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Thijs HazenbergView profile

Researcher

• Plasma-assisted combustion
• Metal fuels
• Combustion simulation
• +3 more

Thijs Hazenberg is a Researcher at the Department of Mechanical Engineering, Eindhoven University of Technology (TU/e), specializing in plasma-assisted combustion and metal fuel combustion. He holds a master's degree from TU/e (2019) and conducted his internship at Rolls-Royce Deutschland. His research focuses on numerical techniques for simulating plasma-assisted combustion and metal fuel oxidation, contributing to emission reduction and sustainable energy solutions. He is part of the Power & Flow group under Prof. van Oijen and collaborates on projects like MPACE (plasma-assisted combustion) and zero-carbon metal fuel studies (2020-2025). His work emphasizes aerosol combustion dynamics, flame propagation, and iron particle oxidation. Recent studies explore radiative heat transfer effects on iron-air aerosol flames and emission control strategies in iron powder burners. He has received awards including the NVV combustion award (2019) for his master's thesis on metal flame models and the KNCV Golden Master Award (2020). Key projects involve multi-scale understanding of metal fuel combustion (2020-2025) and plasma-assisted combustion efficiency (2018-2022). Collaborations span experimental and theoretical approaches, with publications in Combustion and Flame and Proceedings of the Combustion Institute . His academic contributions bridge computational modeling with sustainable energy applications.

Benjamin Ultan CowleyView profile

Professor

• Cognitive science
• Computer and information sciences
• Neurosciences
• +7 more

Benjamin Ultan Cowley is Professor of Learning in Humans and Machines at the University of Helsinki 's Doctoral Programme Brain & Mind and Doctoral Programme in Cognition, Learning, Instruction and Communication . He obtained his PhD in Computer Science from the University of Ulster in 2009 after completing his Bachelors in ICT at Trinity College Dublin (2003). As leader of the HiPerCog research group , his work focuses on high performance cognition – studying how humans master complex cognitive tasks. Current research integrates cognitive science with educational technology through projects like AiWo (Human-Centric AI for fieldwork operations) and AiPerCog (AI learning from human gameplay). He also investigates decision-making in extreme environments through avalanche research collaborations. Recent publications demonstrate his interdisciplinary approach: 2025 studies include SSSUMO for real-time submovement decomposition, Structured human-LLM interaction for AI content generation dynamics, and Mechanisms of learning in ADHD using EEG biomarkers. His work bridges neuroscience, computer science, and educational psychology while developing practical applications for ADHD treatment and outdoor safety. Dr. Cowley currently manages two active projects: AIWo (Business Finland, 2025–2027) and AI Personality and Cognition (Academy of Finland, 2023–2027), while serving as project manager for the GUESSED project on uncertainty in experiential decisions (2021–2025). His research has been funded by NordForsk, Business Finland, and the Academy of Finland.

ALI ŞENDURView profile

Associate Professor

• Applied Mathematics
• Numerical Analysis
• Mathematics Education
• +3 more

Assoc. Prof. Ali Şendur holds an Associate Professor position at the Department of Mathematics Education, Faculty of Education, Alanya Alaaddin Keykubat University. He obtained his Ph.D. in Mathematics from Izmir Institute of Technology (2012) and has held academic positions at institutions like Akdeniz University and Mediterranean University. His research focuses on applied mathematics, numerical analysis, and mathematics education technology integration. He has served in administrative roles including Head of Department, Vice Dean, and Erasmus Coordinator. Key educational qualifications include: Ph.D. in Mathematics, Izmir Institute of Technology (2012) M.Sc. in Mathematics, Dokuz Eylül University (2007) B.Sc. in Mathematics, Dokuz Eylül University (2002) Research interests span numerical methods for PDEs (convection-diffusion-reaction systems), finite element stabilization techniques, epidemiological modeling, and technology-enhanced mathematics education. Notable projects include design-based studies on Web 2.0 tools for teacher training and TÜBİTAK-funded research on mathematical applications. Recent publications emphasize hybrid numerical methods for singular perturbations, AI/AR integration in geometry education, and epidemiological modeling of health policies. He has received multiple TÜBİTAK awards for international scientific contributions (2012–2021).

