جست‌وجوی استاد و پژوهشگر

• Remote Sensing
• Forestry
• Geospatial Data Fusion
• +۴ مورد دیگر

Dr. Jim O'Hehir is a Researcher affiliated with the University of South Australia under the UniSA STEM school and the Sustainable Infrastructure and Resource Management (SIRM) department. He also serves as the General Manager of the Forestry Centre of Excellence at the university. His work spans interdisciplinary applications in remote sensing, geospatial analysis, and virtual reality for forestry. He collaborates with institutions like the University of Tasmania, OneFortyOne Plantations, and the National Institute for Forest Products Innovation (NIFPI), with recent grants from the Australian Government Research Training Program Scholarship , Gottstein Trust , and industry partners. Dr. O'Hehir’s research focuses on overcoming technical limitations in forest inventory systems through LiDAR data fusion , UAV-based hyperspectral imaging , and VR visualization techniques . His 2024 publications highlight innovations in 3D point cloud generation, multispectral residue assessment, and AI-driven fire suppression frameworks. He contributes to policy discussions on carbon storage optimization in timber plantations under Australia’s Emissions Reduction Fund (ERF). 2024: 3D Point Cloud Fusion Using Aerial and Terrestrial Laser Scanning 2024: Multispectral Assessment of Clean-Row Treatments 2024: Immersive VR for Forest Point Clouds 2024: AI in Fire Smoke Detection 2023: Sub-Metre Geospatial Feasibility His grants and collaborations emphasize operational efficiency in forestry, with teams like the Forestry Centre of Excellence and partnerships with Geoscience Australia and Swinburne University of Technology . Future work includes scaling onboard AI for satellite missions and refining standards for data fusion in sub-canopy environments.

Noboru Matsudaمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Learning Sciences
• Educational Technology
• +۵ مورد دیگر

Noboru Matsuda is an Associate Professor in the Department of Computer Science at North Carolina State University, affiliated with the Chancellor’s Faculty Excellence Program cluster in Digital Transformation of Education . He leads the Innovative Educational Computing Laboratory and is an affiliate of the Center for Educational Informatics . His research bridges artificial intelligence , cognitive science , and education to develop adaptive learning technologies. Master of Science in Math Education, Tokyo Gakugei University Ph.D. in Intelligent Systems, University of Pittsburgh Matsuda’s work focuses on intelligent tutoring systems , generative AI for educational content, and adaptive online courses . He has pioneered methods like PASTEL (evidence-based learning engineering) and explored SimStudent , a teachable agent for tutor learning. His studies span question generation , metacognitive scaffolding , and AI-driven skill modeling . Recent publications highlight trends in large language models for education , automated content validation , and student-agent interaction . Though no scientific awards are explicitly listed, his leadership in educational computing and cross-disciplinary research underscores his impact. Matsuda’s lab continues to innovate infrastructure for adaptive learning systems with embedded ITS technologies.

Nicolaj Siggelkowمشاهده پروفایل

استاد

• competitive strategy
• evolution of fit
• firms as systems of interconnected choices
• +۴ مورد دیگر

