جست‌وجوی استاد و پژوهشگر

• Robotics
• Computer Architecture
• Cybersecurity
• +۳ مورد دیگر

Juan Felipe García Sierra is a Professor at the University of León, affiliated with the College of Industrial, Computer and Aerospace Engineering within the Department of Mechanical, Computer and Aerospace Engineering. His academic career focuses on interdisciplinary research bridging robotics, computer architecture, and cybersecurity with applications in pharmacology and medical informatics. He earned a PhD in 2011 with the thesis Contributions to visual attention computation and application to the control of a humanoid robot , supervised by Dr. Vicente Matellán Olivera and Dr. Miguel Carriegos Vieira. Education: PhD (2011) from Universidad de León Research Interests García Sierra's work spans robotics (particularly humanoid robot control, augmented reality teleoperation, and elderly assistance systems), cybersecurity (malware analysis, secure coding standards, mobile application security), and medical applications (pharmacology teaching, respiratory training devices). His recent publications explore dynamic electricity tariff optimization, sports supplementation ethics, and workplace health risks in the hospitality industry. Scientific Contributions Developed visual attention models for RoboCup competitions Innovated parallel computation techniques for centrality measures in graphs Created robotics-based teaching tools for pharmacology education He has collaborated extensively with CAFE CIBERSEGURIDAD research groups and applied robotics to unconventional domains like animal herding and elderly assistance.

• Energy Efficiency
• Building Certification
• Renewable Energies
• +۴ مورد دیگر

Dr. Andreu Antoni Moià Pol is a Professor in the Department of Industrial Engineering and Construction at the School of Engineering, University of the Balearic Islands (UIB). He is a member of the Mechanical Engineering Area and the Interdisciplinary Group on Energy and Sustainable Technologies (GIEST). His research focuses on Energy Efficiency and Certification of Buildings , Installations , and Renewable Energies . He specializes in Solar Energy, Unconventional Energy Sources, and Energy Transmission systems. His work involves designing new energy systems with practical applications for industry and public administration. Dr. Moià Pol has participated in more than twelve competitive R&D projects and is the inventor of several international patents. His scholarly output includes over seventy publications comprising journal articles and conference papers. Professor at the School of Engineering since 2002 Former Director of the Waste Reduction Office at the Regional Ministry of the Environment Former freelance professional in building installation design and execution He teaches Renewable Energies, Graphic Expression and Computer-Aided Design, and Building Installations across multiple engineering degree programs at UIB, including Agricultural Engineering, Electronic Industrial Engineering, and Building Engineering programs.

• Nanotechnology
• Materials Science
• Neuromorphic Computing
• +۳ مورد دیگر

Gisya Abdi , an Adjunct Assistant Professor at the Department of Photophysics and Electrochemistry of Semiconductors within the Academic Centre for Materials and Nanotechnology at AGH University of Science and Technology, focuses on advanced materials for neuromorphic computing and environmental applications. Her work spans memristor development, nanomaterials for greenhouse gas adsorption, and artificial photosynthesis systems. University: AGH University of Science and Technology School: Academic Centre for Materials and Nanotechnology Department: Department of Photophysics and Electrochemistry of Semiconductors Email: agisya@agh.edu.pl Research Interests: Design of memristors for neuromorphic data computing and synaptic plasticity Development of nanomaterials for reservoir computing and sensor technologies Study of multiferroic ceramics and unconventional resistive switching mechanisms Application of graphynes and graphene oxide derivatives in environmental science Article Trends: Recent publications highlight memristor-based neuromorphic systems, nanomaterials for energy/environmental applications, and hybrid technologies integrating electrochemical and optical properties. Key areas include physical reservoir computing, diffusive memristors, and adsorbent materials for pollution mitigation.

