جستجوی استاد راهنمای دانشگاهی

Olli Seppänen serves as Associate Professor in Civil Engineering at Aalto University's School of Engineering, specializing in operations management for construction productivity improvement. He coordinates the Vision 2030 consortium—comprising 13 Finnish construction and design firms—to develop industrialized building methods for 2030, while leading multiple Business Finland-funded research initiatives focused on digital construction workflows and real-time monitoring. His research centers on lean construction principles, location-based management systems, and digital transformation through IoT, AI, and robotic vision. Key focus areas include prefabrication optimization, construction logistics, and shifting work off-site to industrialize processes. He aims to solve industry-wide productivity challenges by creating real-time situational awareness and implementing takt production systems for workflow stability. Recent publications (2024-2025) reveal strong emphasis on digital twin frameworks, semantic modeling for quality assurance, and AI applications in risk management. His work bridges theoretical lean construction concepts with practical implementations, particularly in real-time resource tracking, waste reduction in MEP work, and cross-sector learning from high-performing teams. Seppänen has received significant recognition including: School of Engineering doctoral dissertation award (2024) Best paper at IEEE Wireless Sensors Conference (2019) Nordic Conference best paper award for PhD research (2019) DSc dissertation award (2010) As principal investigator, he manages: Vision 2030 consortium projects (2-3 annually; PI for two current projects) iCONS: Real-time resource flow monitoring via indoor positioning RECAP: Deep learning analysis of progress/quality from images/point clouds DiCtion: Integrated data systems for real-time stakeholder situation pictures He actively contributes to the "Performance in Building Design and Construction" research group and leverages the Vision 2030 consortium as a collaborative platform for industry transformation, driving adoption of digitalized, industrialized construction methods through academic-industry partnerships.

• Lean Construction
• Real-time Production Control
• Location Based Management Systems
• +۷ مورد دیگر

Keenan Albee is a Robotics Technologist at NASA’s Jet Propulsion Laboratory and an incoming Assistant Professor at the University of Southern California (starting Fall 2025). His research focuses on autonomous robotics for extreme environments including lunar missions, microgravity, and underwater operations. Education: Ph.D. in Aeronautics and Astronautics (Autonomous Systems), MIT (2022) S.M. in Aeronautics and Astronautics, MIT (2019) B.S. in Mechanical Engineering, Columbia University (2017) Albee’s work integrates optimal control , reinforcement learning , and motion planning to develop autonomy for mobile robotic systems operating under uncertainty. His expertise spans space robotics , microgravity systems , and underwater robotics , with a focus on environment-aware algorithm design. Recent research includes parametric information-aware motion planning (RATTLE algorithm), distributed multi-agent exploration, and robust control for uncooperative targets. His publications highlight on-orbit validation of autonomy algorithms via NASA’s Astrobee platform and upcoming lunar missions. Scientific Awards: NASA Space Technology Research Fellowship (2022) Albee actively develops open-source autonomy frameworks and will establish the Laboratory for Autonomous Systems in Exploration and Robotics (LASER) at USC. His work bridges theoretical control methods with real-world deployment, including first-of-its-kind achievements in space robotics.

• Robotic Motion Planning
• Autonomous Systems
• Optimal Control
• +۵ مورد دیگر

Professor Hossein Rahmani serves at the School of Computing and Communications , Lancaster University , with a focus on Computer Vision and Machine Learning . His career spans institutions like the University of Western Australia (PhD), Shahid Beheshti University (MSc), and Isfahan University of Technology (BSc). Research Interests : Computer Vision, Machine Learning, Video Analysis, Action Recognition/Detection, Object/Human Pose Estimation, 3D Reconstruction, Diffusion Models, Human-Object Interaction Editorial Roles : Associate Editor for IEEE Transactions on Neural Networks and Learning Systems , Pattern Recognition , ACM Computing Surveys ; Area Chair for CVPR 2025, ICLR 2025, ECCV 2024, IJCAI 2024 His recent work leverages diffusion models for domain-generalized object pose estimation, 3D scene editing, and human mesh recovery, published in top venues like TPAMI , CVPR , ICCV , and ECCV . He received the Best Scientific Paper Award from the International Conference on Pattern Recognition and actively supervises 5 PhD students with interdisciplinary projects in digital health and data science.