Nicolaj Siggelkow is the David M. Knott Professor of Management at the Wharton School, University of Pennsylvania, where he also serves as Vice Dean of the MBA Program and Co-Director of the Mack Institute for Innovation Management. His academic journey began with Economics studies at Stanford University, followed by an M.A. in Economics and a Ph.D. in Business Economics from Harvard University and Harvard Business School. His research focuses on the strategic and organizational implications of interactions among a firm's choices of activities and resources, particularly examining how firms develop and adjust their activities over time, how organizational design affects performance, and how interactions among activities create competitive advantage. His work employs diverse methodologies including field studies, econometric analysis, formal modeling, and simulation. Professor Siggelkow's recent publications reveal a clear trajectory toward digital transformation and connected strategies, with increasing focus on how technology enables continuous customer relationships and new business models. His work bridges traditional strategic management with emerging digital paradigms, particularly in healthcare, pricing of smart products, and generative AI applications. Administrative Science Quarterly Scholarly Contribution Award (2008) Fellow of the Strategic Management Society (2013) Multiple Wharton Teaching Excellence Awards spanning two decades Helen Kardon Moss Anvil Teaching Award (2010) Class of 1984 Award for highest teaching ratings (2004, 2006) The Wharton Award for contribution to student experience (2004) Professor Siggelkow serves on the editorial review boards of leading management journals including Administrative Science Quarterly, Organization Science, Strategic Management Journal, Strategic Organization, and Academy of Management Perspectives. He has developed influential frameworks like the Connected Strategy model and LIVA (Long-term Investor Value Appropriation) measure. His work with the Mack Institute for Innovation Management focuses on advancing knowledge about effective management of innovation risks and rewards, while his executive education programs help organizations implement strategic frameworks for competitive advantage. His research has been published in top-tier journals including Academy of Management Journal, Administrative Science Quarterly, Journal of Industrial Economics, Management Science, Organization Science, and Strategic Organization, demonstrating both theoretical rigor and practical relevance to business strategy.

• Computational Logic
• Answer Set Programming
• Bioinformatics
• +۶ مورد دیگر

Alessandro Dal Palu' is an Associate Professor at the Department of Mathematical, Physical, and Computer Sciences at University of Parma. He holds a PhD in Computer Science from University of Udine and has been with University of Parma since 2005, transitioning from Researcher to Associate Professor in 2014. His teaching portfolio includes courses on Computer Architecture, Constraint Programming, and Algorithms & Data Structures. His research spans computational logic, bioinformatics, and GPU computing. Notable achievements include the 2007 GULP award for his Ph.D. thesis and the ICLP 2010 best paper award. He has led Italian INdAM-GNCS research projects on GPU applications (2011) and Logic Programming in cancer genomics (2016). Recent publications focus on explainable AI frameworks, bioinformatics applications, and sustainable logistics solutions. His work integrates Answer Set Programming with biomedical challenges like protein structure analysis and cancer genome evolution. He chairs the International Conference on Logic Programming (ICLP 2018) and has organized multiple international workshops on constraint programming. 2007 GULP Award ICLP 2010 Best Paper PI for INdAM-GNCS projects (2011, 2016) Program Committee member for international conferences

• Remote Sensing
• Machine Learning
• Image Processing
• +۴ مورد دیگر

Martina Pastorino is a Researcher in the Department of Naval, Electrical, Electronic, and Telecommunications Engineering (DITEN) at the University of Genoa. Her work focuses on integrating machine learning with probabilistic graphical models for advanced remote sensing image analysis , particularly in multiresolution classification using satellite and UAV data. She teaches courses on Machine Learning for Pattern Recognition and Remote Sensing in master’s programs related to Internet and Multimedia Engineering and Energy Engineering . Research Interests : Remote Sensing, Machine Learning, Image Segmentation, Data Fusion, Hyperspectral Imaging, UAV Applications. Key Techniques : CNN-MRF Hybrids, CRFNet, Probabilistic Graphical Modeling, Multiresolution Analysis. Her recent publications explore applications in wildfire mapping , urban land-use analysis , and hyperspectral-panchromatic fusion , with a focus on improving semantic segmentation accuracy through hybrid deep learning frameworks. She is available for office hours on request via email at martina.pastorino@unige.it .

