جست‌وجوی استاد و پژوهشگر

• Forest Inventory and Monitoring
• LiDAR Technology Applications
• Forest Regeneration Quantification
• +۳ مورد دیگر

Tobias Ofner-Graff is a researcher at the Institute of Forest Growth within the Department of Ecosystem Management, Climate and Biodiversity at the University of Natural Resources and Life Sciences, Vienna (BOKU). Based at Peter-Jordan-Straße 82, 1190 Wien, his work focuses on advanced forest monitoring technologies. His research interests include: LiDAR and remote sensing applications in forestry Automated forest inventory systems Forest regeneration quantification Airborne Laser Scanning (ALS) data analysis Sustainable forest harvesting planning Recent project contributions include: Leading lidar-based forest monitoring systems development Developing spatial forest growth models Implementing digital inventory workflows His publications demonstrate expertise in: Quantifying forest resources through 3D point clouds Advanced timber stack measurement techniques ALS data integration for forest modeling Mobile laser scanning applications Forest climate adaptation strategies

• Environmental Engineering
• Water Quality
• Plumbing Systems
• +۳ مورد دیگر

Andrew J Whelton is a Professor of Civil and Construction Engineering at Purdue University's College of Engineering, with concurrent appointments in Sustainability Engineering and Environmental Engineering. He serves as Director of the Healthy Plumbing Consortium and Lead for the Center for Plumbing Safety, focusing on water quality, chemical contamination, and public health in building plumbing systems. Professor, Civil and Construction Engineering Professor, Sustainability Engineering Professor, Environmental Engineering Director, Healthy Plumbing Consortium Lead, Center for Plumbing Safety His research spans environmental engineering and public health, with key themes including chemical contamination from plastic pipe degradation, post-disaster water system recovery, wildfire-related water quality impacts, and microbial risks in premise plumbing. Recent work addresses crises like the East Palestine chemical spill and Maui wildfires, while also developing predictive models for water quality and evaluating sustainable infrastructure materials. Scientific awards and recognitions include: Rapid Response Research (RAPID) Grants from NSF for disaster-related studies Environmental Protection Agency (EPA) support for building water quality programs Leadership in interdisciplinary consortia focused on plumbing safety Development of novel tools for water quality monitoring and remediation His publications reveal trends in: Chemical leaching from plastic piping materials Environmental justice in water contamination crises Integration of machine learning for water quality prediction Microbial ecology in stagnant plumbing systems Policy recommendations for disaster response Sustainable material innovation for infrastructure

• Excavation Engineering
• Rock Blasting and Demolition
• Geotechnical Engineering
• +۱۲ مورد دیگر

Marilena Cardu is an Associate Professor in the Department of Environmental, Land, and Infrastructure Engineering (DIATI) at the Polytechnic University of Turin. She is actively involved in teaching, research, and supervision within the fields of excavation engineering, rock blasting, tunneling, and sustainable mining. She serves as a course instructor for key programs including Civil and Environmental Engineering and Georesources and Geoenergy Engineering. Academic Rank: Associate Professor Institution: Polytechnic University of Turin Department: DIATI (Environmental, Land, and Infrastructure Engineering) Email: marilena.cardu@polito.it Her research interests center on excavation engineering and safety, with strong interdisciplinary engagement in geotechnics, environmental engineering, and mineral resource management. She specializes in rock blasting, demolition techniques, TBM (Tunnel Boring Machine) performance, and mining safety. Her work aligns with UN SDGs such as Industry and Innovation, Sustainable Cities, and Responsible Production. The recent publications reflect a strong trend in tunneling technology, rock fragmentation, blast safety, and sustainable resource development. Her work combines experimental, numerical, and field-based approaches, often applied to real-world industrial and infrastructure challenges. Scientific Projects and Responsibilities: Scientific Director for collaborative research in excavation engineering (2023–2026) Scientific Manager for gas network compliance testing (2022–2025) Lead on multiple commercial consultancy projects in rock characterization, blast design, and vibration monitoring She supervises PhD students such as Nestor David Mejia Almeida and Oveis Farzay, focusing on TBM modeling and geomechanics. She is a key member of the Geomechanics and Geotechnologies Laboratory at DIATI, contributing to both academic and applied research in underground construction and mining safety.

