جست‌وجوی استاد و پژوهشگر

Antonis Stylianouمشاهده پروفایل

دانشیار

• Computational Biomechanics
• Musculoskeletal Modeling
• Multibody Dynamics
• +۳ مورد دیگر

Antonis Stylianou is an Associate Professor in the Department of Mechanical Engineering at the University of Missouri - Kansas City (UMKC). He holds a Ph.D. in Mechanical Engineering from the University of Kansas (2004), along with multiple master's degrees in Mathematics (2012) and Mechanical Engineering (2000), and a B.S. in Mechanical Engineering (1998). His primary affiliation is within the School of Science and Engineering, where he focuses on computational biomechanics, musculoskeletal modeling, and multibody dynamics. Dr. Stylianou's research emphasizes Elbow joint mechanics and ligament deficiency modeling Virtual surgical simulators for pelvic surgery error prevention Pediatric knee anatomy and ACL injury risk analysis Musculoskeletal models of human motion Finite element analysis of cartilage contact pressures His work bridges computational methods with clinical applications, including developing tools for orthopedic surgeons and training paradigms for surgical techniques. Recent studies have explored surgeon kinematics during retropubic trocar insertion and posteromedial rotatory incongruity of the elbow. Teaching responsibilities include advanced dynamics, biomechanics, and experimental methods courses. His contributions underscore the integration of engineering principles with medical challenges, particularly in orthopedic and surgical contexts.

• Planetary Science
• Atmospheric Physics
• Astrobiology
• +۷ مورد دیگر

Professor Javier Martin-Torres is a Personal Chair in the School of Geosciences at the University of Aberdeen, where he leads research in planetary science, atmospheric physics, and astrobiology. His work focuses on the study of planetary atmospheres, particularly Mars and the Moon, using remote sensing data, modeling, and space instrumentation. University: University of Aberdeen School: School of Geosciences Rank: Professor Email: javier.martin-torres@abdn.ac.uk His research interests include planetary atmospheres, non-LTE modeling, Mars exploration, lunar subsurface studies, astrobiology, and planetary protection. He has made significant contributions to understanding atmospheric chemistry and energy balance in planetary environments, especially through data from missions such as MIPAS, SABER, Chang’E-4, and Mars Science Laboratory. The most recent publications reflect a strong trend in interdisciplinary planetary science, combining remote sensing, geochemistry, machine learning, and mission design. Key themes include Mars surface and atmospheric processes, lunar subsurface structure, life detection technologies, and the development of cleanroom and sampling systems for space missions. His work bridges observational data with theoretical modeling to advance our understanding of planetary environments. Scientific Awards: Fellow of the Royal Society of Edinburgh Fellow of the Royal Astronomical Society Professor Martin-Torres has been involved in advising and leading research projects related to planetary exploration and instrumentation. He has contributed to major collaborative grants, particularly in the areas of Mars rover missions, lunar science, and planetary protection. His work often involves international consortia and space agencies, indicating significant grant funding and project leadership. He is actively involved in laboratory and team-based research, including the development of planetary instrumentation, cleanroom facilities, and data analysis pipelines for radar and atmospheric sensors. His team works on integrating machine learning with planetary data interpretation and advancing technologies for future space missions.

Bige Unluturkمشاهده پروفایل

استادیار

• Wireless Communication and Networking
• Molecular Communications
• Internet of Bio-NanoThings
• +۳ مورد دیگر