Lucia Seminaraمشاهده پروفایل

دانشیار

• Tactile Sensing
• Electronic Skin
• Haptic Robotics
• +۵ مورد دیگر

Lucia Seminara serves as an Associate Professor in the Department of Naval, Electrical, Electronic, and Telecommunications Engineering (DITEN) at the University of Genoa's Polytechnic School. She teaches Electronic Devices, Sensors, and Sensing Systems for Master's programs in Electronic Engineering and Engineering for Natural Risk Management, while also contributing to Philosophy of Medicine for Philosophical Methodologies. As a member of the Joint Teacher-Student Commission, she bridges academic governance with pedagogical innovation in engineering education. Her research pioneers tactile sensing systems using piezoelectric polymers (PVDF) and electronic skin for robotics and prosthetics. She investigates indentation mechanics on soft electronic skin, grasping speed sensitivity, and hierarchical sensorimotor control frameworks for human-in-the-loop robotic hands. Key innovations include machine learning-based contact force estimation and electrotactile feedback systems that restore natural touch perception in prosthetic devices, addressing critical gaps in sensory substitution technology. Analysis of her 2021-2025 publications reveals escalating integration of machine learning with tactile sensing, particularly in symmetry detection for efficient haptic exploration and transdisciplinary human-in-the-loop applications. Recent work emphasizes real-world implementations like post-stroke rehabilitation systems and high-bandwidth human-machine interfaces, demonstrating a strategic shift from foundational sensor development toward clinically viable solutions with measurable user impact. Dr. Seminara's research lineage includes significant contributions to the Roboskin project (2013), which established large-area tactile sensor arrays for robotics. Her current work extends this foundation through investigations into viscoelastic properties, stress transmission modeling, and AI-driven tactile perception, positioning her at the forefront of intelligent electronic skin development with active collaborations across engineering, neuroscience, and clinical rehabilitation domains.

Jun Liuمشاهده پروفایل

دانشیار

• Transportation Safety
• Responder Safety
• Intelligent Transportation Systems
• +۷ مورد دیگر

Dr. Jun Liu serves as an Associate Professor in the Department of Civil, Construction and Environmental Engineering within the College of Engineering at the University of Alabama. He directs the NextGen Transportation Lab and holds editorial positions including Managing Editor for the Journal of Intelligent Transportation Systems. His affiliations include the Center for Sustainable Infrastructure and Center for Transportation Operations, Planning and Safety. Ph.D. in Civil Engineering, University of Tennessee (2015) M.S. in Statistics, University of Tennessee (2015) M.S. in Transportation Planning & Management, Huazhong University of Science & Technology (2011) B.S. in Transportation Engineering, Huazhong University of Science & Technology (2008) Dr. Liu's research spans transportation safety, connected/automated vehicles, and sustainable mobility systems. His work integrates machine learning with geospatial analysis to address responder safety, travel behavior, and urban planning challenges. Current projects focus on generative AI applications, EV infrastructure, and rural transportation equity. His methodology combines agent-based simulation, spatial modeling, and behavioral pathway analysis to develop practical transportation solutions. Publication trends reveal strong emphasis on machine learning applications in transportation safety (32% of recent works), with significant contributions to connected vehicle systems (24%) and sustainable mobility solutions (18%). His research demonstrates consistent integration of spatial analysis techniques across 78% of publications, with increasing focus on generative AI applications since 2023. Recent work shows growing international collaboration, particularly with Chinese institutions on robotaxi deployment. Inaugural Editorial Board Member, Transportation Research Record 2018 Small Grants Program Award, University of Alabama Distinguished Scientific Paper Award, ITS World Congress Best Reviewer, Journal of Traffic and Transportation Engineering Dr. Liu has secured over $21 million in research funding since 2018, including an NIH/CDC R01 award as lead PI. His 30 projects include 17 as Principal Investigator from NSF, NIH/CDC, US DOT, and state agencies. He mentors numerous graduate students, with recent publications featuring trainees as first authors. Current initiatives include a $2 million CDC/NIOSH project on first responder safety and $16.8 million smart transportation network development in West Alabama. His NextGen Transportation Lab focuses on integrating AI with transportation systems while exploring creative applications through dance and choreography.