• Trustworthy AI
• Software Testing & Verification
• Requirements Engineering
• +۵ مورد دیگر

Prof. Lionel C. Briand is a leading academic in software engineering and trustworthy AI, holding appointments at the University of Ottawa (EECS Department, Nanda Laboratory) and the University of Limerick (Lero - National Software Research Centre). He serves as Director of Lero and Scientific Director of the SnT software verification lab in Luxembourg. His research focuses on software testing, model-driven engineering, AI-driven quality assurance, and regulatory compliance. He has held the Canada Research Chair (Tier 1) since 2003 and led major institutions like Simula Research Laboratory (Norway) and Fraunhofer Institute (Germany). Education & Career: Full Professor at Carleton University (2008–2012) Head of Software Quality Engineering at Fraunhofer IESE (2000–2008) Research Scientist at NASA Software Engineering Lab (1990s) Research Interests: His work spans secure AI systems, automated legal compliance (e.g., GDPR), metamorphic testing, search-based software engineering, and safety-critical systems. He emphasizes practical applications, collaborating with industry partners globally. Awards & Recognition: IEEE Fellow (2010), ACM Fellow (2020) Harlan Mills Award (2012), ERC Advanced Grant (2016) Fellowships from Royal Society of Canada (2023) and Academia Europaea (2025) Grants & Labs: PEARL grant from Luxembourg FNR for SnT lab ERC Advanced Grant for software testing research Leadership roles in Lero and Nanda Lab Publications: Over 500+ papers on testing methodologies, AI ethics, and regulatory compliance. Notable tools include CompAI (GDPR compliance) and Teasma (DNN test adequacy).

Thomas Jordanمشاهده پروفایل

استاد

• Hydrogen Safety
• Energy Technology
• Safety Engineering
• +۳ مورد دیگر

Thomas Jordan is a Professor and head of the Hydrogen Department at the Institute for Thermal Energy Technology and Safety (ITES) at Karlsruhe Institute of Technology (KIT). His research focuses on ensuring the safe deployment of hydrogen technology as a key pillar for fossil-fuel-free energy systems. He investigates hydrogen behavior through theoretical and experimental approaches, including combustion risks in complex environments and safety measures like ventilation systems. Jordan contributes to international standards via the ISO and leads collaborations with institutions in the USA, Canada, Japan, and Korea. As part of KIT’s Energy Center, he oversees the Hydrogen Test Center Karlsruhe (HYKA), an industrial-scale facility for experimental hydrogen safety testing. His work has driven the development of simulation tools for reactive flows and new test standards. Since 2005, he has represented Germany in the Hydrogen Safety Task of the International Energy Agency (IEA) and co-founded the International Association for Hydrogen Safety (HySafe), serving on its board. Since 2017, he has been a member of the European Hydrogen Safety Panel.

Jian Kangمشاهده پروفایل

استاد

• Biostatistics
• Bayesian Methods
• Gaussian Processes
• +۱۱ مورد دیگر

Jian Kang is a Professor and Associate Chair for Research at the University of Michigan School of Public Health , specializing in Biostatistics . His work focuses on developing advanced statistical methods for large-scale biomedical data , with applications to precision medicine , neuroimaging , and genomics . Education: PhD in Biostatistics, University of Michigan (2011) MS in Mathematics (Statistics), Tsinghua University (2007) BS in Statistics, Beijing Normal University (2005) Research Interests include Bayesian nonparametric methods , deep learning for medical imaging , ultra-high-dimensional variable selection , and graphical models for network inference . His 2025-2023 publications demonstrate expertise in Bayesian hierarchical modeling , spatial statistics , and machine learning for healthcare . Scientific Awards : Michigan SPH Excellence in Research Award (2025) ICSA President's Citation Award (2024) Statistics in Biopharmaceutical Research Best Paper (2023) Best Paper in Biometrics by IBS Member (2022) Fellow, American Statistical Association (2021) Grants include NSF-IIS (2021-2025) for BCI statistical learning , NIGMS (2020-2022) for metabolomics biomarker selection , NIDA (2020-2025) for imaging data analysis , and NIMH (2014-2025) for multidimensional neuroimaging methods . Labs and Teams develop Bayesian computational tools for neuroimaging and spatial transcriptomics , collaborating with institutions like Emory University and University of North Carolina.

