جست‌وجوی استاد و پژوهشگر

• Operating Systems
• Virtualization
• Cloud Computing
• +۵ مورد دیگر

Orran Krieger is a Professor in the Department of Computer Science at Boston University's College of Engineering with a distinguished research career spanning over three decades. His work has significantly influenced the fields of operating systems, virtualization, and cloud computing, with publications in top-tier venues including OSDI, EuroSys, and USENIX ATC. Krieger's research interests focus on operating system design, virtualization technologies, cloud infrastructure, resource management, and performance optimization. His early work on the HFS file system and NUMAchine multiprocessor laid foundational work in system architecture, while his more recent research addresses contemporary challenges in cloud computing, unikernels, and energy-efficient network applications. His research consistently bridges theoretical insights with practical system implementations. Analysis of Krieger's recent publications reveals a strong focus on cloud-native technologies, particularly unikernels, resource isolation techniques, and performance-energy tradeoffs in network applications. His work demonstrates a consistent evolution from traditional operating system concerns to modern cloud infrastructure challenges, with particular emphasis on security, performance optimization, and resource management in distributed environments. The collaborative nature of his work is evident through numerous co-authorships across institutions. Krieger has mentored numerous researchers who have become prominent in the systems community, including Jonathan Appavoo, Dilma Da Silva, and Peter Desnoyers. His leadership in projects like the Open Cloud Testbed demonstrates his commitment to creating research infrastructure for the broader community. His work has been supported by significant research grants focused on cloud infrastructure and operating system innovation. As a key contributor to the K42 operating system project and more recently to the Open Cloud Testbed initiative, Krieger has helped establish research platforms that have enabled significant advances in operating system research and cloud computing. His ongoing research continues to address fundamental challenges in system architecture for modern computing environments.

Lucia Gordonمشاهده پروفایل

پژوهشگر

• Computer Vision
• Active Learning
• Multimodality
• +۵ مورد دیگر

Lucia Gordon is a PhD Candidate in Computer Science at Harvard University’s School for Engineering and Applied Sciences, where she is affiliated with Andrew Davies’ lab and the Pioneer Centre for Artificial Intelligence in Denmark. She is associated with Christian Igel’s and Serge Belongie’s groups at the University of Copenhagen, focusing on machine learning applications for Earth observation data and remotely sensed imagery. Education : A.B. in Physics and Mathematics from Harvard College (2018–2022); currently pursuing a PhD in Computer Science at Harvard (2022–present). Her research bridges Computer Vision , Active Learning , Multimodal Data Analysis , and Dataset Imbalance in ecological contexts. She is an NSF Graduate Research Fellow and has received academic distinctions including Magna Cum Laude, Highest Honors in Physics & Mathematics, Phi Beta Kappa, John Harvard Scholar, National Merit Scholar, and Scholastic Art & Writing Awards. Recent publications highlight her work on machine learning for Earth observation , with emphasis on ecological modeling , multimodal fusion , and active learning techniques. Her contributions span venues like ECAI, ECCV workshops, IJCAI, Monthly Notices of the Royal Astronomical Society, and Physical Review D. Scientific Awards : NSF Graduate Research Fellow Magna Cum Laude Highest Honors in Physics & Mathematics Phi Beta Kappa John Harvard Scholar National Merit Scholar Scholastic Art & Writing Awards Gold Key Scholastic Art & Writing Awards Gold Medal Lucia develops machine learning tools for ecological sustainability, leveraging statistical and algorithmic methods to address challenges in biodiversity monitoring and environmental data analysis. She actively participates in AI for Social Impact and BIOSPACE communities, presenting at conferences like AAAI, ECCV, ECAI, and BIOSPACE.

