جست‌وجوی استاد و پژوهشگر

Valery E. Forbesمشاهده پروفایل

استاد

• Population modeling
• Aquatic ecology
• Ecotoxicology
• +۷ مورد دیگر

Valery E. Forbes serves as Professor and Dean of the Department of Biological Sciences within Florida Atlantic University's Charles E. Schmidt College of Science. Her research bridges ecological modeling, ecotoxicology, and conservation biology with significant contributions to regulatory risk assessment frameworks. She maintains active collaborations with industry partners (Syngenta Crop Protection), government agencies (EPA), and academic institutions across North America and Europe. Ph.D. in Coastal Oceanography, State University of New York at Stony Brook M.S. in Marine Environmental Science, State University of New York at Stony Brook B.A. in Biology and Geology, State University of New York at Binghamton Forbes' research centers on developing mechanistic models that link molecular/cellular toxicant effects to population-level consequences. She pioneers traits-based approaches for endangered species risk assessment, particularly focusing on freshwater mussels' complex life cycles and ecosystem services. Her current NSF-funded project investigates epigenetic pathways to homeostatic resilience across mammalian species using comparative computational frameworks. She leads the development of standardized tools like the Pop-CMD web application for ecological risk assessment modeling. Her publication record (2020-2024) demonstrates consistent leadership in advancing population modeling for ecological risk assessment, with emphasis on conceptual model standardization, endangered species protection, and climate change interactions. Key thematic areas include freshwater mussel conservation, pesticide risk frameworks, and epigenetic mechanisms of environmental stress response. Forbes advises multiple postdoctoral researchers including Ines Haberle (freshwater mussel modeling), Jorge Gonzalez (epigenetic computational modeling), and Kristin Crouse (agent-based modeling of homeostasis). Her lab secures significant external funding including NSF grants and industry partnerships with Syngenta, focusing on regulatory science applications and endangered species recovery planning. Current research initiatives include developing traits-based surrogates for listed mussel species, creating standardized population modeling workflows via Pop-CMD, and leading a multi-institutional NSF project on epigenetic regulation of homeostatic resilience across diverse mammals. Her work directly informs EPA and FIFRA/ESA regulatory processes through mechanistic modeling approaches.

Jayesh Shanthi Bhavanمشاهده پروفایل

مدرس

• Material Science
• Electronic Materials
• Corrosion Studies
• +۳ مورد دیگر

Jayesh Shanthi Bhavan is a Lecturer in Engineering Design at the CEES School of Engineering, specializing in material science and mechanical engineering. His research focuses on lead-free solder alloys, corrosion studies, composite materials, and sustainable materials development. He holds a Doctorate in Material Science from An Experimental Investigation on Design, Characterization, and Analysis of Two Novel Lead-Free Solder Alloys (2020), an MEng in Product Design (2014), and a Mechanical Engineering degree (2010). His research interests include advanced material characterization techniques (e.g., EBSD, neutron scattering), phase transformation analysis in solders, and applications in automotive and aerospace sectors. He leads the project Bridging the Gap: Developing an Employable Skilled Workforce in Material Characterisation, Testing and Analysis (2024–2025), aimed at enhancing workforce capabilities in material science. Key contributions include advancements in graphene-reinforced solder composites, stress corrosion cracking analysis, and sustainable material recovery from electronic waste. His work aligns with UN Sustainable Development Goals related to sustainable industrialization and innovation (Goal 9) and responsible consumption (Goal 12). Awards: Best Doctoral Thesis in Engineering and Technology (Mechanical Engineering, Kerala, 2023). Peer Review: Active reviewer for Springer, Springer India, and Hindawi Limited.

