جست‌وجوی استاد و پژوهشگر

Ole Madsenمشاهده پروفایل

استاد

• Robotics
• Automation
• Industry 4.0
• +۶ مورد دیگر

Ole Madsen is a Professor at the Department of Materials and Production within The Faculty of Engineering and Science at Aalborg University . His research focuses on Robotics and Automation , particularly in 5G Smart Production , AI for Manufacturing , and Industry 4.0 applications. He also holds a part-time position at Adding Robotics , applying his expertise in robot integration for industrial and healthcare settings. Research Interests : Robotics, Automation, AI, Sensor Systems, Modular Manufacturing, Welding Technology, Digital Twins, Human-Centered Robotics, Industry 4.0 His work spans 35+ years with over 205 publications , emphasizing smart production systems and robot-assisted processes . Key contributions include Swarm Production Architectures , 5G-Enabled Robotics , and Human-Robot Collaboration frameworks. He has supervised 10 PhD students and led major projects like RAU (Robot-Assisted Ultrasound) and GINP: Robotics & AI Innovation Network . Scientific Awards : SCAP2020 Best Presentation Award (2020) Ole's 31 projects include AP2030: Aseptic Factory 2030 (pharma production), AddSmart (robotics R&D), and 5G-Enabled Autonomous Systems . His 127 press/media mentions highlight advancements in robotic welding , industrial metaverse , and swarm production . He maintains an ORCID: 0000-0003-2133-2541 with extensive publication records across Swarm Robotics , Modular Manufacturing , and AI-Driven Production .

• Computational Biology
• Gene Expression Analysis
• Schizophrenia Research
• +۵ مورد دیگر

Tade Souaiaia serves as Assistant Professor of Cell Biology at SUNY Downstate Health Sciences University's School of Graduate Studies. His research integrates computational biology with mental health investigations, focusing on gene expression dynamics in development and psychiatric disorders. He teaches graduate-level statistics and algorithm analysis courses delivered virtually via YouTube. Dr. Souaiaia's primary research centers on computational method development for multi-omics integration (gene expression, isoform-level data, microRNA, ChIP-Seq) to unravel schizophrenia etiology. His secondary research applies kinematic modeling to athletic performance (sprint/long jump), connecting cellular mechanisms with environmental training models. This dual focus bridges molecular neuroscience with practical biomechanics applications. Analysis of his 2020-2025 publications reveals three dominant research trajectories: (1) Psychiatric genetics through multi-ancestry studies of autism/schizophrenia, (2) Polygenic risk score innovation (notably BridgePRS for cross-ancestry portability), and (3) Primate neurogenomics investigating anxious temperament via orbitofrontal cortex and amygdala transcriptomics. His work consistently emphasizes translational applications of computational genomics to mental health. No scientific awards were documented in the provided materials. Dr. Souaiaia teaches Scientific Computing in Python (GRSC 6974) and Graduate Statistics (GRSC 0120), with virtual instruction accessible on YouTube. While specific grant details and student advising records are unreported, his laboratory actively develops computational frameworks for psychiatric genomics. His research program demonstrates strong interdisciplinary collaboration between neuroscience, psychiatry, and bioinformatics teams. He leads a research laboratory specializing in computational analysis of multi-omics datasets, with particular emphasis on primate brain tissue studies. The lab develops novel algorithms for integrating genomic, transcriptomic, and epigenomic data to model mental health disorders, maintaining active partnerships with neuroscience and clinical psychiatry research groups.

• Database Systems
• Distributed Data Management
• Concurrency Control
• +۵ مورد دیگر

Alan D. Fekete is a Professor at the University of Sydney's Department of Computer Science, specializing in database systems, distributed data management, and consistency models. His work spans transaction processing, cloud computing, and query optimization, with recent focus on enhancing database concurrency and serializable execution. Key Research Areas: Database Concurrency & Transaction Isolation Multicore Scalability & Distributed Systems Cloud Data Consistency & Replication Query Optimization & NoSQL Performance Recent publications (2023-2025) explore transactional frameworks for analytical interfaces, DB-OS co-design for data ingestion, and mixed isolation levels for serializable execution. Earlier works (2018-2014) address scalable lock managers, coordination avoidance in databases, and consistency properties in cloud storage. He has contributed to educational initiatives, including a data-centric computing curriculum (2021) and teaching threading concepts (2008). Collaborations include co-authors like Nancy Lynch, Uwe Röhm, and Joseph Hellerstein.

