جست‌وجوی استاد و پژوهشگر

Amir Tofighi Zavarehمشاهده پروفایل

استادیار

• Biomedical Engineering
• Medical Device Design
• Signal Processing
• +۴ مورد دیگر

Amir Tofighi Zavareh is an Assistant Professor in the Department of Engineering Technology and Industrial Distribution at Texas A&M University, specializing in Electronic Systems Engineering Technology. He is affiliated with the Center for Remote Health Technologies and Systems and Biomedical Engineering. His research focuses on analog and mixed-signal bioelectronic design, biomedical imaging, and wearable technology for healthcare applications. Dr. Tofighi Zavareh earned his Ph.D. in Electrical and Electronics Engineering from Texas A&M University in 2019. His work bridges biomedical engineering and signal processing, with a strong emphasis on developing innovative medical devices and wearable systems for real-time health monitoring. His research interests include wearable biosensors, machine learning-driven diagnostics, and improving mental health support in educational settings through technology. Notable projects involve eye-tracking metrics for online learning accessibility and stress-alleviation systems using emotion recognition. His publications span advancements in optical coherence tomography (OCT), retinal imaging systems, and AI-powered mental health tools. He collaborates across disciplines to address challenges in healthcare technology and education equity.

Ricardo Grau-Crespoمشاهده پروفایل

دانشیار

• Materials Science
• Computational Chemistry
• Energy Materials
• +۳ مورد دیگر

Dr. Ricardo Grau-Crespo is an Associate Professor of Materials Theory and Lead of the Chemical Sciences Research Division at the University of Reading. He is affiliated with the School of Chemistry, Food, and Pharmacy within the Department of Chemistry, focusing on computational materials science for clean energy applications. His research explores molecular-level simulations to investigate materials for energy storage and environmental technologies. Key projects include studies on spinel ferrites, thermal conductivity in pyrochlores, and nanofluids for thermal energy systems. He leads the GCMT Group (https://gcmt-group.github.io/) and is active in advancing computational methods for materials discovery, including machine learning applications. His work bridges theory and experiment, with notable contributions to photocatalysis, thermoelectrics, and interfacial phenomena in nanomaterials. Research Themes: Environment, Energy Materials, and Computational Materials Science. Collaborations include experimental partners for validation of computational models. Active in high-throughput screening and AI-driven material design, emphasizing sustainability and energy efficiency.

• Lithium-ion Battery Technologies
• Redox Flow Batteries
• Bioenergy
• +۵ مورد دیگر

Dr. Jacob Joseph Lamb is an Associate Professor at the Norwegian University of Science and Technology (NTNU), affiliated with the Department of Energy and Process Engineering within the Faculty of Engineering. He serves as the Study Program Manager for the Bachelor of Engineering in Renewable Energy (BIFOREN) and leads the Digital Energy Systems laboratory group. His roles include WP8 leadership in the FME Battery initiative and Theme Leader for Efficient Energy Use at ENERSENSE. Education: PhD in Energy and Process Engineering, NTNU (2013–2016) MSc in Chemical Engineering, University of Otago, New Zealand (2011–2012) BSc in Chemical Engineering, University of Otago, New Zealand (2008–2010) Research Interests: Dr. Lamb focuses on sustainable energy systems, particularly lithium-ion battery technologies , redox flow batteries , bioenergy , and digitization of energy systems . He explores sensor technologies for real-time monitoring and optimization of energy storage devices. His work integrates machine learning with physics-based models to enhance battery performance and reliability. Key Projects: FME Battery: Norwegian research initiative for advanced battery technologies ReZinc: Zinc-air flow battery development for stationary storage HeaLiSelf: Self-healing lithium-ion batteries using optical sensing and data analytics Computational studies on pre-lithiation processes and cold-climate battery performance Publications: His recent work emphasizes lithium-ion battery digitalization , SoC estimation , and electrode structuring . He bridges experimental and computational methods to address challenges in energy storage scalability and safety. Affiliations: ENERSENSE (Efficient Energy Use Theme) NTNU Thermal Engineering Laboratories

Apostolos Georgakisمشاهده پروفایل

دانشیار

• Biomedical Signal Processing
• Audio Engineering
• Electroglottography
• +۷ مورد دیگر