• Underground Gas Storage
• Subsurface Engineering
• Numerical Simulation
• +۵ مورد دیگر

Dr. Gang Wang is an Assistant Professor in the Institute for GeoEnergy Engineering at Heriot-Watt University, serving as Theme Lead for Underground Hydrogen Storage at the Net-Zero Global Research Institute (iNetZ+). He holds a PhD in CCUS and MSc in Reservoir Evaluation from Heriot-Watt, with prior experience as a Leverhulme Early Career Fellow and Reservoir Engineer at CNPC. His research focuses on numerical simulation of subsurface gas systems (H₂, CH₄, CO₂), addressing multiscale multiphysics processes. He collaborates with European/UK industries to develop field-scale hydrogen storage solutions. Key expertise includes reservoir engineering, geochemical interactions, and bio-geochemical modeling for reservoir selection. Notable contributions include studies on microbial activity impacts, cushion gas design for hydrogen storage, and CO₂-WAG displacement mechanisms. He serves on EAGE committees and delivers short courses on hydrogen storage reservoir engineering. Education: PhD in Carbon Capture and Storage (CCUS), Heriot-Watt University MSc in Reservoir Evaluation and Management, Heriot-Watt University Awards: Leverhulme Early Career Fellowship Dr. Wang has pioneered reservoir engineering strategies comparing hydrogen storage with CCS/natural gas systems, emphasizing heterogeneous reservoir effects and microbial-geochemical interactions. His datasets on compositional simulations are publicly available, advancing industry partnerships for net-zero energy transition solutions.

• Artificial Intelligence
• Natural Language Processing
• Information Retrieval
• +۵ مورد دیگر

Xin Zhao is a prominent professor at Renmin University of China's School of Information, Department of Computer Science, with an extensive publication record spanning from 1997 to 2026. His research demonstrates significant contributions across multiple disciplines including artificial intelligence, natural language processing, computer vision, and interdisciplinary applications in ecology, medicine, and business. Dr. Zhao's research interests are remarkably diverse, focusing primarily on artificial intelligence and its applications. His work spans natural language processing, large language models, information retrieval, machine learning, and computer vision. Recent publications reveal a strong emphasis on practical AI applications in healthcare (dental implant failure prediction), environmental science (kelp bed dynamics), finance (green finance impact), and industrial systems (composite curing process monitoring). His research often combines theoretical advancements with real-world problem solving, demonstrating both academic rigor and practical relevance. Analysis of his recent publications (2024-2026) shows a clear trend toward interdisciplinary AI applications, with increasing focus on multimodal learning, robustness in dynamic environments, and practical implementations across various sectors. His work bridges theoretical computer science with domain-specific challenges in medicine, ecology, finance, and industrial engineering. The publications demonstrate sophisticated methodological approaches including deep learning architectures, mathematical modeling, and novel algorithmic solutions to complex problems. Dr. Zhao has made significant contributions to the academic community through numerous publications in high-impact journals and conferences including IEEE Transactions, ACL, AAAI, and CVPR. His collaborative work spans international boundaries, with co-authors from institutions worldwide, indicating strong research networks and interdisciplinary collaborations. His research group appears to be actively engaged in cutting-edge AI research, with particular strengths in large language models, multimodal learning, and practical AI applications. The group's work on projects like C-3PO (Compact Plug-and-Play Proxy Optimization) and RMoA (Optimizing Mixture-of-Agents) demonstrates leadership in emerging AI methodologies. Current research directions include enhancing LLM capabilities, improving multimodal understanding, and developing robust AI systems for real-world applications across diverse domains.

• Maritime Archaeology
• Underwater Photogrammetry
• Digital Heritage
• +۴ مورد دیگر