• Quaternary geology
• glacial geology
• paleoclimatology
• +۵ مورد دیگر

Jason P. Briner is a Professor in the Department of Geology at the State University of New York at Buffalo, affiliated with the College of Arts and Sciences. His research focuses on Quaternary and glacial geology, paleoclimatology, and arctic environmental change. Education Ph.D. in Geological Sciences, University of Colorado (2003) M.S. in Geology, Utah State University (1998) B.S. in Geological Sciences, University of Washington (1996) Briner studies glacial and lacustrine records to understand ice sheet processes, past climate changes, and glacial landscape evolution using cosmogenic exposure dating and paleolimnologic techniques. His work provides insights into Arctic climate change over Pleistocene and Holocene timescales. His recent research involves developing open-source tools through Ghub for ice sheet modeling, NSF-funded projects on climate change, and fieldwork in Alaska, Greenland, and Norway. He teaches courses including Climate Change, Glacial Geology, and Quaternary Dating Methods. Briner leads the Paleoclimate Lab at UB, mentoring graduate students and conducting fieldwork across glacial regions. He is a member of the Geological Society of America, American Quaternary Association, and American Geophysical Union.

Gwen Marchandمشاهده پروفایل

استاد

• Educational Psychology
• Student Motivation and Engagement
• Mixed-Methods Research
• +۳ مورد دیگر

Gwen Marchand, Ph.D. is the Associate Vice President for Research and a Professor of Educational Psychology at the University of Nevada, Las Vegas (UNLV) . She formerly served as Associate Dean of Research and Sponsored Projects in the UNLV College of Education and as Director of the UNLV Center for Research, Evaluation, and Assessment . Education: Ph.D. in Systems Science: Psychology, Portland State University, 2008 – emphasis in human development, student motivation & engagement, and quantitative research methods Research Interests: Professor Marchand’s scholarship applies complexity theory and mixed-methods designs to study student motivation and engagement , classroom systems , student mobility , and collaborative team processes . Her interdisciplinary work emphasizes research-practice partnerships and systems-level understanding of educational phenomena. Current focal areas include: Motivational development of school-aged children Social and personal determinants of student engagement Teacher instructional supports for motivation in science classrooms Program evaluation and evidence-based educational innovation Publications & Scholarly Impact: Across 40+ peer-reviewed works since 2004, Marchand’s research spans complex dynamic systems , mixed-methods innovations , motivational theory , and science education reform . Recent outputs (2020-2024) converge on applying systems perspectives to classroom dynamics and translating motivational theory into scalable teacher professional-development programs. Professional Service & Leadership: Program Chair & Treasurer, Division 15 (Educational Psychology), American Psychological Association (APA) Secretary/Treasurer, Complexity Theories in Education SIG, American Educational Research Association (AERA) President, Scholarly Consortium for Innovative Psychology in Education (SCIPIE) Editorial Boards: Journal of Educational Psychology , Contemporary Educational Psychology Guest Co-Editor, special issues on complex systems ( Journal of Experimental Education ) and mixed-methods ( Contemporary Educational Psychology ) Teaching & Mentoring: Marchand regularly teaches graduate courses in advanced research methods , program evaluation , motivation theory , and quantitative analyses . Her interdisciplinary mentorship spans educational psychology, systems science, and STEM education research. Administrative Oversight: Office of Sponsored Programs Office of Clinical Trials Office of Research Integrity Interdisciplinary research development initiatives and strategic planning Funding: Her research has been supported by the National Science Foundation , the National Institute of General Medical Sciences , and numerous state and local agencies, evidencing broad recognition of her expertise and translational impact.

