation, path planning, and probabilistic modeling. Grants & Awards : Recipient of multiple awards including the AIAA Associate Fellowship (2016), Phi Kappa Phi Professorship (2013), and Research Excellence Awards (2008, 2006). Active in funding initiatives like STAARS (Safe Task-Aware Autonomous Resilient Systems). Advising & Teaching : Has advised over 30 graduate students and teaches advanced courses on flight mechanics, unmanned systems, and control theory. Supervises the Autonomous Vehicles Laboratory. Labs/Teams : Leads research in UTA's Autonomous Vehicles Lab, focusing on UAV navigation, formation flight, and aerial refueling dynamics.

• Flight Dynamics and Control
• Nonlinear Flight Simulation
• Unmanned Vehicle Systems
• +4 more

Paul Milewski is the Department Head and Professor of Mathematics at the Department of Mathematics, The Pennsylvania State University, affiliated with the Eberly College of Science. His research focuses on applied mathematics, numerical methods, fluid mechanics, and nonlinear waves. Education: Ph.D. in Mathematics from the Massachusetts Institute of Technology (1993). Research interests include fluid dynamics phenomena such as gravity-capillary waves, nonlinear wave interactions, and hydroelastic wave dynamics. He has contributed to studies on Faraday pilot-wave dynamics, three-dimensional flexural-gravity waves, and the mathematical modeling of geophysical flows. His work often bridges theoretical analysis with computational methods. Recent research trends involve modeling complex fluid systems like droplet rebounds, internal solitary waves, and compressor surge prediction. Collaborations include special issues dedicated to peers like Professor Jean-Marc Vanden-Broeck. His research has been published in journals such as Journal of Fluid Mechanics and Studies in Applied Mathematics , with a focus on advancing understanding of nonlinear wave behavior and fluid-structure interactions.

• Fluid Mechanics
• Nonlinear Waves
• Applied Mathematics
• +3 more