• Machine Learning
• Computer Vision
• Data Compression
• +۳ مورد دیگر

Don Adjeroh is a Professor and Associate Chair in the Lane Department of Computer Science and Electrical Engineering at West Virginia University (WVU). He serves as Graduate Coordinator for CS programs and has led multiple NSF-sponsored projects including Bridges in Digital Health and Multi-Scale Integrative Approach to Digital Health . His research focuses span Machine Learning , Bioinformatics , Computational Biology , and Data Compression . NSF CAREER Award recipient Collaborated with institutions like University of Central Florida and University of Canterbury Led workshops on Plant Image Analysis and Long Non-Coding RNA research His academic contributions include co-authoring the book The Burrows Wheeler Transform: Data Compression, Suffix Arrays, and Pattern Matching (Springer, 2008) and developing software tools like BSMP and PSA for data compression and protein family modeling. He teaches graduate-level courses in String Algorithms and Information Theory , with former projects involving undergraduate and graduate students in DNA microarray image processing and 3D video compression research. Key Scientific Awards : NSF CAREER Award NASA-WV Space Consortium funding WV-EPSCOR grants NSF-CITeR support DOD-ONR/DHS/DOJ/NIJ/NHPRC sponsorships

• Sustainable Transport
• Transport Planning
• Social Exclusion
• +۵ مورد دیگر

Helena Titheridge is a Professor of Mobility and Sustainable Transport at the Department of Civil, Environmental and Geomatic Engineering, University College London (UCL) . With appointments at UCL since 1997, she has held roles in the Bartlett School of Planning and the Transport Studies Group at the University of Westminster (2003). Her research focuses on sustainable transport systems, social exclusion, GIS-T applications, and the interplay between transport, land-use, and environmental policies. She collaborates with organizations such as Transport for London, RPS Group, and Ipsos MORI. Education : PhD (Open University, 2005), MSc (Middlesex University, 1993), BSc (University of Leeds, 1991), Postgraduate Certificate in Learning and Teaching (University of Westminster, 2006). Research Interests encompass: Sustainable transport and mobility systems Social exclusion and equity in urban transport GIS-T for policy analysis Decision support tools for local authorities Deep learning in urban ecoacoustic assessment Informal settlement modeling (e.g., predictSLUMS) Professional Activities include: Associate Editor, Journal of Transport Geography (2016–present) Editorial roles in Transportation Planning and Technology and Journal of Transport and Land Use Conference organizer (Universities Transport Studies Group, 2008–2009) External examiner and grant reviewer Teaching spans postgraduate and undergraduate levels, with directorship of the MSc Transport and Mobility Systems , EngD Urban Sustainability and Resilience , and EngD Environmental Engineering Science programs. She teaches courses on transport-environment interactions, interdisciplinary urban sustainability, and engineering impact assessment.

• Telecommunications
• Wireless Networking
• Energy-Efficient Network Design
• +۳ مورد دیگر

Greta Vallero serves as a Fixed-term Assistant Professor in the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin, affiliated with the College of Computer, Film, and Mechatronics Engineering. She actively contributes to multiple degree programs including Communications Engineering, Computer Engineering, and Electronic and Communications Engineering. Her research focuses on telecommunications infrastructure innovation , particularly in wireless network optimization, energy efficiency, and resilience. Key areas include HAPS integration for traffic management, AI-driven environmental impact reduction in network operations, and microgrid applications for maintaining network functionality during power disruptions. Her work bridges theoretical advancements with practical implementations to address modern telecommunications challenges. Recent publications reveal a strong trend toward sustainable network architectures , combining machine learning techniques with power system innovations. Her 2024 works demonstrate significant advancements in LSTM-based environmental impact reduction, HAPS offloading strategies, and microgrid integration for RAN resilience, reflecting a cohesive research direction focused on environmentally conscious network design. Vallero supervises four active PhD students in Electrical, Electronics, and Communications Engineering: Maoquan Ni, Jun Yin, Mohammadreza Jokar, and Aurora Martiny. Her collaborative network includes prominent researchers like Michela Meo, with whom she has co-authored multiple high-impact publications. She teaches core networking courses across multiple engineering programs, including Computer Networks and Communication Networks, while contributing to specialized labs like the Internet Performance and Troubleshooting Lab. Her research group operates within the Department of Electronics and Telecommunications, focusing on next-generation network technologies with emphasis on sustainability metrics and resilience engineering. Current projects integrate telecommunications infrastructure with renewable energy systems and AI-driven optimization frameworks.