Fang Kongمشاهده پروفایل

استادیار

• Online Learning
• Reinforcement Learning
• Machine Learning
• +۴ مورد دیگر

Fang Kong is an Assistant Professor in the Department of Statistics and Data Science at the Southern University of Science and Technology (SUSTech). He earned his PhD in Computer Science from Shanghai Jiao Tong University under the supervision of Prof. Shuai Li and received his Bachelor's degree in Software Engineering from Shandong University. Education: PhD in Computer Science, Shanghai Jiao Tong University (2020-2024) Bachelor's Degree in Software Engineering, Shandong University (2016-2020) Dr. Kong is broadly interested in developing theoretically guaranteed algorithms for sequential decision-making problems, with particular focus on multi-armed bandits and reinforcement learning, as well as their applications in online experimentation and recommendation systems. His research spans theoretical foundations of bandit algorithms, matching markets, influence maximization, and online learning under various feedback structures. He has made significant contributions to the understanding of best-of-both-worlds algorithms that perform well in both stochastic and adversarial environments. His publication record shows a strong trajectory of high-impact work in top-tier conferences including NeurIPS, ICML, ICLR, AAAI, WWW, and AAMAS. His research demonstrates expertise in theoretical machine learning with a focus on bandit algorithms, particularly in matching markets and sequential decision-making problems. His work often bridges theoretical guarantees with practical applications in recommendation systems and online experimentation. Scientific Awards: CCF Doctoral Dissertation Award in Agent and Multi-Agent Systems (2025) Baidu Scholarship (2024) National Scholarship for PhD students (2023, 2022) AAMAS Student Scholarship (2023) Microsoft Research Asia Excellence Award (2022) Dr. Kong actively mentors students at various levels, including PhD and Master's students at SUSTech, visiting students from other institutions, and undergraduate researchers. He serves as a reviewer for top machine learning conferences (ICLR, NeurIPS, ICML, WWW) and journals (IEEE PAMI, TMLR). His teaching includes graduate Machine Learning and undergraduate Artificial Intelligence courses at SUSTech.

Sébastien Fournierمشاهده پروفایل

پژوهشگر

• Aspect-Based Sentiment Analysis
• Multimodal Data Processing
• Information Retrieval
• +۶ مورد دیگر

Sébastien Fournier is a researcher affiliated with the University of Aix-Marseille, focusing on natural language processing, multimodal data analysis, and agent-based systems. He has contributed to projects like ANR GUIDANCE, ADNvideo, CoPains, and PhysSocial, emphasizing dialogue-assisted information access, video fingerprinting, persuasive health agents, and psychophysiological foundations of social behavior. Research areas: Aspect-Based Sentiment Analysis, Contradiction Detection in Reviews, Multimodal Data, Recommendation Systems Projects: ANR GUIDANCE (Workpackage 3 Leader), ADNvideo (2014-2016), CoPains (2019-2022), PhysSocial (2018-2021) His work extends to evaluating interactions in serious crisis management games, with supervision of PhD students like Ismail Badache and Adrian-Gabriel Chifu. He collaborates with institutions including LIS, LSIS, and ILCB (Institute of Language, Communication and the Brain).

• Infectious Disease Modeling
• Vector-Borne Disease Epidemiology
• Mathematical Forecasting
• +۴ مورد دیگر

Michael Johansson serves as a Research Professor at Northeastern University's Roux Institute, maintaining offices in London, UK and Portland, ME. His work bridges public health research and operational response through advanced statistical and mathematical modeling of infectious diseases, with primary focus on vector-borne pathogens including dengue, Zika, chikungunya, and West Nile virus. Previously with the CDC in Puerto Rico for over a decade, he co-founded the Epidemic Prediction Initiative and led modeling efforts during Zika, COVID-19, and dengue emergencies. His research integrates biological, ecological, climatic, socioeconomic, and behavioral factors to understand disease emergence and transmission dynamics. Key methodologies include network-based forecasting models, climate-disease interaction analysis, and development of early warning systems. Current work emphasizes improving surveillance, burden estimation, and control strategy evaluation for arboviral diseases through quantitative tools. Recent publications demonstrate expertise in dengue synchronization across the Americas, West Nile virus forecasting, and addressing biases in mobility data for outbreak modeling. His work spans from molecular-level antibody response analysis to global risk mapping, consistently emphasizing operational implementation of research findings. Johansson actively contributes to public health practice through conference presentations including the 2025 American Mosquito Control Association Annual Meeting. His modeling frameworks have directly informed CDC emergency responses and the development of collaborative forecasting initiatives that pioneer open, transparent disease prediction.

Susanna Berkouwerمشاهده پروفایل

استادیار

• Energy Economics
• Environmental Economics
• Development Economics
• +۲ مورد دیگر

Dr. Susanna Berkouwer is an Assistant Professor of Business Economics & Public Policy at the Wharton School, University of Pennsylvania. She focuses on the economics of energy and environmental policy in developing countries, with a particular emphasis on energy efficiency, grid reliability, and climate adaptation strategies. Faculty Research Fellow, National Bureau for Economic Research Coase Project Fellow Penn Environmental Innovations Initiative Fellow J-PAL and BREAD Affiliate Her educational background includes a Ph.D. in Economics from UC Berkeley (Energy Institute at Haas), an MA in International and Development Economics from Yale University, and a BSc in Statistics from University College London. Recent research highlights include analyzing transient air pollution exposure in clean cooking transitions, optimizing donor contracting for electrification projects, and addressing voltage quality improvements in Ghana's energy infrastructure. She explores behavioral economics in energy technology adoption and political economy dimensions of electrification in Kenya. Scientific recognition includes NBER affiliation and contributions to energy policy innovation. She previously held research roles at Harvard's EPoD and worked in international trade finance across London, Johannesburg, and Nairobi.