• Computer Vision
• Machine Learning
• Video Analysis
• +۵ مورد دیگر

Prof. Dr. Norbert Sewald, Chair of Organic and Bioorganic Chemistry at Bielefeld University, is a leading figure in Bioorganic Chemistry , Chemical Biology , and Enzymatic Halogenation . As head of the Organic and Bioorganic Chemistry Group at the Center for Biotechnology (CeBiTec), he drives research on natural products and drug conjugates. Full Professor, Bielefeld University (since 1999) Founding Coordinator, International Graduate School of Chemistry and Biochemistry (2001-2003) Chairman, Institute of Biochemistry and Bioengineering at CeBiTec (2006-2008) Dean, Department of Chemistry (2008-2011) Chairman, Max-Bergmann-Kreis e.V. (since 2010) Coordinator, Marie Skłodowska-Curie Training Networks (MAGICBULLET, 2015-2018; Magicbullet::reloaded, 2020-2023) His research focuses on halogenases for mild peptide bromination, cryptophycin-based tumor targeting , and bioactive natural products from African flora. Collaborative projects span antiplasmodial agents , antibacterial compounds , and neurodegenerative disease inhibitors . Recent work highlights include: Enzymatic halogenation cascades Click-to-release drug conjugates Fluorescent probes for amyloid detection Key affiliations: Faculty of Chemistry Center for Biotechnology (CeBiTec) European Peptide Society (Scientific Affairs Officer, 2016-) Leibniz Institute of Plant Biochemistry (Scientific Advisory Board, 2010-2017)

• Bioorganic Chemistry
• Chemical Biology
• Organic Chemistry
• +۵ مورد دیگر

Dr. Arnold Japutra is an Associate Professor of Marketing at Southampton Business School, University of Southampton. His research focuses on brand management, consumer behaviour, relationship marketing, and the adoption of emerging technologies such as AI, AR/VR, and robotics. Recognized among the Top 2% of Global Scientists, he has published in leading journals including the Journal of Business Research, European Journal of Marketing, International Marketing Review, Journal of International Management, Journal of Travel Research and Tourism Management. Dr. Japutra has held academic roles at the University of Western Australia and Universitas Indonesia, and has extensive experience in teaching, corporate training, and consulting for global organizations. His research interests include: Consumer-brand relationships Consumer negative behaviours Dark-side of brands Human-Robot interactions Adoption of new technologies (e.g., AI, AR, VR) Brand management (e.g., brand attachment, brand loyalty, brand equity) Technology adoption and consumer behaviour (e.g., impulsive and compulsive buying) Dr. Japutra's research sits at the intersection of branding, consumer psychology, and emerging technologies. His work examines how consumer–brand relationship factors drive both positive behaviors and negative ones such as impulsive buying, compulsive consumption, and trash-talking. He investigates how psychological traits shape consumer decision-making and has recently been exploring human-technology interactions with a focus on AI, robotics, AR, and VR. His publication pattern shows a clear evolution from traditional brand management topics toward increasingly technology-focused research, particularly examining the psychological impacts of AI and digital interfaces on consumer behavior. Dr. Japutra has received numerous prestigious awards, including: Stanford 2% Global Scientist Citation Rankings (2023, 2024) Business School Mid-Career Research Award, University of Western Australia (2023) Best Researcher Award, Faculty of Economics and Business, Universitas Indonesia (2023, 2022) Best paper at Journal of Hospitality and Tourism Management (2019) Best Researcher Award and Top Publication Award, Tarumanagara University (2016) Dr. Japutra is actively accepting PhD students and has extensive experience mentoring graduate researchers. His research has been supported by various grants though specific funding sources aren't detailed in the provided materials. He has also delivered corporate training and consulting services for numerous global organizations, bridging academic research with practical business applications.

• Consumer-brand relationships
• Consumer negative behaviours
• Dark-side of brands
• +۷ مورد دیگر