Laia Mogas-Soldevilaمشاهده پروفایل

استادیار

• Biomaterials
• Sustainable Design
• Biofabrication
• +۳ مورد دیگر

Laia Mogas-Soldevila serves as Assistant Professor of Graduate Architecture and Director of DumoLab Research at the University of Pennsylvania's Stuart Weitzman School of Design, pioneering radically sustainable material practices that bridge science, engineering, and the arts for architectural and product design innovation. Her academic credentials include: Interdisciplinary doctorate in biomaterials science, biomedical engineering, and advanced design from Tufts University School of Engineering Two master’s degrees from the Massachusetts Institute of Technology School of Architecture Licensed architect with Fine Arts minor from Polytechnic University of Catalonia and École Nationale Supérieure de Beaux-Arts Dr. Mogas-Soldevila's research reimagines matter as a fundamental design driver through biomaterials and bio-based fabrication , emphasizing environmental justice and circular economy principles. Her work partners with scientists to develop unprecedented material capabilities, spanning from molecular-scale biopolymer engineering to full-scale architectural applications that address climate challenges. Analysis of her 15 most recent publications (2020-2025) reveals dominant themes in carbon-sequestering living materials, agricultural waste valorization, and adaptive biological skins. These works consistently bridge architecture, material science, and environmental engineering, with increasing focus on participatory design and urban farming applications as seen in her 2024 Portable Bioremediation Technologies project. Her scientific recognition includes: Johnson&Johnson Foundation Woman in STEM2D Scholar Award Research funding encompasses Penn's Research Foundation Grant, Environmental Innovation Grant, Sachs Art Innovation Grant, and Global Engagement Fund, supporting her interdisciplinary exploration of sustainable material systems. Her pedagogy cultivates novel theory and applied methods for biomaterial implementation across design disciplines. As DumoLab Research Director, she leads cross-disciplinary collaborations developing material-driven computational workflows for digital fabrication, with recent projects exhibited at MoMA, Milan/London Design Weeks, and ACADIA conferences, translating laboratory innovations into tangible environmental solutions.

Bo Huمشاهده پروفایل

استاد

• Biostatistics
• Bioinformatics
• Neurosurgery
• +۷ مورد دیگر

Bo Hu is Professor of Biostatistics & Bioinformatics and Professor of Neurosurgery at Duke University, where he leads methodological and collaborative research at the intersection of biostatistics, bioinformatics, and clinical neurosciences. His dual appointments situate him within the Division of Biostatistics in the Department of Biostatistics & Bioinformatics and within the neurosurgical faculty. Education: Ph.D. in Biostatistics, University of Wisconsin–Madison, 2006 Research Interests: Professor Hu’s methodological work centers on advanced biostatistical and machine-learning techniques for high-dimensional biomedical data, including generative AI, synthetic data generation, and predictive analytics in medicine. Clinically, he collaborates on precision-medicine trials in oncology, neurodegeneration (Alzheimer’s disease), metabolic disease (type 2 diabetes and bariatric surgery), and treatment-resistant depression. His neuroimaging genetics portfolio explores structural brain endophenotypes in bipolar disorder and epilepsy using single-cell transcriptomic integration. Complementing his medical research, he maintains a vigorous program in remote-sensing informatics, developing deep-learning solutions for object detection, domain adaptation, and energy-infrastructure mapping from overhead imagery. Recent Grant Portfolio: Empagliflozin to Improve Right Ventricular Function in Pulmonary Arterial Hypertension – Cleveland Clinic Lerner College of Medicine (2025-2030) Gender and Asthma – Mayo Clinic Hospital-Arizona (2025-2027) Engaging Patients in Prenatal Genetic Testing Decisions – Cleveland Clinic Lerner College of Medicine (2025-2027) Laboratory & Collaborative Networks: Professor Hu leads interdisciplinary teams that bridge Duke’s Department of Biostatistics & Bioinformatics with clinical departments (Neurosurgery, Psychiatry, Medicine) and external partners such as Cleveland Clinic, Mayo Clinic, and multiple NIH consortia. These collaborations support large-scale clinical trials, multi-omics neuroimaging studies, and AI-driven remote-sensing analytics.