• Environmental Science
• Air Quality Modeling
• Machine Learning Applications
• +3 more

Dimple Pruthi is a Research Fellow in the Gangarosa Department of Environmental Health at Emory University. Her work focuses on advanced computational methods for air quality prediction, integrating machine learning, satellite data analytics, and environmental modeling. She specializes in PM2.5 forecasting, wildfire impact analysis, and sustainable pollution monitoring systems. Her research interests include developing hybrid machine learning models for environmental applications, analyzing transient weather effects on pollution, and optimizing neuronal networks for air quality indices. She has extensively studied Delhi's air quality dynamics and California wildfires' particulate matter emissions. Key trends in her publications (2016–2025) reveal a focus on satellite-based PM2.5 prediction using GOES-R data, low-cost sensor systems, and fractal/wavelet analysis for pollutant variability. She combines computational techniques with environmental science to address urban pollution challenges and climate change impacts. No scientific awards or grants are explicitly listed. Her advising record is not provided, but her work contributes to environmental health policy through predictive modeling frameworks.

• Developmental Psychology
• Parenting Behavior
• Neuroscience
• +3 more

Tal Yatziv, Ph.D., is an Adjunct Assistant Professor at the Yale School of Medicine and a core member of the Child Study Center . She earned her Ph.D. in Psychology from Ben-Gurion University of the Negev, Israel, in 2019. Her research focuses on the interplay of cognitive and affective processes in early parenting , examining how parental executive functions and automatic processing shape infant socioemotional development. Key areas include parental mentalization , neural correlates of parenting , and contextual influences on parent-infant interactions. 2024 : Neural markers of maternal anxiety 2022 : Parental mentalizing during the pandemic 2020 : Executive functions in maternal reflective functioning Dr. Yatziv employs multimodal methods including reaction-time measures, computational modeling , and video-based observational analysis . Her work spans diverse contexts like conflict zones and posttraumatic stress, with a emphasis on ecological validity and developmental outcomes . She received the SRCD Small Grant for Early Career Scholars (2020) . Her lab, The Before and After Baby Lab, integrates systems immunology and behavioral science to advance understanding of adaptive parenting mechanisms .

• Econometrics
• Macroeconomics
• Time-series analysis
• +5 more

Dr. Daniel Lewis is an Associate Professor in the Department of Economics at University College London (UCL). His research focuses on econometric methods for evaluating macroeconomic policies and developing statistical inference techniques applicable to realistic macroeconomic data. He holds a Ph.D. from Harvard University and a B.A. from Princeton University. He previously served as a Senior Economist at the Federal Reserve Bank of New York and currently holds non-academic roles at the Banque de France and the Centre for Microdata Methods and Practice. His work includes creating the Weekly Economic Index (WEI), a real-time economic activity measurement tool, and he leads the CreMac project funded by an ERC Starting Grant. He also serves as an Associate Editor of the Journal of Econometric Methods . Education: Ph.D. in Economics, Harvard University (2013–2018) B.A. in Economics, Princeton University Research Interests: Econometric methods for causal inference in time-series data Macroeconomic policy evaluation (monetary/fiscal) Statistical identification and testing Real-time economic measurement via the Weekly Economic Index (WEI) HAR inference and clustering algorithms Grants & Awards: European Research Council Starting Grant (StG-101161596 CreMac) Consultancy & Advisory: Consultant, Banque de France (2024–present) Academic Consultant, Bank of England (2024–present) Research Staff, Centre for Microdata Methods and Practice (2022–present) Key Contributions: His publications emphasize methodological advancements in macroeconometrics, including shock identification, volatility analysis, and real-time economic tracking. He has organized major conferences such as the NY Fed-Board of Governors Conference on Empirical Macroeconomics and the Oxford-NY Fed-Bank of England Conference on Monetary Economics.