Dr. Apostolos Georgakis is an Associate Professor in Electrical and Electronic Engineering at the School of Computing and Engineering, University of West London (UWL). He joined UWL in 2017 after serving at King’s College London’s Division of Engineering. His academic role involves teaching and research in engineering with a strong focus on signal processing and biomedical applications. University: University of West London School: School of Computing and Engineering Department: Department of Electrical and Electronic Engineering Academic Rank: Associate Professor Email: apostolos.georgakis@uwl.ac.uk Dr. Georgakis holds an MSc in Mathematics and Statistics and a PhD in Engineering. His research interests center on biomedical signal processing, audio engineering, and medical diagnostics using advanced signal analysis techniques. He has made significant contributions to the fields of electroglottography for vocal tract pathology detection and heart rate monitoring via tracheal audio signals. His work bridges engineering with healthcare applications, particularly in non-invasive monitoring and diagnostic systems. His recent publications (2022–2024) demonstrate a clear trend toward applying digital signal processing and machine learning methods to medical diagnostics. Topics include laryngeal pathology detection using MFCC/GTCC features, systematic reviews on electroglottography, and automatic heart rate estimation during sleep. Earlier works (2014–2015) focus on theoretical signal restoration and denoising techniques using fractional Fourier transforms and mask operations, showing a strong foundation in mathematical signal processing. A 2019 publication also highlights his interdisciplinary work in thermal engineering involving liquid desiccant systems. Dr. Georgakis teaches across multiple programs, including: MSc Electronic and Robotic Engineering BEng (Hons) Electrical and Electronic Engineering (with and without Foundation Year) BSc (Hons) Sound Engineering (with and without Foundation Year) BSc (Hons) Mathematics and Statistics (with and without Foundation Year) MSc Digital Audio Engineering PhD Engineering While no specific scientific awards are listed, his sustained publication record in high-impact journals such as Digital Signal Processing , Signal Processing , and MDPI Diagnostics reflects active research engagement. He collaborates with researchers internationally, particularly in biomedical signal analysis and veterinary monitoring. Dr. Georgakis advises postgraduate students and supervises PhD candidates in engineering disciplines, though specific student names are not listed. He has not received mention of external research grants in the provided text, but his involvement in applied research suggests potential grant-funded projects. His work in wireless acoustic sensors and medical diagnostics may involve future expansion into wearable health technologies and AI-driven diagnostic tools. There is no mention of a dedicated lab or research team in the provided text, but his research themes suggest potential affiliation with biomedical engineering or audio signal processing groups within the School of Computing and Engineering at UWL.

Steve Davisمشاهده پروفایل

پژوهشگر ارشد

• Soft Robotics
• Automation
• Biomimetics
• +۴ مورد دیگر

Dr. Steve Davis is a Senior Research Fellow in Robotics at the University of Birmingham and Operational Director of The Birmingham Institute for Robotics. With over 25 years of expertise in robotics, his research focuses on soft robotics, biomimetics, advanced actuators, and robotics applications in healthcare, nuclear decommissioning, and the food industry. He holds a BEng, MSc, and PhD in Robotics from the University of Salford and a PGCert in Academic Practice. Education: BEng in Robotic and Electronic Engineering (1998), University of Salford MSc in Advanced Robotics (1999), University of Salford PhD in Robotics (2005), University of Salford PGCert in Academic Practice (2014), University of Salford Research Interests: Steve’s work spans soft robotics, biomimetic systems, and automation solutions for industries like food manufacturing and healthcare. His innovations include variable stiffness actuators, robotic hands, and grippers designed for safe human interaction. He has pioneered projects such as the Grail Robot for the food industry and contributed to EU-funded initiatives like SMART-E and FAIRSPACE. Publications Trends: His recent work emphasizes soft robotics actuators (e.g., pneumatic muscles, granular jamming grippers) and predictive maintenance methodologies. Collaborations with industry have led to practical automation solutions across sectors. Awards: Fellow of the Higher Education Academy (FHEA) Grants and Supervision: Steve has secured funding from UKRI, EPSRC, Innovate UK, and the EU. He has advised on MSc and PhD projects related to robotics in healthcare, space, and nuclear environments. Notable grants include the EPSRC FAIRSPACE Hub and Innovate UK’s Nuclear Decommissioning project. Labs and Teams: He leads research at the Birmingham Institute for Robotics and collaborates with the EPSRC Centre for Innovative Manufacturing. His work integrates academic research with industrial applications through projects like the Food Robotics Automation Center funded by Yorkshire Forward.