Sophie Caron is an Associate Professor in the Department of Biological Sciences at the University of Utah, where she leads a research laboratory investigating fundamental mechanisms of brain function using Drosophila melanogaster as a model system. Her work focuses on how the brain generates internal representations of the external world, stores memories, and translates these into behavior through multisensory integration. Education: B.S. from Université de Montréal Ph.D. from New York University Dr. Caron's research centers on the Drosophila mushroom body—a critical brain center for learning and memory—with emphasis on multisensory integration mechanisms. Her lab investigates how the brain combines information from multiple sensory modalities (olfaction, vision, etc.) to form unified percepts, challenging traditional views of sensory processing. Key discoveries include the demonstration that mushroom body connectivity follows near-random patterns that maximize memory capacity, and the identification of cross-modal sensory pathways beyond olfaction. Current work explores evolutionary adaptations in neural circuits across Drosophila species and developmental mechanisms establishing sensory wiring. Analysis of her 15 most recent publications (2019-2024) reveals three dominant research trajectories: (1) high-resolution mapping of Kenyon cell inputs using advanced techniques like dye electroporation, (2) computational modeling of how connectivity patterns shape sensory representation and learning, and (3) evolutionary studies of circuit architecture across Drosophila species. Her work consistently bridges experimental neuroanatomy with theoretical frameworks, emphasizing the interplay between random and structured wiring principles in neural circuit design. Scientific Awards: NSF CAREER Award (2021) for research on brain size evolution and neuronal circuit adaptation Dr. Caron mentors graduate students in the University of Utah's Molecular Biology Program and directs an active laboratory utilizing genetic, imaging, and behavioral approaches. Her research program is supported by competitive grants including the NSF CAREER award, with collaborations spanning neuroscience and evolutionary biology. Current projects investigate multisensory integration mechanisms, evolutionary drivers of neural circuit specialization, and developmental basis of sensory wiring. The Caron Lab maintains specialized facilities for Drosophila neurogenetics, advanced microscopy, and behavioral analysis. Her team collaborates with the University of Utah's Brain Institute and Center for Cell and Genome Science, contributing to interdisciplinary initiatives in neural circuit mapping and evolutionary neuroscience. Ongoing work explores how sensory representations evolve in response to ecological pressures and how circuit architecture enables flexible behavior in complex environments.

• Neuroscience
• Neurobiology
• Sensory Systems
• +۵ مورد دیگر

Neda Haj Hosseini is a Senior Lecturer and Associate Professor in Biomedical Engineering at Linköping University's Department of Biomedical Engineering (IMT) . She contributes to teaching courses like TBMT56 - Medical Technology and TBME08 - Biomedical Modeling and Simulation , while leading research initiatives in AI-driven cancer diagnostics and biomedical optics. Research Focus: Development of AI methods for cancer diagnostics, optical coherence tomography (OCT) applications, and fluorescence spectroscopy in surgical guidance Affiliations: Center for Medical Image Science and Visualization (CMIV) , Analytic Imaging Diagnostic Arena (AIDA) , Swedish Medical Technology Association Recent Research Trends demonstrate expertise in applying deep learning to: Pediatric brain tumor classification using multimodal imaging Optical biopsy techniques for intraoperative decision support Automated biomarker quantification in histopathology Medical imaging data integrity and algorithm validation Scientific Awards include grants from: Joanna Cocozza Foundation (2022) Swedish Childhood Cancer Foundation (2024) Academic Leadership involves mentoring students in projects such as: "Multiple Instance Attention-based Learning for Brain Tumor Classification" "Vision Transformers for Multiclass Brain Tumor Tissue Classification" "Reaction-diffusion Models for Image-driven Tumor Simulation"

• Biomedical Engineering
• Medical Imaging
• Artificial Intelligence in Healthcare
• +۳ مورد دیگر

Arnav Arora is a PhD Fellow at the Department of Computer Science , University of Copenhagen (DIKU), specializing in Natural Language Processing . His work focuses on ethical AI, bias detection, and societal impacts of language models. Email: aar@di.ku.dk Location: Universitetsparken 1, 2100 København Ø Arnav's research explores fine-grained value alignment in language models, harmful content detection , and cross-cultural differences in AI responses. His work bridges technical NLP advancements with social responsibility, including dual use ethical frameworks and community value analysis . Key publication trends include: 2025: Bias mitigation through BiasGym framework 2024: Factcheck-Bench benchmark development 2023: Thorny Roses dual use analysis 2022: Cross-cultural value probing methods 2020: Multi-hop fact checking systems Arnav contributes to the Software, Data, People & Society (SDPS) section, collaborating with interdisciplinary teams on projects involving language model evaluation and societal impact mitigation . His work often addresses real-world AI deployment challenges through academic-industry partnerships.

• Natural Language Processing
• Machine Learning
• AI Ethics
• +۵ مورد دیگر

Prof. Dr. Matthias Weidlich is a faculty member at Humboldt University of Berlin within the Institute of Computer Science under the Faculty of Mathematics and Natural Sciences . His research focuses on Process Mining , Complex Event Processing , and Data Privacy with applications in Business Process Management and Scientific Workflows . Research Interests: Business Process Management and Process Mining Complex Event Processing and Stream Data Analysis Data Privacy and Security in Process Systems Scientific Workflow Systems and User Behavior Heterogeneous Network Embeddings Algorithm Design and Optimization Recent Publications (2023-2025) demonstrate expertise in: Efficient stream processing techniques Privacy-preserving process mining frameworks Scientific workflow analysis tools Graph neural network applications Multi-modal data integration Adaptive querying systems Contact: Office: Unter den Linden 6, 10099 Berlin Phone: 030 2093-41277 Email: matthias.weidlich@hu-berlin.de Web: hu.berlin/data