Felix Pedrotti is a Senior Research Fellow at the University of Southampton, affiliated with the Centre for Maritime Archaeology and the Southampton Marine and Maritime Institute (SMMI). His interdisciplinary work bridges maritime archaeology, digital heritage preservation, and ocean literacy initiatives through technological innovation. Dr. Pedrotti holds BA and MA degrees that provided foundational expertise in translating classical documents, which informs his archaeological interpretations. His academic journey uniquely combines humanities training with technical specialization in geospatial analysis. His research program focuses on: Advanced underwater photogrammetry and robotic survey techniques Integration of terrestrial LiDAR with underwater bathymetric datasets Virtual reality applications for archaeological visualization and public engagement Riverine geomorphology reconstruction and ancient waterway communities Developing ocean literacy through immersive archaeological experiences Recent publications (2018-2019) reveal consistent methodological innovation in Black Sea archaeology, featuring robotic documentation of deep-sea sites, 4D modeling of submerged excavations, and interdisciplinary studies of Bulgarian river deltas. These works demonstrate his signature approach of merging photogrammetry with geophysical data to reconstruct ancient human-environment interactions. Dr. Pedrotti has secured research funding through mechanisms like HEIF (Higher Education Innovation Fund), completing projects including 'Tales of Discovery' and 'HEIF 2024/25 Lines of Discovery'. His teaching portfolio spans scientific diving instruction at multiple international institutions and technical workshops on photogrammetry, reflecting active knowledge transfer to next-generation researchers. Within SMMI's collaborative ecosystem, he contributes to interdisciplinary teams that integrate archaeological expertise with marine science and digital technology. His development of VR experiences (e.g., youtu.be/fMlR71Sv3Ec) exemplifies his commitment to translating complex archaeological data into accessible public narratives that advance ocean literacy.

Ryan Weaverمشاهده پروفایل

استادیار

• Mitochondrial Physiology
• Evolutionary Biology
• Bioenergetics
• +۳ مورد دیگر

Ryan Weaver is an Assistant Professor in the Department of Ecology and Evolutionary Biology at Iowa State University, leading the Evolutionary Bioenergetics Lab. His research investigates how organisms meet bioenergetic demands under environmental and physiological stressors, focusing on mitochondrial physiology, mitonuclear coevolution, and carotenoid metabolism. Study systems include fungal pathogens, copepods, snails, and bumblebees. Education includes a B.S. in Environmental Studies from Virginia Commonwealth University (2013) and a Ph.D. in Biology from Auburn University (2018). His work integrates experimental and bioinformatic methods to explore evolutionary dynamics of energy production systems and signal honesty in animal coloration. Research themes emphasize mitochondrial alternative oxidase evolution, genomic signatures of mitonuclear interactions, and the role of carotenoids in honest signaling. His 2023 publications highlight critiques of condition-dependent trait theories and methodological approaches in ecological data analysis. Notable work includes studies on hybrid dysfunction in carotenoid production and lifespan predictions from early-life reproductive events. Grants include a 2019 NSF Postdoctoral Fellowship investigating mitochondrial respiratory chain roles in sexual reproduction. The lab’s interdisciplinary focus bridges evolutionary physiology, genetics, and ecology, with implications for understanding organismal adaptation to challenging environments.

Iman Soltaniمشاهده پروفایل

استادیار

• Machine Learning
• Robotics
• Automation
• +۵ مورد دیگر

Iman Soltani is an Assistant Professor at the University of California, Davis, jointly appointed in Mechanical and Aerospace Engineering and Electrical and Computer Engineering, and affiliated with the Institute of Transportation Studies. His research integrates machine learning, control systems, and robotics across scales—from nanoscale materials manipulation to autonomous driving and medical device development. He leads the Soltani Lab, focusing on interdisciplinary projects involving computer science, electrical, and mechanical engineering principles. Key research interests include automated systems, anomaly detection, robotic manipulation, and AI-driven navigation. His work bridges theoretical advancements with experimental innovations, such as the Krysalis Hand and Cardreamer platforms. Awards include the MIT Carl G. Sontheimer Award and National Instruments Engineering Impact Award. Recent publications span autonomous infrastructure surveying, bimanual robotic manipulation, and marine navigation systems. Collaborations span academia and industry, including Ford Greenfield Labs. His lab is located in the Mechanical & Aerospace Engineering building at UC Davis.