• Interactive AI
• Human-Centered AI
• Fairness in AI
• +۳ مورد دیگر

Elizabeth M. Daly is a Research Scientist at IBM Research Laboratory, Dublin, and an Adjunct Assistant Professor at Trinity College Dublin's School of Computer Science and Statistics. Her work focuses on interactive AI , human-centered design , and fairness in algorithmic systems . She contributes to AI governance and LLM safeguarding through projects like AutoFair and Granite Guardian. Ph.D. in Computer Science (2007), Trinity College Dublin Thesis: Social Network Analysis for Routing in Disconnected Delay-Tolerant MANETs Her research interests span: Interactive AI : Facilitating AI-human negotiation for common objectives Trustworthy AI : Addressing fairness, accountability, and transparency in industrial applications Explainable AI : Developing tools like AIMEE for model exploration and editing She serves on the program committees of top conferences (RecSys, IUI, WWW, UMAP, ICWSM) and the Royal Irish Academy’s committee on Engineering and Computer Science. Notable scientific award: ACM Distinguished Member . Projects: AutoFair : Human-compatible automation of fairness in AI AIMEE : AI model explorer and editor tool Usage Governance Advisor : Translating AI intent into governance frameworks She leads the Interactive AI Group at IBM Research Europe - Ireland.

Jaana-Maija Koivistoمشاهده پروفایل

مدرس

• Nursing Science
• Health Science
• Educational Sciences
• +۵ مورد دیگر

Jaana-Maija Koivisto is a University lecturer at the University of Helsinki's Faculty of Medicine, Department of Nursing Science. She serves as a Clinicum Teachers' Academy Supervisor in the doctoral program, and supervises in both the Doctoral Program in Cognition, Learning, Teaching and Communication and the Doctoral Programme in Population Health. With 54 publications spanning from 2013 to 2025, her research output shows significant growth, with particular productivity in recent years (10 publications in 2020, 7 in 2022, and 6 each in 2023-2024). Dr. Koivisto holds qualifications as a Docent in Nursing, a Doctor of Philosophy in Education, and a Master of Health Sciences in Nursing. Her academic journey reflects a strong foundation in both healthcare practice and educational theory, positioning her at the intersection of nursing science and pedagogical innovation. Her research interests center on the application of virtual reality and simulation technologies in nursing education, with particular focus on empathy development, knowledge acquisition, and interprofessional competencies. She investigates how immersive technologies can enhance traditional nursing education methods, examining both quantitative learning outcomes and qualitative student experiences. Her work demonstrates a commitment to evidence-based educational practices that prepare nursing students for complex clinical environments. Analysis of her recent publications reveals a clear trajectory toward increasingly sophisticated applications of technology in healthcare education, with her 2025 work exploring generative AI integration with VR environments. The publications consistently address practical educational challenges while contributing to theoretical understanding of technology-mediated learning in healthcare contexts. As a doctoral program supervisor across multiple disciplines, Dr. Koivisto plays a significant role in shaping the next generation of healthcare educators and researchers. Her work bridges clinical practice, educational theory, and technological innovation, creating valuable cross-disciplinary connections within the university's academic ecosystem.