• Business Process Management
• Process Mining
• Complex Event Processing
• +۵ مورد دیگر

Benedikt Warth is a Full Professor for Food Chemistry and Exposome Research at the Department of Food Chemistry and Toxicology, Faculty of Chemistry, University of Vienna (since 2022). He coordinates the Austrian node of the ESFRI research infrastructure EIRENE and leads the 'Global Exposomics and Biomonitoring Laboratory' since 2017. His work bridges chemistry and toxicology, focusing on exposomics and metabolomics to assess chemical exposure and its health impacts. Education: PhD in Analytical Chemistry (2012), Master’s in Biotechnology (2009), Bachelor’s in Food Science and Biotechnology (2007) Research interests center on exposomics , metabolomics , and analytical chemistry , particularly for environmental and food-related toxicants. Recent articles highlight advancements in mass spectrometry for exposome-scale analysis, combining targeted and non-targeted approaches, and exploring chemical interactions (e.g., xenoestrogens, mycotoxins, flame retardants) in biological systems. Key trends in his publications include: Development of hybrid LC-MS methods (targeted/untargeted) for sensitive exposomics Integration of AI and cognitive computing for pathway analysis Global biomonitoring of mycotoxins and xenobiotics in vulnerable populations Standardization frameworks for non-targeted analysis (SRT) Notable awards include the 2025 Chemical Research in Toxicology Young Investigator Award , Brigitte Gedek-Science Award , and multiple grants (ERC Consolidator, Erwin-Schrödinger Fellowship). He has delivered over 20 invited talks on exposomics, including sessions at ACS Fall Meetings and international conferences. His laboratory's projects span: Breast cancer exposomics (linking environmental exposures to disease onset) High-throughput sample preparation for exposome-wide studies Systems toxicology of chemical mixtures (e.g., flame retardants, mycotoxins) Development of global metabolomic assays for toxicity prediction

• Exposomics
• Metabolomics
• Analytical Chemistry
• +۴ مورد دیگر

Summary Luis A. Duffaut Espinosa is an Assistant Professor in the Department of Electrical and Biomedical Engineering at the University of Vermont (UVM), affiliated with the College of Engineering and Mathematical Sciences. His research focuses on control theory, estimation, robotics, and nonlinear systems with applications in autonomy, quantum control, and environmental monitoring. He holds a Ph.D. in Electrical and Computer Engineering from Old Dominion University (2009) and has held academic positions at George Mason University and postdoctoral roles at Johns Hopkins University and the University of New South Wales. Education: Ph.D. in Electrical and Computer Engineering (2009), Old Dominion University M.S. in Mathematics (2005), Pontificia Universidad Católica del Perú B.S. in Physics (2003), Universidad Nacional de Ingeniería, Peru Research Interests: His work emphasizes data-driven control and estimation methodologies, including model-free approaches for power systems, environmental monitoring, and quantum control. Current projects include real-time data assimilation in harsh environments, resilient robotics in GPS-denied conditions, and SAR with small satellites. He co-directs the Autonomous and Intelligent Systems Research Laboratory (AIRLab) and is part of the CREATE center. Recognition: 2024 NSF CAREER Award for work on safety-aware data-driven control frameworks Teaching & Advising: He teaches courses in estimation theory, control systems, and signal processing. Advises a team of graduate and undergraduate students focusing on autonomy, robotics, and control systems. Notable students include Danial Waleed (Ph.D. 2024), Jacob Friz-Trillo (M.S. 2025), and Farnaz Boudaghi (Ph.D. candidate). Labs & Collaborations: AIRLab: Focuses on data-driven control for autonomy in robotics and engineered systems CREATE: Research on resilient energy and autonomous technologies