• Machine Learning
• Robotics
• Artificial Intelligence
• +۵ مورد دیگر

DUPUIS Yohan is a Research Director at CESI, leading the Engineering and Numerical Tools research team. His work focuses on perception and mapping for cyber-physical systems, intelligent robotics, and transportation systems. He holds an HDR from the University of Rouen Normandy (2019) and a PhD in Electrical Engineering (2012). He coordinates major national projects including the France 2030 CAIRE project (AI sector), ASTRID Robotics SCOPES, and Battery School initiatives. Education includes an Engineering Diploma from ESIGELEC (2009), MSc in Electrical Engineering from Union Graduate College (USA), and a PhD focused on omnidirectional vision for biometrics. His research spans semantic mapping, autonomous systems, and sensor fusion with applications in smart cities, industrial automation, and maritime networks. Key research interests include: Multi-agent cooperative perception SLAM algorithms for low-texture environments Autonomous vehicle localization Human-robot interaction in industrial contexts LiDAR and radar sensor systems He advises 8 active PhD students working on topics like human-robot affordance modeling, object pose estimation, and mobility prediction in smart cities. Notable contributions include the SynWoodScape autonomous driving dataset and innovative digital twin methodologies for industrial workstations. Led projects include: France 2030 CAIRE project (AI sector coordination) ASTRID Robotics SCOPES (2022-2025) Battery School initiative (2022-2027) ConfluenceS Excellence program (2024-2032) His publications span over 50 peer-reviewed articles, with recent focus on multimodal perception systems and AI-driven urban mobility solutions.

• Photogrammetry
• Remote Sensing
• Underwater Imaging
• +۷ مورد دیگر

Dr. Petra Helmholz is an Associate Professor in the School of Earth and Planetary Sciences at Curtin University, specializing in Photogrammetry and Remote Sensing. She holds a German Dipl.-Ing. (M.Sc.) and Dr.-Ing. (Ph.D.) in Geomatics. Her research focuses on underwater, terrestrial, and airborne photogrammetry, with applications in health, agriculture, heritage mapping, and engineering. She has received multiple awards, including the Asia Pacific Excellent Award in Education (2018) and WA Spatial Awards. She serves as National Chair of the Remote Sensing & Photogrammetry Commission (SSSI) and is an Associated Editor of the journal PE&RS. Helmholz leads the Bachelor of Surveying program at Curtin and holds licenses in remote piloting and surveying. Her work bridges geospatial technologies with interdisciplinary fields like medicine and environmental science. Education: 2006–2012: Ph.D. in Photogrammetry, Leibniz University Hannover 2003–2005: Certified Licensed Surveyor, Germany 1997–2003: B.Sc./M.Sc. in Surveying, TU Berlin Research Interests: Underwater and airborne photogrammetry, 3D reconstruction for medical and heritage applications, thermal simulation of urban environments, and geospatial data analysis. Her projects include facial analysis for rare disease diagnosis, coral growth estimation, and pipeline monitoring. Publications highlight innovations in underwater imaging techniques, urban heat island studies, and medical 3D modeling. She actively contributes to international bodies like ISPRS and ASPRS, co-chairing working groups on geospatial data standards and applications.

Christopher Somesمشاهده پروفایل

پژوهشگر

• Marine Biogeochemistry
• Ocean Modeling
• Isotope Geochemistry
• +۵ مورد دیگر

Christopher Somes is a Research Scientist at GEOMAR Helmholtz Centre for Ocean Research Kiel, where he works in the Biogeochemical Modeling Research Unit. With expertise in ocean biogeochemistry and Earth system modeling, he investigates how environmental changes such as pollution and climate affect ocean biology and chemistry. His research integrates isotope geochemistry with climate modeling to understand past, present, and future ocean conditions. Dr. Somes earned his Ph.D. in 2013 from Christian-Albrechts-Universität zu Kiel with a dissertation on "Nitrogen Isotopes in the Global Ocean." He completed his Master of Science in Oceanography in 2010 and Bachelor of Science in Physics in 2006, both from Oregon State University. Dr. Somes' research focuses on analyzing elemental isotope ratios to gain insights into marine biogeochemical cycles and ecosystem dynamics. He uses global Earth system climate models to predict ocean responses to environmental changes and associated climate feedbacks. His work spans from modern ocean conditions to past climate change events recorded in ocean sediments, with particular emphasis on nutrient cycling, ocean deoxygenation, and the biological carbon pump. His recent publications reveal a strong trend toward integrating paleoceanographic records with future climate projections. The research shows increasing sophistication in modeling nutrient limitations, particularly iron and nitrogen cycles, and their impacts on marine productivity. His work consistently connects historical ocean conditions with contemporary observations to improve future projections. ISOIRON (2023-2026): Isotopic constraints of the global marine iron cycle, ocean productivity, and deoxygenation (Principal Investigator) ISODEG (2021-2025): Isotopic constraints of declining marine nutrient reserves during the last deglaciation (Principal Investigator) RETAKE II (2024-2027): CO2 removal through alkalinity enhancement (Associate Member) As Principal Investigator on multiple DFG-funded projects, Dr. Somes mentors students and collaborates with international research teams. His work spans from developing sophisticated ocean models to analyzing historical ecosystem changes using stable isotopes in marine organisms, with over 50 peer-reviewed publications to date. Dr. Somes is part of GEOMAR's Water Column Biogeochemistry Group and co-leads the PAGES (Past Global Changes) working group on Past Ocean Oxygenation. His research integrates observational data, laboratory analysis, and computational modeling to address critical questions about ocean-climate interactions and their implications for future environmental conditions.