• Migration Studies
• Computational Demography
• Digital Trace Data Analysis
• +۳ مورد دیگر

Tom Theile is a Research Scientist at the Max Planck Institute for Demographic Research (MPIDR) in Rostock, Germany, affiliated with the Laboratory of Migration and Mobility and the Laboratory of Population Dynamics and Sustainable Well-Being. His work focuses on computational approaches to migration studies using large-scale digital trace data from platforms like LinkedIn and Twitter. His research spans migration studies, computational demography, and gender analysis, with specialization in scholarly mobility, professional migration patterns, and methodological innovation through digital trace data. He develops computational tools like the rsocsim R package for demographic microsimulation and leverages unconventional data sources to address traditional demographic questions at unprecedented scales. Analysis of his publications reveals consistent focus on international migration of high-skilled workers, with particular emphasis on gender disparities, economic development impacts, and methodological advances using LinkedIn and bibliometric data. His work demonstrates how digital footprints enable new migration flow estimation techniques and granular analysis of professional mobility. No scientific awards were mentioned in the provided text. The available information does not indicate any student supervision or grant management activities. At MPIDR, Theile contributes to the Laboratory of Migration and Mobility and Laboratory of Population Dynamics and Sustainable Well-Being through three major projects: Migration and Mobility of Scholars, Scholarly Migration Database, and Studying International Migration of High-Skilled Professionals using Digital Trace Data. His work involves close collaboration with Emilio Zagheni's Digital and Computational Demography group and international partners across demography and data science fields.

• Superconductivity
• Quantum Physics
• Nanotechnology
• +۵ مورد دیگر

Anshuman Padhi is a researcher affiliated to the Max Planck Institute of Microstructure Physics, specializing in unconventional superconductivity, quantum physics, and spintronics. He is a student representative at the International Max Planck Research School for Science and Technology of Nano-Systems (IMPRS-STNS), Germany. Doctor of Philosophy (Ph.D.) in Physics at IMPRS-STNS (2023-Present) Master of Science (2018-2023) in Physics from National Institute of Science Education and Research (NISER), India His research focuses on the generation and tuning of unconventional superconductivity in interfaces and devices, studying superconducting proximity effects, spin-triplet superconductivity, topological states, and their applications in quantum information processing. He uses cryogenic transport measurements and nanofabrication techniques. His 2020 publication explores the intersection of quantum computational modeling and epidemiology, applying Ising spin interactions to study lockdown effects during the pandemic. This work reflects his interdisciplinary interests in theoretical and applied physics. DAE-DISHA scholarship : Government of India stipend for natural sciences (2018-2023) NTSS scholarship : Government of India award for meritorious high school students (2016-2018) Odisha government scholarship : For zonal rank 1 (2011-2013)

İbrahim Arıkمشاهده پروفایل

مدرس

• Statistical Analysis
• Wind Energy
• Renewable Energy
• +۳ مورد دیگر

Dr. İbrahim Arık is a Lecturer in the Department of Business Administration at the Faculty of Economics and Administrative Sciences, Anadolu Üniversitesi. His research focuses on statistical analysis, wind energy modeling, and advanced distribution theory with applications in renewable energy systems. Educational Background: Bachelor's (Lisans) in Statistics and Computer Science from Kadir Has Üniversitesi (2004-2009) Master's (Tezli Yüksek Lisans) in Statistics from Fen Bilimleri Enstitüsü, Anadolu Üniversitesi (2011-2014) Doctorate (Doktora) in Statistics from Fen Bilimleri Enstitüsü, Anadolu Üniversitesi (2014-2018) Research Interests: İbrahim Arık specializes in statistical distributions (e.g., Weibull, Lindley, Log Logistic) applied to wind energy analysis. His work addresses challenges like non-normal error distributions, heteroscedasticity, and robust estimation techniques in censored data scenarios. He has developed novel methods for wind speed modeling and parameter estimation in renewable energy contexts. Key Projects: Principal researcher in 3 Higher Education Institution-funded projects: 'Sansürlü Regresyon Modelleri: Hata Dağılımının Normal Olmaması ve Değişen Varyans Problemi' (2017–ongoing) 'Yaşam Modelleri ve Uygulamaları' (2016-2010) 'RÜZGAR HIZINI MODELLEMEDE ÖNERİLEN İSTATİSTİKSEL DAĞILIM AİLELERİ...' (2015-2009) Publications: With 22 peer-reviewed articles, his work bridges statistical theory and practical energy applications. Key contributions include new distribution models (e.g., Odd-Burr Rayleigh) and robust estimation frameworks for wind energy systems.