• Electrocatalysis
• Solar Energy Conversion
• Materials Science
• +3 more

Sol A Lee is a Postdoctoral Scholar Research Associate in the Department of Applied Physics and Materials Science at the California Institute of Technology (Caltech). His research focuses on advancing sustainable energy technologies through innovations in electrocatalysis, photoelectrochemistry, and materials science. Key areas include developing high-performance electrocatalysts for solar fuels production, improving water splitting efficiency, and enhancing CO₂ conversion systems. Lee’s work emphasizes the design of durable materials and scalable processes for renewable energy applications. His research interests span electrochemical energy storage, photocatalytic systems, and nanomaterials engineering. He explores novel catalysts for oxygen evolution reactions, solar-driven water oxidation, and CO₂ reduction, with a focus on material stability and reaction kinetics under real-world conditions. Lee has contributed to breakthroughs in operando measurements of membrane electrode assemblies and the development of 2D metal-organic frameworks for enhanced catalytic performance. Lee’s recent studies address challenges in variable-energy solar fuels systems and the integration of single-atom catalysts into membrane-coated electrolyzers. His work on graphene-based sensors and tailored nanostructures highlights interdisciplinary approaches to energy and environmental challenges. While no awards or grants are explicitly listed, his publications demonstrate impactful contributions to sustainable energy research.

Kalvir DhugaView profile

Associate Professor

• Nuclear Experimental Physics
• Optical Astronomy
• Gamma-ray Astrophysics
• +4 more

Kalvir Dhuga is an Associate Professor of Physics specializing in nuclear experimental physics, optical astronomy, and gamma-ray/X-ray astrophysics. His research focuses on X-ray binaries, exoplanet studies via transit timing variations (TTVs), and accretion phenomena. He is affiliated with the Department of Physics, contributing to classes like Modern Physics and Astrophysics courses. Education: BSc (1976) and PhD (1980) in Physics from the University of Birmingham, England. Research Interests: Nuclear physics (pion reactions, nucleon form factors), optical counterparts of X-ray sources, exoplanet detection through TTVs, and temporal analysis of X-ray binaries. Notable studies include ultraluminous X-ray sources (ULXs) in NGC galaxies and spectral transitions in low-mass X-ray binaries (LMXBs). Recent work emphasizes multiwavelength observations (Kepler/TESS missions) and disk-corona models for ULXs. His articles explore accretion dynamics, gamma-ray burst variability, and neutron star/black hole binary systems.

Klaus NeymeyrView profile

Professor

• Numerical Analysis
• Linear Algebra
• Chemometrics
• +3 more

Prof. Dr. Klaus Neymeyr is a Professor of Numerical Mathematics at the University of Rostock, affiliated with the Faculty of Mathematics and Natural Sciences and the Institute of Mathematics. Since 2023, he serves as Prodekan of the faculty. Previously, he was Dean (2014–2023) and an associated member at the Leibniz Institute for Catalysis (LIKAT). He obtained his habilitation in mathematics at the University of Tübingen (2001) and has held academic roles since 2003. His research spans numerical linear algebra, chemometrics, and catalysis, with a focus on eigenvalue problems, multivariate curve resolution (MCR), and spectral data analysis. Notable contributions include advancements in preconditioned eigensolvers and the development of FAC-PACK for feasible solution computation. Neymeyr’s work integrates computational methods with chemical applications, such as catalyst characterization via FTIR and NMR spectroscopy. He has been recognized with awards including the Kowalski Prize (2016) and a highly cited paper designation by ISI (2003). His collaborations extend to interdisciplinary projects in catalysis and biopharmaceutical data analysis. Publications emphasize algorithm development, convergence analysis, and data-driven methodologies. Scientific achievements include patents on energy-optimized pump regulation and contributions to the theoretical foundations of MCR and eigensolver convergence. His research group actively publishes in top journals like SIAM Journal on Matrix Analysis , Analytica Chimica Acta , and Journal of Chemometrics .