• Sustainable Power Systems
• Smart Grids
• Energy Physics
• +۴ مورد دیگر

Heidi Samuelsen Nygård is an Associate Professor in Energy Physics at the Department of Physics, Faculty of Natural Sciences and Technology, Norwegian University of Science and Technology (NTNU). She holds a PhD (2014) from the Norwegian University of Life Sciences (NMBU) on thermochemical biomass conversion in molten salts and has conducted postdoctoral research on CO2 capture in molten salts. Her research focuses on: Sustainable power systems and renewable energy integration Smart grids and power flexibility Molten salt technology for CO2 capture and energy applications Convection dynamics in porous media Recent publications highlight advancements in: Electric vehicle grid integration and demand flexibility Battery energy storage optimization Molten salt-based carbon capture systems Renewable energy forecasting algorithms She supervises master’s and PhD students in topics spanning grid frequency prediction, EV scheduling, thermal energy storage, and molten salt chemical processes.

Keikhosro Karimiمشاهده پروفایل

استاد

• Biotechnology
• Biofuel Production
• Waste Valorization
• +۳ مورد دیگر

Prof. Keikhosro Karimi is a Professor in the Department of Bio-engineering Sciences at Vrije Universiteit Brussel. His research focuses on sustainable biorefinery systems, waste valorization, and biofuel production. Key areas include biomass pretreatment, bioenergy optimization, and circular economy strategies for industrial and agricultural residues. Research Projects STEP-Chem (2025–2029): Technological strategies for a sustainable chemical industry. IPSU 2024: Smart biorefinery concepts for municipal biowaste valorization in Europe. Research Interests Prof. Karimi’s work integrates advanced pretreatment technologies, machine learning optimization, and life cycle assessment to address sustainability challenges in bioenergy systems. He explores innovative approaches for converting lignocellulosic biomass, marine macroalgae, and food industry byproducts into biofuels, biochemicals, and high-value materials. Recent Contributions Recent studies highlight breakthroughs in ultrasound-assisted biomass processing , fish waste biorefining , and blockchain-enabled food waste management . His work emphasizes scalability, economic viability, and environmental impact mitigation in bioprocess design. Grants & Collaborations Active collaborations include EU-funded initiatives and industry partnerships focused on bio-based economies. Ongoing projects aim to harmonize technological, socio-economic, and environmental dimensions of sustainable chemical production.

• Disaster Management
• Public Health Preparedness
• Emergency Response
• +۵ مورد دیگر

Dr. Curt Harris is an Associate Professor and Director of the Institute for Disaster Management (IDM) at the University of Georgia's College of Public Health. He holds concurrent appointments in Health Policy & Management and Epidemiology & Biostatistics. His roles include overseeing undergraduate and graduate educational programs, directing IDM's research and outreach initiatives, and serving as a liaison between the college administration and external partners. Dr. Harris earned a BS in Chemistry from Georgia College and State University and a PhD in Toxicology from UGA. His career at UGA spans over a decade, encompassing staff and faculty roles before becoming IDM Director. His research focuses on disaster management, public health preparedness, and emergency response systems, with recent emphasis on healthcare workforce resilience, nuclear event response, and pandemic preparedness. His recent publications highlight interdisciplinary approaches to disaster challenges, including nuclear fallout modeling, CNA staffing shortages, and integrating machine learning in burn patient outcomes. Dr. Harris leads major projects like the South Carolina Low Country Emergency Preparedness Program and the Southern Regional Disaster Response System. His work has been featured in media outlets like NPR, CBS46, and the Huffington Post. Dr. Harris teaches courses such as Introduction to Disaster Management and Public Health Crises and Disaster Management . He advocates for disaster education as a core competency in public health curricula. His professional service includes coordinating the CPH graduate program and advising on emergency medical protocols.