• Decision Support Systems
• Energy Management
• Sustainable Energy Planning
• +۸ مورد دیگر

Dr. Vangelis Marinakis is an Assistant Professor at the School of Electrical and Computer Engineering (ECE) of the National Technical University of Athens (NTUA). His academic background includes an Electrical and Computer Engineering degree and a PhD in Decision Support Systems for Sustainable Energy Planning from NTUA. PhD in Decision Support Systems for Sustainable Energy Planning (NTUA) Electrical and Computer Engineer (NTUA) His research focuses on designing methodologies for intelligent energy management across Smart Homes, Buildings, Cities, and Districts, leveraging technologies like IoT, AI, and Big Data. He has contributed to over 25 European (Horizon Europe, H2020) and national projects, with more than 50 journal publications and book chapters. Key research areas include Decision Support Systems , Energy Efficiency , and Renewable Energy Integration . He has led research in AI-driven energy forecasting, federated learning for privacy-preserving data models, and blockchain applications in energy markets. His work explores the intersection of Smart Grids , Building Informatics , and Climate Resilience . Dr. Marinakis has developed frameworks for: Decarbonization-as-a-Service in building renovations Scalable Big Data architectures for smart buildings Multi-criteria optimization of EV charging stations Explainable AI in energy decision-making Climate resilience assessment for urban housing

Patrick Aignerمشاهده پروفایل

مربی

• Environmental Science
• Atmospheric Modeling
• Climate Impact Assessment
• +۲ مورد دیگر

Patrick Aigner, M.Sc., is a Tutor at the Technical University of Munich , affiliated with the Professorship for Environmental Sensors and Modeling led by Prof. Jia Chen. His work focuses on urban greenhouse gas monitoring , particularly through automated measurement networks and emission inventory analysis . Research : Urban CO2/CH4 sensing, high-density sensor networks, spatial emission inventories Teaching : Tutor for Environmental Sensing and Modeling lectures and seminars Email : patrick.aigner@tum.de Research Areas include: Environmental Science : Urban climate impact assessment Atmospheric Modeling : Flux tower measurements, footprint analysis Climate Policy : Quantitative mapping of mitigation plans Air Quality Monitoring : CO/NOx co-emissions Publication Trends show collaboration across European cities (Munich, Zurich, Paris) with emphasis on high-density sensor networks , emission inventory methods , and climate verification frameworks . Key projects include ICOS Cities , MUCCnet , and SCOUT .

• Formal Methods of Software Engineering
• Operating Systems Verification
• Critical Systems Development
• +۵ مورد دیگر

Alexey Vladimirovich Khoroshilov is an Associate Professor at the Faculty of Computer Science of the National Research University Higher School of Economics (HSE), affiliated with the Basic Department "System Programming" of the Institute for System Programming named after V.P. Ivannikov of the Russian Academy of Sciences (ISP RAS). He joined HSE in 2015, bringing 20 years of scientific and teaching experience to his position. His academic background includes a Candidate of Physical and Mathematical Sciences degree (2006) and a specialty in Applied Mathematics and Computer Science from Moscow State University named after M.V. Lomonosov (2001), with the qualification of Mathematician and Systems Programmer. His primary research interests focus on formal methods of software engineering, particularly in the verification and validation of critical systems. He specializes in methods for designing and developing critical systems, formal verification techniques, model-based testing, and requirements analysis. His work has significant applications in operating systems security, real-time systems, and safety-critical software development. His recent publications demonstrate a strong focus on operating system verification, with particular emphasis on abstract model-based runtime verification, security policy integration, and multi-level requirements compliance. His research often combines theoretical formal methods with practical applications in operating system security and verification. The recurring themes across his work include component-based verification approaches, thread-modular analysis techniques, and formal modeling of security policies. Khoroshilov maintains a strong connection with the Institute for System Programming of the Russian Academy of Sciences, where he has worked since 1999 and held the position of leading research fellow as of 2014. He also teaches at Moscow State University's Department of System Programming within the Faculty of Computational Mathematics and Cybernetics since 2009. His teaching focuses on operating system development, particularly courses on the design of operating system kernels for both bachelor's and master's programs. His technical expertise includes verification of operating system components, security policy implementation, and requirements management for critical systems. He has contributed to significant projects related to aviation real-time operating systems, formal security models, and Linux kernel verification.