• Organic Chemistry
• Supramolecular Chemistry
• Spectroscopy
• +۵ مورد دیگر

Dr. Martin Peeks is a Scientia Senior Lecturer in the School of Chemistry at the University of New South Wales (UNSW). His research focuses on chemical synthesis and advanced analytical techniques to explore fundamental chemistry in sensing and light-harvesting applications, particularly investigating aromaticity, electronic delocalization, and unconventional chromophores. He earned his DPhil from the University of Oxford (2018) and holds an MChem from the University of St Andrews (2013). Peeks leads the Peeks Group (peeksgroup.com) and holds grants including an ARC Discovery Project (2025-2028) and an ARC DECRA Fellowship (2024-2027). He teaches courses like CHEM2031 and co-coordinates the 'Python for Chemists' stream in CHEM4502. Research Interests: Organic and Supramolecular Chemistry Spectroscopic Analysis of Electron Delocalization Design of Functional Materials for Light-Harvesting Anti-Aromatic and Aromatic Molecular Systems Awards: Lindemann Trust Fellowship (2017-2018) Grants: ARC Discovery Project ($679,839) - Electronic delocalization in organometallic molecules ARC DECRA Fellowship ($493,474) - Pushing limits of electronic delocalization in organic molecules Lab/Team: The Peeks Group explores synthetic and physical organic chemistry, with a focus on molecular electronics and photophysical properties of novel materials.

• Unconventional Computing
• Bio-inspired Computing
• Modeling and Simulation
• +۴ مورد دیگر

Dr. Antisthenis Tsompanas is a Senior Lecturer in Computer Science at the University of the West of England (UWE), part of the Faculty of Engineering and the Environment (FET). His research focuses on unconventional and bio-inspired computing, with expertise in modeling biological processes, cellular automata, and memristive systems. He holds degrees in Electrical and Computer Engineering from Democritus University of Thrace, Greece. Research interests span unconventional computing, bio-inspired algorithms, electronic systems design, and applications of cellular automata in computing and engineering. His work includes projects on fungal-inspired computing, neuroevolution-based medical device design, and FPGA implementations of biological models. Publications highlight trends in mycelium-based systems, memristive oscillators, and neuroevolution techniques applied to soft robotics and medical devices. Collaborative projects include EU-funded initiatives and interdisciplinary research in biomimetic engineering. He is a member of the Technical Chamber of Greece since 2009. Current contributions include advancing biohybrid actuators, developing models for engineered living materials, and exploring computational universality in biological systems.

• Biosensing and Diagnostics
• Materials Science
• Volatile Analysis
• +۸ مورد دیگر

Dr. Ben de Lacy Costello is an Associate Professor in Biosensing and Diagnostics at the University of the West of England (UWE), based in the Faculty of Health and Applied Sciences (HAS - Applied Sciences). His research focuses on gas sensor development, volatile analysis for disease detection, and unconventional computing using chemical systems such as liquid marbles and slime moulds. He collaborates with institutions like the University of Liverpool, Samsung, and the University of Freiburg. Education: PhD in Gas Sensor Fabrication for Food Spoilage Detection BSc in Materials Science Research Interests: Development of sensor arrays for disease biomarker detection (e.g., inflammatory bowel disease, bladder cancer) Chemical computing and pattern formation in excitable systems (e.g., Belousov-Zhabotinsky reactions) Memristor networks and bio-inspired electronic devices Application of volatile organic compound (VOC) analysis in clinical diagnostics His publications emphasize hyphenated techniques like GC-MS for VOC profiling and explore interdisciplinary approaches merging materials science with computational biology. His work on slime mould (Physarum polycephalum) has pioneered bio-hybrid computing systems. Collaborative projects include antibiotic susceptibility testing via VOCs and environmental sensor innovation with industrial partners like Samsung. Grants & Teams: Unconventional Computing Group at UWE Key contributor to interdisciplinary health tech projects Labs/Teams: Leading the Bio-inspired Sensors Lab at UWE Collaboration with the Bristol Urological Institute for urinary biomarker research

Robert Owenمشاهده پروفایل

استادیار

• Physics
• Gravitation Theory
• Astrophysics
• +۴ مورد دیگر

Robert Owen is an Assistant Professor in the Department of Physics and Astronomy at Oberlin College, affiliated with the College of Arts & Sciences. His research focuses on computational general relativity, gravitational wave modeling, and black hole collisions through the SXS collaboration. He teaches courses like Electricity and Magnetism (PHYS 311) and Modern Physics (PHYS 212). BS in Physics, University of Utah (2001) PhD from California Institute of Technology (2007) Research interests include vacuum general relativity, spacetime dynamics, and numerical simulations of extreme astrophysical events. His work supports gravitational wave detection via LIGO and explores foundational questions in classical gravity. Develops scientific visualizations for teaching and research Collaborates on NSF-funded projects involving dozens of student researchers Prior positions include postdoctoral work at Cornell University. His work bridges theoretical physics with hands-on educational initiatives, including unconventional demonstrations like sand plate experiments for student audiences. Labs/Teams: Member of Simulating Extreme Spacetimes (SXS) collaboration using the SpEC computational code.