• Analysis and transformation of programs
• Software Security
• Parallel and distributed computing technologies

Harutyun Ishkhanovich Avetisyan is a Professor and Head of the Basic Department "System Programming" at the Faculty of Computer Science of the National Research University Higher School of Economics (HSE). He began his tenure at HSE in 2017 and brings 30 years of scientific and teaching experience to his role. Additionally, he serves as the Director of the Institute for System Programming of the Russian Academy of Sciences (ISP RAS), a position he has held since 2015. Avetisyan holds numerous prestigious academic distinctions, including being elected as an Academician of the Russian Academy of Sciences in 2019 and as a Corresponding Member in 2016. He earned his Doctor of Physical and Mathematical Sciences degree in 2012 and was awarded the academic title of Associate Professor in 2009. His educational background includes a specialty in "Applied Mathematics" from Yerevan State University (1993). His research focuses on three main areas: analysis and transformation of programs, software security, and parallel and distributed computing technologies. These interests are reflected in his extensive publication record and leadership in major research initiatives. His work bridges theoretical computer science with practical applications in cloud computing, secure data storage, and high-performance computing systems. Avetisyan's scholarly contributions demonstrate a consistent focus on system programming challenges, particularly in the areas of code analysis, optimization, and security. His recent publications indicate a growing interest in cloud computing paradigms, smart city infrastructure, and energy-efficient computing solutions. His research has significant implications for both academic theory and industrial applications in software development. Among his notable recognitions, Avetisyan was awarded the medal of the Order "For Merit to the Fatherland" 2nd degree in 2021 for his significant contributions to science and dedicated service. He also serves on the editorial boards of several prestigious journals including "Programming" (since 2015) and "Proceedings of the Institute for System Programming of the RAS" (since 2010). Throughout his career, Avetisyan has led and participated in numerous research grants funded by the Ministry of Education and the Russian Foundation for Basic Research. His professional trajectory shows steady progression from postgraduate studies (1997-2000) to research fellow (2000-2002), deputy director of ISP RAS (2002-2015), and ultimately director of the institute (2015-present). At HSE, Avetisyan teaches courses in parallel programming and mentor seminars for master's students in Software Engineering. His teaching philosophy emphasizes the integration of cutting-edge research with practical software development skills, preparing students for careers at the forefront of computer science.

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

Paulo Jorge Freitas de Oliveira Novais is a Full Professor of Computer Science at the Department of Informatics, School of Engineering, Universidade do Minho, where he also holds a Habilitation in Computer Science. He leads the Synthetic Intelligence Lab at ALGORITMI Centre and coordinates the research line on Ambient Intelligence for Well-Being and Health Applications. His research spans Intelligent Systems, Machine Learning, Multi-Agent Systems, and their applications in Smart Cities, Health Informatics, and AI Ethics. PhD in Computer Science, Universidade do Minho, 2003 Habilitation in Computer Science, Universidade do Minho, 2011 Research interests include Ambient Intelligence, Ambient Assisted Living, Intelligent Environments, AI and Law, Conflict Resolution, and Explainable AI. His work focuses on enhancing system intelligence and reliability through novel architectures and ethical frameworks. Recent publications highlight applications in wastewater energy prediction, violence detection, student risk modeling, and urban logistics. Awards include multiple Best Paper and IBM Excellence recognitions across 2015–2023, plus a 2022 Career Recognition Award from the Ibero-American Society of Artificial Intelligence. Senior IEEE Member Chair of IEEE Computational Intelligence Chapter, Portugal IFIP TC 12 Artificial Intelligence Working Group Leadership He has supervised 132 PhD and Master’s students and contributed to editorial boards of journals like JAISE and ComSIS . His leadership roles include coordinating LASI – Intelligent Systems Associate Laboratory and serving as former president of APPIA.