Paola Paciمشاهده پروفایل

دانشیار

• Computational Biology
• Bioinformatics
• Network Medicine
• +۳ مورد دیگر

Paola Paci is an Associate Professor at the Department of Computer, Control, and Management Engineering "Antonio Ruberti" of Sapienza University of Rome and an Affiliate Professor at the Department of Laboratory Medicine, Cardio-Metabolic Unit of Karolinska Institutet, Sweden. She has held visiting positions at Harvard Medical School and research roles at CNR's Institute for Systems Analysis and Computer Science. Her work bridges computational biology and network medicine. 2010: Second Level Master in Bioinformatics (Sapienza University of Rome) 2003: PhD in Physics (University of Pavia) 1999: MSc in Physics (Sapienza University of Rome) Paci develops algorithms for biomarker discovery and drug repurposing in network medicine. Her tools include SWIM for glioblastoma biomarkers, SPINNAKER for ceRNA interactions, SAveRUNNER for drug repurposing, and MIENTURNET for miRNA-target analysis. Recent work focuses on single-cell multi-omics, adverse drug effects, and pathogen spillover mechanisms. Her research spans 2025-2024 publications covering Alzheimer’s disease drug prioritization, COPD pathway analysis, obesity therapeutics avoiding hepatic steatosis, and neuroblastoma immunotherapy resistance. These works integrate network medicine with pharmacology, genomics, and systems biology. 2018: BITS Best Poster Award 2017: IEEE TCCLS Best Poster (700 USD) 2016: IEEE TCCLS Best Poster (500 USD) 2014: SYSBIO Award (10,000 EUR) 2010: Master Award (1,500 EUR) She teaches bioinformatics at Sapienza University and Campus Biomedico University, organized key IEEE workshops, directs training courses, and serves on editorial boards (Scientific Reports, Biotechnology Reports). Her affiliations include the Network Medicine Institute and GNB bioengineering society.

• Environmental Archaeology
• Coastal Geography
• Holocene Sea Levels
• +۳ مورد دیگر

Alexandra Bivolaru is a Researcher at the Department of Humanities of Ca' Foscari University of Venice . Her work focuses on interdisciplinary studies bridging archaeology, environmental science, and coastal geography. Her research examines long-term human-environment interactions in coastal lagoons, with a focus on Holocene sea-level changes, paleoenvironmental reconstruction, and climate impacts on historical ecosystems. Collaborative projects include multi-scalar analyses of sedimentological and archaeological data from the Venice Lagoon and Adriatic Sea regions. Recent Publication Focus : Coastal wetlands, Holocene climate modeling, and lagoon sedimentology. Email : alexandra.bivolaru@unive.it

Michael Mendilloمشاهده پروفایل

استاد

• Space Physics
• Planetary Atmospheres
• Solar-Terrestrial Relations
• +۳ مورد دیگر

Michael Mendillo is a Professor of Astronomy and Electrical and Computer Engineering at Boston University. His research spans space physics and planetary astronomy, focusing on atmospheric emissions and plasma dynamics in Earth and Solar System bodies. He leads a research group at the Center for Space Physics and has developed innovative imaging techniques for atmospheric studies. Education: B.S. in Physics (1966, Providence College), M.A. (1968) and Ph.D. (1971) in Physics and Astronomy from Boston University His research interests include space physics , planetary atmospheres , and solar-terrestrial coupling . Key projects involve low-light-level imaging, incoherent scatter radar, and theoretical modeling of ionospheric and planetary phenomena. Recent work analyzes sodium emissions in Mercury's atmosphere and comparative aeronomy of Mars and Earth. Professor Mendillo has received funding from NASA , NSF , Air Force Geophysics Laboratory , and other agencies. His research involves active experiments using sounding rockets and space shuttles to perturb space plasmas and derive physical processes. Scientific Collaborations: National Academy of Sciences committees Facilities: Boston University Station at McDonald Observatory He teaches graduate courses in space physics and undergraduate general astronomy for non-science majors. His leadership roles include founding the Center for Space Physics and serving as Associate Dean for the Graduate School of Arts and Sciences (1978-1987).