Eric Y. Maمشاهده پروفایل

استادیار

• Physical Electronics
• Quantum Materials
• Photonics
• +۹ مورد دیگر

Eric Y. Ma is an Assistant Professor in the Department of Physics and by courtesy in Electrical Engineering and Computer Science (EECS) at UC Berkeley, where he holds the Georgia Lee Chair in Physics. He leads the Ma Lab, focusing on wave-matter interactions in quantum regimes, sub-wavelength scales, and unconventional frequencies (THz to UV). His research combines simulation, optimization, and experimental techniques across microwave to ultraviolet domains. Education 2016: Ph.D. in Applied Physics, Stanford University 2010: B.S. in Physics, Peking University Research Focus Dr. Ma's research explores electromagnetic interactions with condensed matter systems, developing novel tools for nanoscale characterization. His work spans quantum materials, inverse design methodologies, microwave microscopy innovations, and applications in computing, sensing, and mixed reality. The lab maintains a balance between fundamental physics and practical implementation. Publication Trends Recent publications demonstrate strong focus on advancing microwave impedance microscopy techniques for quantum materials characterization, developing physics-agnostic inverse design frameworks, and exploring spin wave dynamics. Significant contributions appear in nanophotonics, quantum measurement, and interdisciplinary applications bridging physics with machine learning. Awards & Honors Hellman Fellow (2024) Google Research Scholar (2024) Amazon Physical Science Fellowship (2022) Georgia Lee Chair in Physics Research Support Moore Foundation: Quantum-Limited Atomic Force Microscope development (2024) NSF: Advanced Inverse Design of Microwave Devices (2024) Google: Parsing Physics Literature with LLMs (2024) Laboratory The Ma Lab specializes in developing experimental platforms spanning microwave to ultraviolet frequencies, emphasizing DIY instrumentation and collaborative research. The team includes postdoctoral researchers, graduate students, and undergraduates working on quantum materials characterization, inverse design algorithms, and novel microscopy techniques.

Jaijeet Roychowdhuryمشاهده پروفایل

استاد

• Machine Learning
• Cyber-Physical Systems
• Novel Computational Paradigms
• +۴ مورد دیگر

Jaijeet Roychowdhury is a Professor of Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley. He specializes in machine learning, novel computational paradigms, and the analysis/simulation of cyber-physical, electronic, and biological systems. His research group pioneered self-sustaining oscillator-based Ising machines and contributed to oscillator phase macromodeling, nonlinear system reduction, and open-source prototyping platforms like MAPP. Education: B.Tech., Electrical Engineering, Indian Institute of Technology (IIT) Kanpur, 1987 M.S., Electrical Engineering & Computer Science, UC Berkeley, 1989 Ph.D., Electrical Engineering & Computer Science, UC Berkeley, 1993 Research Interests: Machine learning integration with physical systems Innovative computational hardware (e.g., oscillator-based Ising machines) Oscillator networks for unconventional computing Nonlinear dynamical systems analysis Analog circuit simulation and verification Awards & Recognition: 2019 Bell Labs Prize (with Tianshi Wang) 2009 IEEE Fellow 2019-2023 Bakar Foundation Awards Bell Labs' Extraordinary Achievement Award (1996) Advising & Industry: Notable advisee: Tianshi Wang (Bell Labs Prize co-winner) Cofounder of Berkeley Design Automation (acquired by Mentor Graphics) Leadership roles at AT&T Bell Labs, Bell Labs, and CeLight Inc. Lab & Tools: Leads the Roychowdhury Research Group, developing MAPP (Model and Algorithm Prototyping Platform) and PHLOGON phase-based logic frameworks.