Kumar Sridharanمشاهده پروفایل

استاد

• Materials Science
• Metallurgy
• Nuclear Reactor Materials
• +۷ مورد دیگر

Prof. Kumar Sridharan is the Grainger Professor and Vilas Distinguished Achievement Professor at the University of Wisconsin-Madison , with appointments in the Departments of Nuclear Engineering & Engineering Physics and Materials Science & Engineering. His research spans materials science, metallurgy, and nuclear engineering, focusing on nuclear reactor materials, irradiation effects, corrosion, surface modification, and advanced manufacturing technologies. Research interests include: Nuclear reactor materials development Irradiation effects and corrosion of materials Surface engineering and coatings Machine learning applications for materials analysis High-temperature materials behavior Key awards: Bollinger Award for Vision and Leadership Chancellor’s Award for Excellence in Research Mentoring Undergraduates Award Fellowships in American Nuclear Society and other institutions

• Battery Management Systems
• Electric Vehicles
• Lithium-ion Batteries
• +۱۴ مورد دیگر

Professor Weixiang Shen is a full Professor in the Department of Engineering Technologies at the School of Engineering, Swinburne University of Technology, Melbourne, Australia. He holds a PhD in Electrical Engineering and has extensive academic experience across China, Germany, Singapore, and Malaysia. Bachelor of Engineering (BEng), Electrical Engineering Master of Engineering (MEng), Electrical Engineering Doctor of Philosophy (PhD), Electrical Engineering His research focuses on battery management systems for electric vehicles and renewable energy integration. Key areas include battery capacity estimation, charging strategies, fault diagnosis, thermal and mechanical management, and grid integration of EVs. He employs advanced techniques such as physics-informed machine learning, electrochemical modeling, and multidimensional sensing to enhance battery safety and performance. His recent publications (2024–2025) reveal a strong trend toward intelligent battery health monitoring, degradation modeling, and innovative thermal management using origami-inspired designs. These works appear in top journals like Applied Energy , IEEE Transactions , and Journal of Energy Chemistry . Associate Editor, IET Power Electronics Editorial Board Member, Journal of Energy Storage Founding Board Member, Vehicles Guest Editor, Applied Energy , Journal of Cleaner Production , Energy General Chair, ICEEE2018 Program Chair, CoEEPE2023 Professor Shen actively supervises PhD and Master’s students in areas such as battery fault diagnosis, energy storage, and control systems. His research is supported by grants from the Australian Research Council, Department of Industry, Science and Resources, and industry partners. He leads projects on intelligent energy management, battery testing, and EV control systems. His lab explores cutting-edge topics including solid-state batteries, multidimensional sensing, and origami-based thermal solutions for battery packs.

Hesham El-Askaryمشاهده پروفایل

استاد

• Global Climate Change
• Earth Systems
• Remote Sensing
• +۱۱ مورد دیگر

Dr. Hesham El-Askary is a Professor of Computational and Data Science at Schmid College of Science and Technology, Chapman University . With expertise in Global Climate Change, Remote Sensing, and Natural Disasters , his research spans atmospheric aerosols, marine ecosystems, and sustainable resource management. He holds a Ph.D. in Computational Sciences from George Mason University. B.Sc. Alexandria University M.Sc. George Mason University (×2) Ph.D. George Mason University His research interests focus on: Dust storm monitoring via remote sensing Climate change impacts on sea-level rise and coral reefs Renewable energy for sustainability Hydrological extremes and drought analysis AI/ML applications in environmental science Marine habitat and coastal zone management Recent publications highlight his work in: Machine learning for groundwater vulnerability Land surface temperature trends Coral reef monitoring in the Red Sea Solar energy optimization in Egypt/UAE Drought prediction in Mediterranean regions Awards & Grants : Chapman University Senior Wang-Fradkin Professorship (2015) Regional Coordinator for EU Horizon 2020 GEO-CRADLE Project ($3M, 2016) Saudi Environmental Management Award (2006) Funding from NSF, NASA, USDA, and EU As a IEEE and AGU member , he bridges environmental science with advanced computational methods.

• Engineering Geology
• Rock Mechanics
• Slope Stability
• +۵ مورد دیگر

Tümay Kadakci Koca is an Associate Professor in the Department of Geological Engineering, Faculty of Engineering at Muğla Sıtkı Koçman University. She holds a Ph.D. in Applied Geology from Dokuz Eylül University (2021), an MSc in Applied Geology (2011), and a BSc in Geological Engineering from Hacettepe University (2009). Research Focus: Engineering geology, rock mechanics, slope stability analysis, geotechnical engineering, and soft computing applications in geological problems. Academic Contributions: Over 15 publications focusing on rock slope stability in mining operations, soil burn severity mapping post-wildfires, and geomechanical properties of sedimentary rocks. Scientific Recognition: Recipient of Kemal Erguvanlı Engineering Geology Award (2022) and Altın Çekiç Geology Research/Article Award (1900). Projects: Led TÜBİTAK-funded research on post-fire soil burn severity in Muğla, contributed to dam reservoir landslide analyses, and consulted for private mining projects in Turkey. Her work integrates numerical modeling with field studies, emphasizing Turkey-specific geological challenges and environmental impacts.