Robert KieschnickView profile

Associate Professor

• Corporate Finance
• Mergers and Acquisitions
• Corporate Restructuring
• +5 more

Robert Kieschnick is an Associate Professor of Finance and Managerial Economics at the Naveen Jindal School of Management, University of Texas at Dallas. He has held academic positions since 1987, including roles at George Mason University, University of Manitoba, and the University of Texas at Austin. His research focuses on corporate financing, mergers & acquisitions, working capital management, IPOs, and corporate governance. He directs the MS in Financial Technology and Analytics program and previously coordinated the Finance and Managerial Economics group. Education includes a PhD in Finance from the University of Texas at Austin (1987), MA in Economics from UT Austin (1976), and B.A. in Economics from Southern Methodist University (1972). Professional experience includes roles as a Senior Economist at the Federal Communications Commission (1994–1999) and Senior Financial Analyst at Southern Union Gas Company (1984–1986). Research interests emphasize corporate restructuring, valuation methods, and risk management strategies. Key publications address IPO underpricing, dual-class stock decisions, and the impact of operating leases on corporate finance. Awards include the Teppo Martikainen Best Paper Award (2001) and membership in Phi Kappa Phi. Grants include a three-year SSHRC Canada grant (2000–2003) for studying Canadian dual-class firms and a National Cable Television Association grant (2001) on cable diffusion. Current research explores algorithmic trading, spillover effects in executive compensation, and nonstationarity in governance-accounting relationships.

• Heterogeneous catalysis
• Reaction engineering
• Biorefining
• +5 more

Dr. Gabriel Luiz Lopes Fraga is a Research Fellow in Process Engineering at Queensland University of Technology's (QUT) School of Mechanical, Medical & Process Engineering, affiliated with the Centre for Agriculture and the Bioeconomy. He holds a BSc in Chemical Engineering (2014, Universidade Federal do Parana), MSc in Bioenergy (2016, University of Illinois), and a PhD in Heterogeneous Catalysis (2022, University of Queensland). His research focuses on reaction engineering, biorefining, and valorization of lignocellulosic and plastic wastes into fuels/chemicals, with emphasis on catalytic processes and techno-economic analysis. Key research areas include: heterogeneous catalysis, transfer hydrogenation, biomass/plastic conversion, and sugarcane industry optimization. He contributes to industry through consulting and training for process efficiency improvements. Recent work explores co-liquefaction of biomass/plastics and integrates PET recycling with pyrolysis. Publications highlight innovations in process design (e.g., furfuryl alcohol production, hydrogenation catalysts) and automation in sugarcane processing (e.g., massecuite control, sensor integration). His work balances academic research with industrial applications, addressing sustainability challenges in bioenergy and waste management. Teaching includes courses like Biorefineries and Sustainable Products (ENN436) and supervises undergraduate/master’s students. Collaborations span academia and industry, advancing scalable biorefinery technologies and circular economy strategies.

Yihua Bruce YuView profile

Professor

• Protein Biophysics
• Nuclear Magnetic Resonance (NMR)
• Biomaterials
• +7 more

Dr. Yihua Bruce Yu is a Professor in the Department of Pharmaceutical Sciences at the University of Maryland School of Pharmacy. He is also affiliated with the Institute for Bioscience and Biotechnology Research (IBBR), a collaborative institute between the University of Maryland and the National Institute of Standards and Technology (NIST), located in Rockville, MD. His research is centered on advancing pharmaceutical quality and safety through innovative biophysical technologies. B.S. in Biochemistry, Peking University Ph.D. in Biophysics, Johns Hopkins University Postdoctoral Training: NMR Spectroscopy (SUNY Buffalo), Protein Engineering (University of Alberta) Dr. Yu's research focuses on protein biophysics, biomaterials, and the development of water proton nuclear magnetic resonance (wNMR) technology for pharmaceutical manufacturing and quality control. His work enables noninvasive, real-time monitoring of biologics such as vaccines, therapeutic proteins, and gene therapy products. He is particularly interested in vaccine stability, excipient innovation, and preventive pharmacovigilance to reduce adverse events. His recent publications highlight the application of wNMR in detecting falsified drugs, characterizing vaccine formulations, monitoring bioprocessing, and ensuring product consistency. The research spans from fundamental biophysics to translational applications in point-of-care diagnostics and cold chain elimination for biologics. Dr. Yu has received several prestigious honors, including: Kimmel Scholar Award (2004) US Presidential Early Career Award for Scientists and Engineers (2005) Inaugural MPower Professor at the University of Maryland (2021) He actively mentors graduate students and postdoctoral researchers, offering dissertation projects and laboratory rotations. His lab collaborates with researchers from NIST, industry partners, and regulatory agencies such as the FDA, NIH, and USP. Dr. Yu’s team applies biophysical techniques to characterize biologics and improve pharmaceutical manufacturing standards. The Yu Lab, based at IBBR, operates at the intersection of academia, government, and industry, leveraging advanced NMR methods to solve critical challenges in biopharmaceutical development and quality assurance.