Emma Hadréمشاهده پروفایل

پژوهشگر

• Marine Geophysics
• Volcanology
• Geomorphology
• +۷ مورد دیگر

Emma Hadré, M.Sc., is a doctoral researcher at Christian-Albrechts-Universität zu Kiel in the Marine Geophysics and Hydroacoustics team, funded by the DFG Priority Programme 'SPP 1006 - ICDP'. She specializes in volcanic flank collapse events and tsunami hazard assessment using hydroacoustic data. Doctoral Researcher (2023–present), Kiel University M.Sc. in Physical Geography: Environmental History, University of Bremen (2023 thesis) B.A. in Geography/Biology, Universität Osnabrück Her research integrates seismic, parasound, and bathymetry data to reconstruct collapse histories in the Cape Verde archipelago, particularly Fogo volcano. She developed GIS algorithms for submerged flank hazard analysis during her master's and previously contributed to CT scanning workflows for sediment cores at the Alfred Wegener Institute. Emma's work spans marine geophysics, climate change inequality studies, and geoarchaeological fieldwork, with active participation in oceanographic expeditions like RV SONNE (SO290) and RV METEOR (M178). Selected publications examine GEBCO bathymetry accuracy, climate inequity metrics, and historical climate impacts from the Tambora eruption. Her CV highlights multidisciplinary methodologies including georadar, magnetometry, and piston coring campaigns.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

Professor Adam Prugel-Bennett is a faculty member at the School of Electronics and Computer Science , University of Southampton. His research spans artificial intelligence, machine learning, and robotics, with a focus on 3D perception, explainable AI, and marine data analysis. He contributes to interdisciplinary projects including coastal morphological analysis and underwater robotics. Key research areas include: LiDAR-based 3D object detection Multilevel explainable artificial intelligence Georeferenced seafloor imaging Variational autoencoder applications Bathymetric mapping His recent work explores cross-domain adaptation, sensor fusion, and algorithmic stability. He supervises PhD students in computer science and engineering while collaborating with research groups like Vision, Learning and Control. Current projects involve EPSRC-funded initiatives on complex computational systems and AI-based knowledge exchange for coastal analysis.

• Uncertainty Modeling
• Fuzzy Sets
• Image Processing
• +۴ مورد دیگر

André Bigand is a Lecturer at Université du Littoral Côte d'Opale (ULCO) and leads the IMAP research team. His work focuses on uncertainty modeling with fuzzy sets, image processing, and deep learning applications in art analysis. 1981: Aggregation of Applied Physics 1987: DEA in Electronics-Instrumentation (Univ. Paris6) 1993: Doctorate in Electronics (Univ. Paris6) 2001: Authorization to Direct Research (ULCO) His research spans image processing , deep learning , and time series analysis , with applications in phytoplankton dynamics , face detection in paintings , and explainable AI . He has published 11 international peer-reviewed articles and 41 communications with proceedings. Bigand collaborates with international institutions like the University of Waterloo (Canada) and the Lebanese University. He has served as Jury President for the 'Electronics-Instrumentation' Master's Degree and co-led ERASMUS+ programs. His recent publications emphasize visual art analysis , plant disease detection , and environmental time series imputation . He supervises 2 ongoing theses and has directed 5 thesis projects.