Bige Unluturk is an Assistant Professor in the Departments of Electrical and Computer Engineering and Biomedical Engineering at Michigan State University (MSU), with an affiliation at the Institute for Quantitative Health Science & Engineering. She holds a Ph.D. from Georgia Institute of Technology (2020), M.Sc. from Koç University (2013), and B.Sc. from Middle East Technical University (2011). Her research focuses on molecular communication, the Internet of Bio-NanoThings, and their applications in healthcare, including projects like the ARPA-E-funded 'Strong and CO2-Consuming Living Wood' initiative. Education: Ph.D., Electrical & Computer Engineering, Georgia Tech (2020) M.Sc., Electrical & Computer Engineering, Koç University (2013) B.Sc., Electrical & Electronics Engineering, METU (2011) Research Interests: Biologically inspired communication systems Molecular communication networks in biological systems Healthcare applications of bio-nano sensors Wireless communication protocols for biomedical devices Awards: Recipient of NSF Student Travel Grants, Georgia Tech’s Researcher of the Year Award, and Outstanding Graduate Teaching Awards. She has also been recognized as a METU valedictorian and TUBITAK Fellow. Labs & Collaborations: Leads the Unluturk Lab at MSU, collaborating with Purdue University on bio-engineered materials. Previously worked as a postdoc in Dr. Chris Contag’s Lab at IQ and conducted research at Aalto University and the University of Oslo.

Seyhan Onbaşıoğluمشاهده پروفایل

استاد

• Heat Transfer
• Two-Phase Flow
• Numerical Modeling
• +۳ مورد دیگر

Seyhan Onbaşıoğlu is a Professor in the Department of Mechanical Engineering at Istanbul Technical University (ITU), actively engaged in thermal engineering research with current projects extending to 2025. Affiliated with ITU's Ayazağa Campus in Istanbul, Turkey, the profile shows ongoing research leadership including principal investigator roles in multiple national projects. Research interests center on heat transfer enhancement, two-phase flow phenomena, and thermal system optimization, with fingerprint analysis indicating strong expertise in heat transfer (100%), flow distribution (94%), and experimental investigation (83%). Key focus areas include nucleate boiling, ice sublimation dynamics, and energy-efficient appliance design. Publication trends since 2016 emphasize experimental validation of thermal systems, with significant contributions to refrigeration technology, domestic appliance efficiency, and microchannel heat transfer. Recent works (2023-2025) increasingly integrate numerical modeling with experimental verification, particularly in suction muffler design and ice sublimation under humidity effects. h-index: 12 Total Citations: 129 (Scopus) Research Outputs: 27 publications Active Projects: 1 (2025) Completed Projects: 6 (2012-2022) As principal investigator, leads projects funded by TUBITAK, SRP, and TTO including refrigerator system development, steam generation technology, and ship diesel engine turbocharger design. Supervised 53 research works to date across thermal engineering applications. Current projects focus on refrigerator cooling system enhancement (2025) and ejector-integrated refrigeration design (2022).

Javier Cabreraمشاهده پروفایل

استاد

• Biostatistics
• Data Mining
• Clinical Trial Methodology
• +۵ مورد دیگر

Javier Cabrera is a Professor in the Department of Statistics at Rutgers University with a joint affiliation at the Cardiovascular Institute. He holds a Ph.D. from Princeton University and is recognized as a Fulbright Scholar. His office is located at Hill Center 471, 110 Frelinghuysen Road, Piscataway, NJ. His research focuses on: Biostatistics and clinical trial methodology Data mining for functional genomics and DNA/protein arrays Statistical computing, machine vision, and high-dimensional data analysis Cardiovascular health applications using statistical modeling Recent publications (2022-2025) demonstrate strong emphasis on: Novel statistical methods for medical/biological data Machine learning applications in diagnostics and genomics Clinical risk modeling and epidemiological studies Big data reduction techniques and computational efficiency He frequently publishes in interdisciplinary collaborations at the intersection of statistics, biomedicine, and computational science. Awards: Fulbright Scholar He collaborates extensively with the Cardiovascular Institute, contributing statistical expertise to research on cardiovascular outcomes, disease risk modeling, and clinical data analysis.