• Physical Education
• Motor Learning and Development
• Health Promotion
• +3 more

Xavier Garcia Masso is a Professor at the Faculty of Teacher Training, Universitat de València, specializing in the Didactics of Body Expression. His research focuses on motor competence, physical literacy, and health promotion through physical activity. He leads the Human Movement Analysis Group (HuMAG) and contributes to research in Physical Activity, Education, and Society (AFES) and Physical Activity and Health Promotion Group (AFIPS). His work employs advanced methodologies like self-organizing maps (SOM) and causal decomposition to analyze complex patterns in physical activity adherence, cognitive-motor integration, and postural control development. He designed the ALPHYL intervention protocol for physical literacy promotion and the ParaSportAPP for spinal cord injury patients' physical activity engagement. Recent publications examine topics from gamification in physical education to biomechanical comparisons of cycling equipment. His research spans developmental kinesiology, sports ergonomics, and educational technology implementation in physical education contexts. Key collaborations include motor competence assessment frameworks like Cognitive CAMSA and studies on neighborhood walkability's impact on active commuting. His work integrates interdisciplinary approaches across education, neuroscience, and public health domains.

• Process Control
• Real-Time Optimization
• Chemical Engineering
• +3 more

Dominique Bonvin is a Professor at the School of Engineering (STI) of École Polytechnique Fédérale de Lausanne (EPFL), holding a position within the Automatic Control Laboratory (LA). His research focuses on advanced process control, real-time optimization, and model-based systems engineering. Key topics include modifier adaptation for uncertain systems, dynamic optimization of chemical processes, and control strategies for reaction systems and energy systems. He has published extensively in top-tier journals such as Computers & Chemical Engineering and Journal of Process Control , with over 450 scholarly works to date. His work addresses challenges in industrial processes like wastewater treatment plants, gas compressors, and solid-oxide fuel cells, emphasizing robustness against plant-model mismatches. Collaborations span global institutions, with notable contributions to bioprocess modeling and control of energy-harvesting systems such as kite power. Research Themes: Real-Time Optimization (RTO), Model Predictive Control (MPC), Process Automation, and Systems Engineering Key Technologies: Modifier Adaptation, Dynamic Optimization, Port-Hamiltonian Systems, and Extent-Based Reaction Modeling His recent efforts include accelerating optimization algorithms (e.g., gradient-directed modifier adaptation) and integrating transient measurements for improved plant modeling. He has also pioneered the use of vessel extents to simplify reaction system analysis, enabling decoupled state estimation without full kinetic knowledge.

• Biomechanics of health
• Sports Training Theory & Application
• Stroke rehabilitation
• +5 more

Giannakou Erasmia is an Assistant Professor at the Biomechanics Division within the Faculty of Physical Education and Sports Sciences at the Democritus University of Thrace . Her expertise lies in Biomechanics of health with a focus on Sports Training Theory & Application . Her research integrates biomechanical analysis, musculoskeletal modeling, and artificial intelligence applications in healthcare. Teaching responsibilities include academic supervision during office hours (Tue 15:00-18:00 & Wed 15:00-17:00). While formal education details are not provided, her work demonstrates advanced training in biomechanics and clinical movement analysis. Research interests span post-stroke gait mechanics , musculoskeletal modeling validation , AI-driven assessment tools , and athletic performance analysis . Her recent publications (2022-2025) emphasize machine learning applications in stroke rehabilitation, gait mechanics quantification, and biomarker development for neurological conditions. No awards or grants are explicitly listed. Her work frequently involves collaborations in stroke recovery mechanisms, wrestling biomechanics, and translational clinical research.