Klaus Mosthafمشاهده پروفایل

دانشیار

• Contaminant Transport in Porous Media
• Groundwater Contamination
• Numerical Modeling
• +۱۰ مورد دیگر

Klaus Mosthaf is an Associate Professor in the Department of Environmental and Resource Engineering at the Technical University of Denmark (DTU), where he conducts research on contaminant transport and numerical modeling in porous and fractured media. His work focuses on protecting groundwater resources through advanced modeling of contamination from substances like PFAS, chlorinated solvents, and pesticides. He is actively involved in teaching and academic leadership, coordinating the Nordic Masters program Enviro5Tech and the Sino-Danish Center module on Pollutants and Pollution Control. Research Interests: Transport processes in porous media Groundwater contamination and remediation Numerical modeling of reactive transport Aquifer Thermal Energy Storage (ATES) Fractured and variably saturated geologies Coupled porous-medium and free-flow systems His recent publications reveal a strong focus on PFAS fate, bioremediation in ATES systems, and tracer-based characterization of glacial tills. He employs tools like COMSOL Multiphysics, Python, and FEFlow to develop predictive models grounded in laboratory and field data. Scientific Contributions: Active contributor to over 60 publications in hydrogeology and environmental engineering Key developer of models for coupled processes in subsurface systems Organizer and speaker at international conferences on multiphase flow and contaminant transport Advising and Grants: Klaus Mosthaf supervises multiple PhD students and has coordinated significant research projects, including those on PFAS transport and bioremediation. He is the main supervisor of two active PhD projects and has previously co-supervised two others. His leadership extends to board membership in the Danish Academy of Technical Sciences on Soil and Groundwater (ATV Jord og Grundvand), where he fosters collaboration among academia, consultants, and public authorities. Laboratories and Research Groups: His work is conducted within DTU Sustain, a leading research environment in environmental engineering, where he collaborates with experts in hydrogeology, bioremediation, and sustainable technologies. He is deeply integrated into a network of national and international collaborators focused on groundwater protection and sustainable subsurface utilization.

• Reservoir Engineering
• CO2 Enhanced Oil Recovery & Storage
• Data-Driven Reservoir Modeling
• +۵ مورد دیگر

Ashkan Jahanbani Ghahfarokhi is an Associate Professor in Reservoir Engineering at NTNU’s Department of Geosciences since 2019. He leads the CEORS Gemini Centre (CO2 Enhanced Oil Recovery & Storage) and is a core member of the BRU21 Reservoir Management group. His research focuses on data-driven subsurface modeling, CO2 storage, and optimization of oil recovery processes. Education: PhD, NTNU (2015); MEng, University of Calgary (2009); MSc/BSc, Petroleum University of Technology, Iran (2006–2009). Roles: Head of Reservoir Engineering Group (2021–2022), Project Manager for NORHED II (2022), and NTNU’s Outstanding Academic Fellow (2022–2026). Research interests include CO2-EOR/Storage, machine learning applications, proxy modeling, and reservoir simulation. He has supervised 20+ students and published over 40 journal/conference papers. Awards include DNVA postdoc scholarship (2015–2017) and PoreLab postdoc (wettability studies). Teaching: Masters/PhD courses in reservoir fluids, simulation, and geomechanics. Guest editor for Energies (AI in Oil & Gas).