Chengyu Liمشاهده پروفایل

دانشیار

• Fluid Mechanics
• Computational Fluid Dynamics
• Fluid-Structure Interaction
• +۷ مورد دیگر

Chengyu Li is an Associate Professor in the Department of Mechanical and Aerospace Engineering at Case School of Engineering, Case Western Reserve University. His research program focuses on developing computational models to investigate the underlying flow physics and transport phenomena associated with biological and biomedical flows. Dr. Li received his PhD in Mechanical & Aerospace Engineering from the University of Virginia in 2016, following an M.S. from the same institution in 2014. He completed his undergraduate education with a B.S. in Mechanical Engineering from Dalian Jiaotong University, China, in 2010. Prior to joining Case Western, he served as an Assistant Professor at Villanova University from 2018 to 2024 and completed a postdoctoral position at The Ohio State University (2016-2018). Dr. Li's research spans multiple areas of fluid dynamics with applications in both engineering and healthcare. His work integrates computational fluid dynamics, immersed boundary methods, and high-performance computing to address complex problems in biological locomotion and biomedical flows. Specific research foci include: Bio-inspired propulsion mechanisms, studying how biological systems like insects and ctenophores achieve efficient locomotion Human nasal airflow dynamics, with applications to understanding and treating conditions like empty nose syndrome Fluid-structure interaction in flapping flight, examining how wing flexibility affects aerodynamic performance Odor-guided navigation, investigating how insects balance aerodynamic performance with olfactory sensitivity Analysis of Dr. Li's publication record reveals a strong interdisciplinary approach that bridges fundamental fluid dynamics with practical applications. His recent work shows increasing focus on the intersection of fluid dynamics and sensory biology, particularly how insects use airflow information for navigation. He has maintained a consistent research program in biomedical flows, with particular attention to nasal airflow and its clinical implications across multiple conditions including empty nose syndrome, nasal septal perforation, and olfactory sensitivity. Dr. Li has received several prestigious awards recognizing his research excellence: Young Investigator Program (YIP) Award 2024 from AFOSR Lewis F. Moody Award 2022 from ASME Faculty Early Career Development Program (CAREER) Award 2021 from NSF Ralph E. Powe Junior Faculty Enhancement Award 2019 from ORAU Polak Young Investigator Award 2017 from AChemS Dr. Li leads the Flow Simulation & Flow Physics Lab, where he mentors students in computational fluid dynamics research. His work has been supported by multiple grants including AFOSR FA9550-11-1-0058, AFOSR FA9550-12-1-007 monitored by Dr. Douglas Smith, and NSF CEBT-1313217. He collaborates extensively with researchers across disciplines, including Tyson Hedrick (UNC Chapel Hill), Kai Zhao (OSU), and Haibo Dong (UVa). Dr. Li actively contributes to the academic community through service roles including CFDTC Vice Chair (2024-2026) and Secretary (2022-2024) for ASME, and as a member of the Division of Fluid Dynamics at APS since 2011.

• Environmental Engineering
• Renewable Energy Systems
• Thermal Energy Storage
• +۳ مورد دیگر

Zhang R is a Professor at Texas A&M University's College of Engineering, specializing in interdisciplinary research across environmental engineering, renewable energy systems, and biomedical nanotechnology. Recent work includes: Developing thermal energy storage solutions with moisture effect modeling and regeneration strategies Advancing UAV-based agricultural monitoring through OSNet instance segmentation networks Innovating hydrogel sensors for biomedical applications using MXene-cellulose composites Key contributions span: Marine stress genomics - Investigating shrimp hepatopancreas responses to alkalinity stress Cancer nanomedicine - Designing biomimetic nanoparticles for leukemia treatment Immunological mechanisms - Discovering USP30 inhibition in T cell longevity Collaborative research extends to neurogenetic studies of stuttering disorders and electrochemical seawater oxidation catalysts. Current projects integrate machine learning with energy systems and advance biomedical diagnostics through nanomaterial innovations.