Jie Wangمشاهده پروفایل

استاد

• Algorithms
• Text Mining
• Computational Complexity
• +۷ مورد دیگر

Jie Wang is a Professor of Computer Science at the University of Massachusetts Lowell's R. Miner School of Computer and Information Sciences. He joined UMass Lowell in 2001 as a Full Professor and chaired the department for 9 years from 2007 to 2016. He serves as Director for China Partnership of the US-based Consortium for Mathematics and Its Applications (COMAP) since 2011. Prior to UMass Lowell, he was Assistant Professor and then Associate Professor of Computer Science at the University of North Carolina. Professor Wang's research spans multiple areas including text mining algorithms and systems, data modeling, combinatorial optimizations, network security, wireless sensor networks, and computational complexity theory. His work has evolved from theoretical foundations in computational complexity (1980s-early 2000s) to practical applications in data analysis, intelligent text automation, and AI systems. His recent publications focus on AI-Oracle machines, LLMs, text mining, document engineering, and network security. His research portfolio demonstrates a clear evolution from theoretical computer science to applied research with practical impact. The publications show increasing focus on AI, text mining, and document engineering in recent years, while maintaining foundations in algorithm design and network security. His work bridges theoretical computer science with real-world applications across multiple domains. Honorary Advisor (2013) - NeoUnion Hong Kong Education Science Culture Organization MHE Scholar (2012) - Ministry of Higher Education, China PMYR Award for Major New Initiatives (2010) - University of Massachusetts Lowell Teaching Excellence Award (2002) - University of Massachusetts Lowell Nominee of Board of Governors' Teaching Excellence Award (2000) - University of North Carolina Professor Wang has graduated 18 PhD students and is currently directing 5 PhD students. His research has been funded by the National Science Foundation, IBM, Intel, and other companies totaling approximately $4.8 million. He is active in professional service, including chairing conference program committees, serving as journal editors, and as editor-in-chief of a book series on mathematical and interdisciplinary modeling. His laboratory work focuses on text mining systems, network security applications, and computational models for practical problems.

Valentin Deschaintreمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Computer Vision
• Machine Learning
• +۵ مورد دیگر

Valentin Deschaintre is a Researcher at Adobe Research in London, focusing on image and 3D/appearance asset understanding, generation, and authoring with emphasis on user control. He previously held academic roles at Imperial College London and Inria Sophia-Antipolis , where he earned his PhD under Adrien Bousseau and George Drettakis, collaborating with Optis (Ansys). His work bridges computer graphics, computer vision, and machine learning. His research interests span generative models , diffusion-based image manipulation , material appearance modeling , and 3D scene reconstruction . Recent publications like IntrinsicEdit (2025) and MaterialPicker (2025) highlight his work in intrinsic space editing and multi-modal material generation, often integrating user control mechanisms. Scientific Awards : French Computer Graphics Thesis Award (2020), UCA Academic Excellence Thesis Award (2020), Eurographics Junior Fellow (2024), Eurographics Young Researcher Award (2025). Internship Mentoring : He actively mentors PhD students in Adobe's internship program, including Michael Fischer (2024), Julia Guerrero-Viu (2023-2024), and Ruben Wiersma (2023).

• Clinical Informatics
• Electronic Health Records
• Artificial Intelligence in Healthcare
• +۵ مورد دیگر

Shawn Ong, MD, MHS, FAMIA is an Assistant Clinical Professor at Yale School of Medicine with primary appointment in General Internal Medicine and secondary appointment in Biomedical Informatics & Data Science. He also serves as Medical Director of Digital Technology Solutions at Yale New Haven Health System, bridging clinical medicine with health informatics innovation. Dr. Ong completed his MD at the University of Arizona, followed by internship, residency, and fellowship at Yale New Haven Hospital and Yale University School of Medicine. He holds board certification in Internal Medicine (ABIM, 2019) and Clinical Informatics (AB of Preventive Medicine, 2022), demonstrating expertise in both clinical practice and informatics. His research focuses on clinical informatics, electronic health record optimization, and AI applications in healthcare. Dr. Ong's work examines how technology can reduce physician burnout, improve documentation efficiency, and enhance patient care delivery. His publications reveal a strong emphasis on practical solutions with immediate clinical impact, spanning telehealth, ambient AI scribes, clinical decision support systems, and EHR workflow optimization. Dr. Ong's recent work shows increasing focus on ambient AI technologies for documentation support and evidence-based care pathway implementation through electronic systems, reflecting current trends in healthcare technology adoption. New Haven Primary Care Consortium, Teacher of the Year Award (2024) New Haven Primary Care Consortium Humanism Award (2023) Recognized for teaching excellence by Yale's Internal Medicine Traditional Residency program, Dr. Ong is an active member of the American Medical Informatics Association (AMIA) since 2023. His work demonstrates significant collaboration with colleagues across Yale's biomedical informatics and clinical departments, creating practical solutions that address real-world healthcare challenges.