• Ecohydrology
• Terrestrial Carbon Cycle
• Machine Learning Applications in Ecology
• +۵ مورد دیگر

Jacob A. Nelson serves as Project Group Leader for the Cross-Scale Terrestrial Ecophysiology (XTE) group within the Biogeochemical Integration Department at the Max Planck Institute for Biogeochemistry in Jena, Germany. His research bridges ground-based ecosystem measurements with global carbon, water, and energy cycle analysis through knowledge-guided data-driven methodologies. The XTE group focuses on synthesizing ecophysiological understanding from direct measurements while developing advanced models for global flux estimation. Nelson's research centers on ecohydrological processes, particularly plant water use and its interaction with carbon cycles. His work employs machine learning approaches guided by physiological understanding to estimate transpiration across diverse ecosystems. Current research priorities include advancing the FLUXCOM framework for global data-driven estimates of terrestrial carbon, energy, and water fluxes, with significant contributions to the X-BASE product development. His methodological innovations address critical challenges in eddy covariance measurements, energy balance closure, and evapotranspiration partitioning. Analysis of Nelson's 15 most recent publications reveals strong emphasis on resolving measurement limitations in ecosystem flux quantification while developing next-generation scaling frameworks. His work consistently integrates machine learning with biophysical understanding to improve terrestrial flux estimates, with particular focus on evapotranspiration dynamics, carbon-water interactions, and addressing energy imbalance issues in flux tower data. The research spans from vineyard-scale applications to global FLUXCOM-X products. Nelson actively supervises a research team including doctoral researchers Deep Prakash Sarkar, Xiuzhi Chen, Sinikka Jasmin Paulus, Laura Nadolski, Yucong Hu, Luca Tuzzi, and Kai-Hendrik Cohrs, along with bachelor student Jakob Lambert-Hartmann. He recently supervised Weijie Zhang through successful PhD defense at Ghent University. Current projects include EO-LINCS for terrestrial carbon cycle assessment and FLUXCOM for upscaling biosphere-atmosphere fluxes from FLUXNET sites to global scales.

Jane Cleland-Huangمشاهده پروفایل

استاد

• Cyber-Physical Systems
• Software Traceability
• Safety Assurance
• +۳ مورد دیگر

Jane Cleland-Huang serves as the Frank M. Freimann Professor of Computer Science and Department Chair of the Department of Computer Science and Engineering within the College of Engineering at the University of Notre Dame. Her leadership spans academic administration and pioneering research in safety-critical cyber-physical systems. Her educational foundation includes a Ph.D. from the University of Illinois-Chicago (2002), establishing her expertise in software engineering and systems safety. This background directly informs her current research trajectory. Research interests center on Safety Assurance for Cyber-Physical Systems , with specialized focus on software traceability , safety case evolution , and runtime monitoring of non-functional requirements . Her work uniquely bridges theoretical requirements engineering with real-world emergency response applications, particularly through drone technology. Key methodologies include human-on-the-loop systems design , adaptive autonomy frameworks , and value-sensitive engineering to ensure systems align with societal and regulatory contexts. Analysis of her 2023-2025 publications reveals strong thematic concentration on sUAS safety assurance , with 78% of articles addressing drone-specific challenges. Dominant subfields include runtime monitoring (28%), safety case automation (22%), and multi-UAV coordination (19%). Her work increasingly integrates reinforcement learning for environmental adaptation and human-value alignment in autonomous systems , reflecting evolving priorities in trustworthy AI deployment. As principal investigator of the DroneResponse project, she directs significant grant-funded research in collaboration with the South Bend Fire Department. This partnership exemplifies her commitment to co-design methodologies where end-users actively shape system development. Current grants focus on Smart and Connected Communities (NSF SCC program) with emphasis on emergency response drone integration. The DroneResponse laboratory operates as an interdisciplinary hub within Notre Dame's Computer Science department, combining expertise in software engineering, computer vision, and human factors. Her team maintains close operational ties with first responders to ensure research directly addresses field challenges in search-and-rescue operations and disaster management.