• Control Theory
• Estimation Theory
• Robotics
• +۷ مورد دیگر

Dr. Carsten Nowak serves as Head of Conservation Genetics at the Senckenberg Research Institute and Natural History Museum Frankfurt, where he leads the national reference center for genetic analyses of wolves and lynx. His work bridges cutting-edge molecular methods with practical conservation applications, focusing on wildlife monitoring and species preservation. Since 2010, his laboratory has been responsible for central examination of all samples collected through Germany's nationwide wolf and lynx monitoring programs. Nowak's research interests center on developing highly sensitive molecular marker systems for wildlife monitoring, with particular expertise in environmental DNA (eDNA) methods and SNP chips optimized for genotyping forensic and non-invasively collected environmental samples. His work addresses critical questions in conservation biology, including inbreeding, genetic impoverishment, population origins, and human environmental impacts on genetic population structures of native species. He investigates how genetic methods can clarify previously unanswered questions in nature conservation, where data limitations often hinder efficient and targeted conservation measures. His extensive publication record (2023-2025) reveals a strong focus on wolf population dynamics across Europe, hybridization detection methodologies, and conservation genomics of endangered species like the garden dormouse. Nowak's research demonstrates sophisticated approaches to tracking animal movements across national borders, assessing genetic diversity in recovering populations, and developing practical tools for non-invasive wildlife monitoring. His work on wolf-dog hybridization has particular policy relevance as wolf populations expand across Europe. As a public-facing scientist, Nowak regularly engages with policymakers and the public through presentations, media appearances, and citizen science projects. He has participated in high-profile events including briefings for Federal Environment Minister Svenja Schulze and numerous public lectures on wildlife conservation topics. His leadership extends to coordinating international research collaborations, including the CEwolf Consortium and various transboundary monitoring networks. Nowak directs the Center for Wildlife Genetics in Gelnhausen, where his team conducts DNA-based analyses of predator-prey interactions, livestock depredation incidents, and wildlife population monitoring. His laboratory serves as the national reference center for genetic analyses of wolves and lynx in Germany, processing samples from across the country to distinguish individuals, determine relatedness, and monitor population health. The center also develops molecular methods for detecting wolf-dog hybrids and other conservation genetics applications.

• Conservation Genetics
• Wildlife Monitoring
• Environmental DNA (eDNA) Analysis
• +۵ مورد دیگر

Muhammad Asaduzzaman is an Assistant Professor in the School of Computer Science within the Faculty of Science at the University of Windsor. His research focuses on software engineering, particularly software maintenance, mining software repositories, and recommendation systems for developers. Research interests span empirical studies of software artifacts, API usage analysis, and improving developer productivity through tools like COSTER for API element identification. Recent work examines dependency management in Maven ecosystems and AI-assisted code completion. Publications show consistent focus on analyzing developer activities through platforms like Stack Overflow and GitHub. Current investigations include LLM applications for code synthesis and technical debt impact analysis.

• Software Engineering
• Mining Software Repositories
• Empirical Software Engineering
• +۲ مورد دیگر

Hayretdin Bahsi is an Assistant Professor at the School of Informatics, Computing, and Cyber Systems at Northern Arizona University . His research focuses on cybersecurity, with expertise in malware detection, IoT security, and machine learning applications in defense mechanisms. He collaborates internationally on maritime cybersecurity, healthcare systems, and critical infrastructure protection. Research Interests include Android malware analysis, botnet detection, explainable AI in intrusion detection, and threat modeling for AI-driven systems. His work addresses challenges like concept drift in malware detection and privacy-preserving techniques for IoT networks. Publications span 66 scholarly works since 2009, emphasizing cybersecurity trends in AI, IoT, and healthcare. Recent contributions explore large language model (LLM) applications in vulnerability detection and cyber threat modeling for healthcare systems. Collaborations include projects on maritime cyber-insurance, cyber incident management in low-income countries, and datasets like MedBIoT for IoT botnet analysis. His work bridges theory and practice, addressing real-world cybersecurity challenges.

• Cybersecurity
• Malware Detection
• Machine Learning
• +۷ مورد دیگر

Dick Houtman is a Professor of Sociology at KU Leuven's Faculty of Social Sciences , leading the Centre for Culture, Conflict, and Inequalities (C3I) . He also holds a Faculty Fellow position at Yale University's Center for Cultural Sociology . His work focuses on cultural change and cultural conflict in the West since the 1960s, particularly in politics and religion , with a special interest in the Romantic turn that has transformed Western societies. Research topics: Cultural sociology, secularization, spirituality, cultural-political polarization, anti-institutionalism, and the romantic legacy in modernity. Teaching: Culture and Society specialization in KU Leuven's Master of Sociology program. Key projects include: Non-Religious Discourses and the Secularization of the Secular (2021-2025) Fashioning Ideology, Ideologizing Fashion (2020-2024) Boundaries Across Borders (2022-2023) The Implications of Religious Pluralism (2014-2025) Scientific honors : Yale University Center for Cultural Sociology Faculty Fellow Recent publications (2023-2025) show strong focus on spirituality , secularization , religious pluralism , and cultural polarization , with keywords spanning from political sociology to digital religion . His work often examines authenticity claims, the cultural significance of science, and the transformation of religious and cultural identities in contemporary societies.

• Cultural Sociology
• Religious Pluralism
• Secularization
• +۴ مورد دیگر