• Sports Science
• Exercise Physiology
• Nutritional Science in Athletics
• +۱۴ مورد دیگر

Dr. Ciarán Ó Catháin is a Lecturer in the Department of Sport and Health Science within the Faculty of Science and Health. He is actively engaged in research at the intersection of sports science, exercise physiology, and nutritional health, with a strong emphasis on athlete performance and well-being. His research interests include: Sports Science and Exercise Physiology Nutritional Science in Athletics Female Athlete Health, particularly menstrual cycle and hormonal contraceptive tracking Dietary intake and culinary nutrition among athletes Resisted sprint training and performance monitoring Systematic reviews and meta-analyses in sports interventions Application of machine learning and wearable technology in sports Dr. Ó Catháin’s recent publications demonstrate a trend toward evidence synthesis (systematic reviews and meta-analyses), interdisciplinary methodologies, and a growing focus on gender-specific considerations in sports performance. His work integrates engineering concepts such as gait analysis and phase velocity with health sciences, reflecting a cross-disciplinary approach. He also explores emerging technologies like augmented reality and synthetic data generation for performance prediction. While no formal scientific awards are listed, his research has contributed to high-impact journals including Sports Medicine , Frontiers in Sports and Active Living , and Nutrition Bulletin . His h-index of 10 and 254 citations reflect a solid and growing academic influence. There is no available information regarding student supervision, grant funding, laboratory affiliations, or collaborative teams. However, his frequent co-authorship suggests active research collaboration, particularly with researchers in sports physiology and nutrition.

• Quantum Computing
• Nanotechnology
• Nanoscale Electronics
• +۵ مورد دیگر

Heike Riel serves as IBM Fellow, Head of Science of Quantum and Information Technology, and Lead of IBM Research Quantum Europe at IBM Research. Her work focuses on quantum computing, nanoscale electronics, and optoelectronic device innovation. PhD in Physics (University of Bayreuth, 2003) MBA (Henley Business School, 2010) Research interests center on quantum computing hardware, nanoscale device engineering, and neuromorphic computing technologies. Her publications demonstrate expertise in semiconductor-metal interfaces, superconducting quantum devices, and nanowire-based systems. Article keywords include Quantum Physics , Nanotechnology , and Materials Science with sub-fields spanning spin qubit control , Josephson junction dynamics , and hybrid quantum systems . TR100 (2003) IEEE Andrew S. Grove Award (2022) National Academy of Engineering (2022) Riel advises academic institutions as member of review committees and serves on Germany's Forschungszentrum Jülich Scientific Advisory Council. She has filed over 50 patents in semiconductor technologies and led the development of 20" full-color OLED displays.

• Bioinformatics
• Computational Intelligence
• Natural Language Processing
• +۵ مورد دیگر

Prof. Yu-Seop Kim is a Professor at the School of Software, Hallym University, Chuncheon-si, Republic of Korea. He holds a B.Eng. in Computer Science from Sogang University (1992), and M.Eng. (1994) and D.Eng. (2000) in Computer Engineering from Seoul National University. His academic work is centered on the integration of artificial intelligence with biomedical applications. B.Eng., Department of Computer Science, Sogang University, 1992 M.Eng., Computer Engineering, Seoul National University, 1994 D.Eng., Computer Engineering, Seoul National University, 2000 His research interests lie at the intersection of bioinformatics, computational intelligence, natural language processing, and deep learning , with a strong emphasis on medical applications. He actively explores how AI can assist in clinical diagnostics and healthcare documentation. The recent trend in his publications demonstrates a focus on AI-driven medical image analysis and automated clinical text generation . His work leverages convolutional neural networks and language models to interpret brain CT scans, detect aortic dissection, and augment medical reports for cerebrovascular diseases. These efforts reflect a consistent effort to bridge machine learning with real-world clinical challenges. While no scientific awards are listed in the provided text, his collaborative research output suggests active engagement in academic and clinical partnerships. Prof. Kim has advised multiple researchers and co-authored numerous publications, particularly in journals like Applied Sciences and Journal of Clinical Medicine . Although specific grant information is not mentioned, his research likely involves funding for AI in healthcare. He collaborates with colleagues such as Byoung-Doo Oh, Chulho Kim, and Bitnarae Kim, indicating a multidisciplinary team approach. His work appears to be conducted within a research group or lab focused on AI for medical imaging and language processing , potentially involving students and clinical collaborators from affiliated institutions like Chuncheon Sacred Heart Hospital. This environment supports translational research from algorithm development to clinical validation.