Tobias Windischمشاهده پروفایل

استاد

• Machine Learning
• Computer Vision
• Reinforcement Learning
• +۴ مورد دیگر

Prof. Dr. Tobias Windisch is a Professor at the University of Applied Sciences Kempten, where he serves as head of the Institute for Machine Vision within the Faculty of Mechanical Engineering. He leads the Optical 3D Measurement and Computer Vision Laboratory (3D visionlab) and oversees research activities focused on machine learning applications for industrial automation. Dr. Windisch received his PhD in mathematics from OvGU Magdeburg under the supervision of Thomas Kahle, and holds an Honors Master's degree in mathematics from TU Munich within the elite TopMath program. Prior to his academic career, he worked on machine learning projects for Robert Bosch GmbH and Daimler TSS GmbH (now Mercedes-Benz Tech Innovation). His research spans machine learning, computer vision, and optical sensing with a strong focus on industrial applications. Windisch's work primarily explores how reinforcement learning can be combined with optical sensing to develop intelligent control strategies for manufacturing processes. His team develops mechanical processes built around machine learning models to further automate industrial applications using data from optical sensors. The research has practical applications in automotive production, quality control, and precision manufacturing. Analysis of his recent publications reveals a strong trend toward practical implementations of machine learning in industrial settings, with particular emphasis on reinforcement learning for process optimization, drift detection in high-dimensional data, and causal structure learning for manufacturing analytics. His work bridges theoretical machine learning with real-world industrial challenges. As a dedicated educator and research leader, Windisch maintains high standards for academic integrity and excellence. He believes in creating an environment where students can focus deeply, think boldly, and innovate through meaningful research. Dr. Windisch leads a dynamic research group with numerous Master's and Bachelor's students working on cutting-edge projects including reinforcement learning for active alignment, drift detection in sensory data, latent drift detection with Autoencoders, and representation learning for industrial processes. His laboratory, the 3D visionlab, serves as the physical hub for this research. The Institute for Machine Vision under his leadership develops practical tools and frameworks such as relign, lineflow, and driftbench that are openly available on GitHub, demonstrating his commitment to reproducible research and practical applications.

Jason F Luckمشاهده پروفایل

استادیار

• Biomedical Engineering
• Impact Biomechanics
• Cervical Spine
• +۷ مورد دیگر

Jason F. Luck is an Assistant Research Professor in the Department of Biomedical Engineering at Duke University and a Faculty Network Member of the Duke Institute for Brain Sciences. His research focuses on impact biomechanics, traumatic brain injury, and spinal injury mechanisms. Ph.D., Duke University (2012) Dr. Luck's work investigates biomechanical responses to head and neck trauma, particularly in sports and vehicular contexts. Key areas include: Instrumented Mouthguard Validation: Assessing accuracy in measuring head kinematics during combat sports impacts. Pediatric Spinal Biomechanics: Analyzing cervical spine dynamics and failure properties in children. Trauma Epidemiology: Identifying mortality predictors in global traumatic brain injury cases. His recent publications emphasize sensor technology validation, sports-related concussion, and spinal injury thresholds. Dr. Luck collaborates with multidisciplinary teams on helmet design and impact mitigation strategies. Dr. Luck's laboratory (Hudson Hall Annex, Durham, NC) conducts experimental injury biomechanics using cadaveric and computational models.

Donatella Spanoمشاهده پروفایل

استاد

• Agrometeorology
• Biometeorology
• Ecophysiology of agricultural and forestry ecosystems
• +۵ مورد دیگر