• Climate Dynamics
• Numerical Weather Prediction (NWP)
• Atmospheric Modeling
• +۳ مورد دیگر

Professor Eigil Kaas is affiliated with the Niels Bohr Institute at the University of Copenhagen . His work spans climate dynamics , numerical weather prediction (NWP) , and atmospheric modeling . As former Section Head of Climate and Computational Geophysics , he leads research on climate-chemistry coupling and sea ice impacts. Education : MSc (1987) and PhD (1993) in Meteorology from University of Copenhagen Research Focus : Climate dynamics and physics Numerical methods in atmospheric models Machine learning for weather prediction Arctic sea ice-climate interactions Thunderstorm electricity and radiation Coupled atmosphere-ocean modeling Article Trends : Recent work combines neural networks with radiative transfer optimization Focus on storm dynamics and gamma-ray flashes Extreme precipitation modeling under climate change Pioneering tidal flow studies in Faroe Island fjords Teaching Legacy : Instructor of Atmospheric Physics and Dynamical Meteorology courses Developed zonally averaged climate model for educational use Mentored 12 PhD/MSc students with DMI/ECMWF collaborations Professional Roles : Chairman of BFI Group 28 (Geosciences & Climate) Scientific Advisory Committee member at ECMWF Project lead in EU ENSEMBLES and PEGASOS initiatives

• Intelligent Control Systems
• Fault and Anomaly Detection
• Virtual and Robust Sensors
• +۵ مورد دیگر

Dr. José Luis Calvo Rolle serves as a Professor in the Department of Industrial Engineering at the School of Engineering, Universidade da Coruña (UDC), specializing in Systems Engineering and Automation. His research focuses on intelligent control systems, fault detection, and virtual instrumentation within the Cybernetic Science and Technology Research Group. Teaches across multiple programs including Master's in Industrial Computing and Robotics, Textile Technology, and Occupational Risk Prevention Coordinates thesis supervision across Industrial Engineering and related disciplines His research spans intelligent control systems and optimization, with significant contributions in virtual sensors, fault detection, and AI-driven modeling for industrial applications. Current projects integrate machine learning with industrial processes for naval construction, wastewater treatment, and precision livestock farming, demonstrating cross-disciplinary impact from energy systems to agricultural technology. Recent publications reveal strong trends in applying deep learning to industrial metaverse frameworks, wastewater optimization, and livestock monitoring systems. His work bridges theoretical control engineering with practical implementations in energy management, naval manufacturing, and sustainable agriculture, frequently utilizing dimensionality reduction and one-class classification techniques. Dr. Calvo Rolle actively mentors students through thesis supervision across multiple engineering disciplines and coordinates research projects with diverse funding sources including the European Commission, Spanish National Research Agency, and industrial partners like Navantia and Telefónica. His laboratory work centers on the Cybernetic Science and Technology Research Group, developing testbeds for industrial automation, virtual instrumentation, and AI-driven monitoring systems. Current initiatives include digital twin implementations for naval manufacturing and smart energy management systems.

• Civil Engineering
• Climate Science
• Machine Learning
• +۶ مورد دیگر

Brennan Bean is an Assistant Professor in the Mathematics and Statistics Department at Utah State University's College of Arts & Sciences. His work focuses on geospatial modeling, statistical methods for extreme weather analysis, and machine learning applications in structural and environmental engineering. Recent publications highlight expertise in snow load prediction, Bayesian entropy, and interdisciplinary data science. Notable contributions include optimizing design methods for insulated concrete wall panels and addressing deployment challenges for ML models in engineering contexts. Research trends span geospatial data integration, climate change impact assessments, and educational interventions in STEM. Key subfields include ground snow load mapping, extreme value statistics, climate downscaling, and high-dimensional ecological modeling.