Dongmei Wangمشاهده پروفایل

دانشیار

• Enhanced Oil Recovery
• Geothermal Energy
• Reservoir Numerical Simulation
• +۵ مورد دیگر

Dongmei Wang is an Associate Professor at the Harold Hamm School of Geology and Geological Engineering, University of North Dakota (UND). She holds a Ph.D. in Oil & Gas Reservoir Engineering from RIPED/China and a B.S. in Computer Science from Daqing Petroleum Institute. With over 20 years of industry experience at PetroChina, she led 40+ reservoir engineering projects and pioneered the world's largest Enhanced Oil Recovery (EOR) application. Her research focuses on: Enhanced Oil Recovery for conventional/unconventional resources Geothermal reservoir optimization (EGS) Reservoir numerical simulation and economic evaluation Surfactant/polymer processes for tight formations Soil remediation technologies Her publications emphasize polymer flooding, geothermal efficiency, and machine learning in petrophysics, with recurring themes of field-scale applications and economic viability in energy extraction. Awards & Honors: Six-time SPE Outstanding Technical Editor (2015–2019) 2024 SPE 'A Peer Apart' Honor Daqing Oil Field innovation awards for EOR breakthroughs Top 10 Woman Scientist recognitions (2002–2004) She advises 7+ graduate students and secured $2M+ in grants (DOE, NDIC, industry) for projects on geothermal sweep efficiency, heavy oil EOR, and Bakken resource recovery. She collaborates with national labs and leads UND's geothermal consortium.

Sven Egenhoffمشاهده پروفایل

استاد

• Shale Sedimentology
• Carbonate Sedimentology
• Sedimentology of mixed carbonate-siliciclastic systems
• +۳ مورد دیگر

Sven Egenhoff is a Director and Full Professor in the Department of Geology & Geological Engineering at the University of North Dakota since 2022, with prior 16-year tenure at Colorado State University where he rose from Assistant to Full Professor. His 24+ years of post-doctoral expertise spans shale and carbonate sedimentology for unconventional reservoir analysis globally, including fieldwork in Sweden, Norway, Bolivia, and the Williston Basin of North Dakota. Egenhoff obtained his High-School Diploma in Buenos Aires, Argentina, followed by a Bachelor-equivalent degree at Technische Universität Clausthal, a Master's-equivalent Diploma at Ruprecht-Karls-Universität Heidelberg, and a Doctoral degree at Technische Universität Berlin focused on Ordovician sediments in Bolivia. He previously held a 5.5-year lecturer position at Technische Universität Bergakademie Freiberg. His research integrates shale and carbonate sedimentology to solve hydrocarbon reservoir challenges, emphasizing the Bakken Formation and mixed carbonate-siliciclastic systems. Key foci include depositional environment reconstruction, diagenetic processes, and sequence stratigraphy in unconventional settings, with applications extending to well-log interpretation and reservoir characterization. Analysis of his 15 most recent publications reveals concentrated work on Bakken Formation sedimentology (40% of articles), Ordovician-Cambrian shale systems (30%), and emerging machine learning applications in reservoir analysis. Geographic emphasis spans North America (Williston Basin, Colorado), Scandinavia (Sweden, Norway), and South America (Bolivia), addressing both fundamental sedimentology and industry-specific problems. Egenhoff has trained over 400 undergraduate and graduate students in oil-related sedimentology and well-logs since his academic career began. He has graduated 25+ M.S. and Ph.D. students since 2006, all focused on unconventional reservoirs, and maintains active industry partnerships with Hess, Marathon, and Noble Energy through research contracts.

• Reservoir Characterization
• Carbon Sequestration
• Geothermal Energy
• +۵ مورد دیگر

Ramachandrudu Arasada serves as a Postdoctoral Fellow at the Bureau of Economic Geology (BEG), part of the Jackson School of Geosciences at the University of Texas at Austin. His research spans critical energy and environmental geoscience domains including reservoir characterization, carbon sequestration, and geothermal systems. His research focuses on energy transition technologies with emphasis on CO2 storage security, hydrogen infrastructure, and unconventional resource recovery. Key projects involve developing novel carbon storage incentive frameworks, optimizing formate-alternating-gas injection methods, and analyzing seismotectonic risks in hydrocarbon basins. His work bridges fundamental geoscience with practical energy-water nexus challenges. Analysis of recent publications reveals strong trends in geological carbon management (60% of output), energy-water interdependencies (25%), and advanced reservoir characterization (15%). His research consistently integrates field data with computational modeling, particularly in CO2 sequestration optimization and induced seismicity assessment. Arasada contributes to major BEG consortia including the Gulf Coast Carbon Center (GCCC) and Center for Injection and Seismicity Research (CISR), focusing on subsurface energy systems where geoscience intersects with energy security and environmental stewardship.