Donatella Spano is Full Professor and Scientific Coordinator of the PhD programme in Agrometeorology and Ecophysiology of Agricultural and Forestry Ecosystems at the University of Sassari, Italy. She also coordinates the Agrometeorology and Ecophysiology Laboratory at the same university and serves as Senior Member of the Strategic Council of the Euro-Mediterranean Centre on Climate Change (CMCC). A founding member and former President (2015–2016) of the Italian Society for Climate Sciences, Prof. Spano has held numerous high-profile roles including Regional Minister for the Environment of Sardinia (2014–2019) and Pro-Rector for Research at the University of Sassari (2009–2014). Education Degree in Agricultural Sciences, University of Sassari Three-year Post-Doctoral specialisation in Biometeorology, University of Sassari Research Focus Prof. Spano’s work lies at the intersection of agrometeorology, biometeorology, and ecophysiology . Her team investigates the energy and mass exchange between terrestrial ecosystems and the atmosphere using advanced micrometeorological techniques such as Surface Renewal. She pioneered temperature-based phenological models to quantify chilling requirements and degree-day accumulation. Current research lines include climate-change impacts on crop yields (coffee, olives, maize), fire-behaviour modelling (danger indices and propagation), and the development of integrated systems for quantifying net CO₂ exchanges at urban and territorial scales. Across her recent publications, two dominant themes emerge: (1) climate-change projections and their sectoral impacts , where process-based and ensemble models are used to evaluate water demand, yield trends, and fire risk under future climates, and (2) micro-to-macro scale biometeorological observations , combining eddy-covariance data, phenological monitoring, and sensor-network optimisation to refine predictive models. Scientific Awards & Recognition Medal of the University of Sassari for best scientific production (2012) Best Practice Paper Award, American Society of Civil Engineers (2001, co-recipient) Advising & Grants Prof. Spano has chaired more than 40 doctoral and master theses. She is responsible for the scientific cooperation agreement with the University of California, Davis, a collaboration active since 1993. She leads or participates in numerous EU-funded projects focused on climate-change adaptation, sustainable farming strategies, and integrated fire-risk management systems. Laboratory & Team Leadership Since 2006 she has directed the Agrometeorology and Ecophysiology Laboratory at the University of Sassari, managing a team of 25 researchers, post-docs, and PhD students in cutting-edge experimental and modelling activities.

• Ultra-Low Power Analog/Mixed-Signal Circuits
• Biomedical Wearable/Implantable Devices
• Artificial Intelligence of Things (AIoT)
• +۵ مورد دیگر

Dr. Huan Hu is an Assistant Professor at the School of Microelectronics, Southern University of Science and Technology (SUSTech), Shenzhen, China. He holds a Ph.D. from Washington State University (2021) and has worked in industry at Skyworks Solutions and Biotronik/MSEI on low-power circuits for IoT and biomedical applications. Education: Ph.D., Washington State University, 2021 M.S., Oregon State University, 2015 B.S., University of Electronic Science and Technology of China, 2013 His research focuses on ultra-low power analog/mixed-signal integrated circuits for biomedical wearable/implantable devices and artificial intelligence of things, including applications in sensor interfaces, energy-efficient radios, and in-memory computing architectures. Recent publications highlight advancements in time-domain processing , biofuel cell integration , and injection-locked transmitters for IoT and biomedical applications, with awards including Shenzhen Overseas High-level Talent (2022) and IEEE RFIC Best Student Paper Award Nomination (2020). Scientific Awards: Shenzhen Overseas High-level Talent (Class C), 2022 RFIC Best Student Paper Award Nomination, 2020 Alaska Airline Travel Award, 2018 WSU Grand Challenges Fellowship, 2016-2017 OSU Laurels Scholarship, 2014-2015 He seeks motivated researchers for Research Assistant Professor , Postdoctoral Fellow , and Graduate Student positions in his group. Visit his lab page for details.

• 3D printing
• Materials science
• Electromagnetic compatibility testing
• +۶ مورد دیگر

Pererik Andreasson is a Lecturer at the Academy of Information Technology , Halmstad University. His research focuses on 3D printing, materials science, electromagnetic compatibility testing, and wireless communication. Key contributions include optimizing 3D-printed radar lenses, advancing phase-change material characterization via femtosecond x-ray diffraction, pioneering augmented reality methods for electromagnetic field visualization, and developing substrate integrated waveguide antennas for IoT devices. 3D printing of optical components Dynamic processes in phase-change materials Augmented reality for electromagnetic testing IoT antenna design His recent work on frequency-adjustable SIW antennas (2024) and AR-based EMC visualization (2021) demonstrates cross-disciplinary innovation. While no scientific awards are documented, his 15+ publications since 2007 highlight sustained expertise in material science and wireless technologies.

Jonathan W. Naughtonمشاهده پروفایل

استاد

• Experimental Fluid Dynamics
• Aerodynamics
• Turbulent Flow Characterization
• +۶ مورد دیگر

Jonathan W. Naughton is a Professor in the Department of Mechanical Engineering at the University of Wyoming. His research focuses on experimental fluid dynamics, aerodynamics, and turbulence characterization, with applications in wind energy and advanced instrumentation. He has contributed extensively to the understanding of wall shear stress measurement techniques and turbulent flow control. Research interests include: Experimental fluid dynamics and aerodynamics Turbulent flow characterization and control Instrumentation development for aerodynamic flows Wind energy systems, atmospheric inflow modeling, and blade aerodynamics His publications highlight expertise in swirling jets, shear stress sensors, and supersonic flowfield measurements. Key trends in his work span computational fluid dynamics, turbulent mixing enhancement, and aerospace instrumentation. Teaching responsibilities include undergraduate and graduate courses in fluid dynamics, thermodynamics, and turbulence.

Chuanmin Huمشاهده پروفایل

استاد

• Ocean Optics
• Optical Remote Sensing
• Harmful Algal Blooms
• +۳ مورد دیگر

Chuanmin Hu is a Professor at the University of South Florida College of Marine Science , leading the Optical Oceanography Laboratory . His work integrates in situ optical measurements with satellite remote sensing to study coastal ocean dynamics, harmful algal blooms, and climate impacts on water quality. Education: Ph.D. in Physics (University of Miami, 1997) Research Focus: Ocean optics, remote sensing algorithms, algal blooms, carbon cycling, and coastal observing systems Leadership: Director of the Optical Oceanography Lab and developer of systems like Sargassum Watch System and Integrated Red tide Information System His lab utilizes autonomous underwater vehicles (AUVs) and high-resolution satellite data to map bio-optical properties in coastal zones, coral reefs, and estuaries. Recent innovations include the Virtual Buoy System for real-time water quality monitoring. Scientific Awards: 2024 Pecora Group Award (USGS-NASA) Dr. Hu's work bridges optical oceanography with practical coastal management solutions, addressing challenges like the Tampa Bay Piney Point effluent plume and Sargassum inundation forecasting . His group has produced over 100 peer-reviewed publications and developed multiple satellite-based monitoring platforms.

• Additive Manufacturing
• Laser Metal Deposition
• Process Monitoring
• +۳ مورد دیگر

Marco Mazzarisi serves as an Assistant Professor in the Department of Mechanics, Mathematics and Management at the Polytechnic University of Bari, Italy, specializing in Manufacturing Technology and Systems (ING-IND/16 classification). Based at Via Orabona 4, 70125 Bari, he can be contacted via marco.mazzarisi@poliba.it or the departmental line +39 080 596 3522. His research centers on laser-based additive manufacturing processes, with primary expertise in Laser Metal Deposition (LMD) and Directed Energy Deposition. Key investigation areas include real-time process monitoring using coaxial infrared systems and off-axis optical techniques, defect detection (particularly subsurface voids), melt pool dynamics analysis, and sustainability assessment through exergetic analysis. His work focuses on nickel-based superalloys (Inconel 718) and stainless steels (AISI 316L), addressing critical challenges in geometric accuracy, energy consumption, and material compatibility in hybrid manufacturing. Analysis of his 2020-2025 publications reveals consistent innovation in LMD monitoring methodologies. His research demonstrates strong interdisciplinary integration between thermal physics, optical engineering, and sustainable manufacturing principles. Notable contributions include the development of off-axis monitoring frameworks, causal models for void prediction, and exergy-based sustainability metrics that bridge process quality with environmental impact assessment. Scientific awards: No awards, fellowships, or medals are documented in the provided materials. Advising and grants: No information regarding graduate student supervision, research grants, or funding sources is provided in the source text. Laboratory facilities: The text does not specify any dedicated laboratories, research teams, or collaborative groups associated with Dr. Mazzarisi's work.