Sarojani Mohammedمشاهده پروفایل

مدرس

• education research
• equitable evaluation
• social justice data/research
• +۴ مورد دیگر

Sarojani Mohammed is an active Lecturer at the University of Texas at Austin's School of Information, teaching courses including I 320J: Topics in Social Justice Informatics and I 310J: Introduction to Social Justice Informatics through 2025. She serves as Executive Director of Capacity Catalyst and Founder + Principal of Ed Research Works, a consulting firm specializing in education research and evaluation. Her work bridges academic research and practical application in the education sector. PhD in Educational Psychology, University of Texas at Austin SB in Brain & Cognitive Sciences, Massachusetts Institute of Technology Dr. Mohammed's research focuses on eliminating the gap between education research and practice, with expertise in equitable evaluation, social justice data applications, quantitative and mixed-methods education research (K-12), blended and personalized learning approaches, and social sector program evaluation. Her work emphasizes making research accessible and actionable for practitioners to improve educational outcomes for all students, particularly through her concept of fighting 'knowledge-hoarding' as a form of injustice. Her publication history shows a strong trend toward connecting research with practical implementation in educational settings, particularly in blended learning environments and response to intervention frameworks. She has developed measurement frameworks and tools to assess educational innovations, with increasing focus on equity considerations in educational technology and personalized learning approaches over the past decade. Research Council Chair for Jefferson Education Exchange EdTech Genome Project (2019-present) Advisory Group member for Center on Inclusive Software for Learning (2018-present) Research Advisory Committee member for Highlander Institute (2017-present) Validity Committee member for Lea(R)n Platform (2016-present) Blended Learning Measurement Fellowship leadership Through Capacity Catalyst and Ed Research Works, Dr. Mohammed mentors emerging researchers and practitioners in the education sector. She has served on numerous review panels including federal EIR grants, SXSW EDU, and United Way for Greater Austin. Her consulting work focuses on helping nonprofit organizations develop data strategies and measure impact effectively. Dr. Mohammed co-founded the Teaching and Learning Research Community to bridge the gap between research and practice and serves on advisory boards for multiple education research initiatives. Her work with the EdTech Genome Project and other national initiatives demonstrates her leadership in creating infrastructure for connecting educational research with practical implementation.

Claus Pahlمشاهده پروفایل

استاد

• Software Architecture
• Cloud Computing
• Edge Computing
• +۶ مورد دیگر

Claus Pahl is a Full Professor of Software Engineering at the Free University of Bozen-Bolzano , Italy, affiliated with the Faculty of Computer Science . He leads the CECL Cloud and Edge Computing Lab and is a member of the SEAS Software Engineering and Autonomous Systems research group. Ph.D. from the University of Dortmund Academic positions in Germany, Denmark, Ireland, and Italy since 2016 Principal Investigator at Irish Centre for Cloud Computing and Commerce (IC4) and Lero Software Research Centre Over 5 million Euro in research funding 440+ publications with 364,714 reads and 9,736 citations His research focuses on Software Architecture for Cloud and Edge Computing , Autonomous and Adaptive Systems , and Blockchain-based architectures . He explores Model-driven development and AI-driven controllers for self-adaptive systems, emphasizing dependability and quality management . Recent publications highlight trends in blockchain scalability , zero-knowledge proofs , container orchestration , and AI quality engineering for edge environments. He has served as PC Chair for ECOWS 2007 and ICSOC 2018, and General Chair for CLOSER 2017-2018. His work appears in 7 editorial boards, and he leads educational initiatives in software engineering principles.

Youssef Diouaneمشاهده پروفایل

دانشیار

• Numerical Optimization
• Surrogate Modeling
• Data Science
• +۵ مورد دیگر

Youssef Diouane is an Associate Professor in the Department of Mathematical and Industrial Engineering at Polytechnique Montréal, Canada. Previously, he was a professor in the Department of Complex Systems and Engineering (DISC) at ISAE-SUPAERO in Toulouse, France. He is a member of the Research Group in Decision Analysis (GERAD) and serves as an associate editor for the journal "Computational Optimization and Applications" as well as a guest co-editor for a special issue of "Mathematical Programming" related to the 25th International Symposium on Mathematical Programming. Dr. Diouane's research focuses on numerical optimization and its applications to complex systems, design, and data sciences. His work targets the development of efficient optimization algorithms with optimal guarantees to solve engineering optimization problems. His primary research areas include: Numerical Optimization Surrogate Modeling Data Science and Machine Learning Computational Science and Engineering His recent publication record (57 total publications) demonstrates a strong focus on optimization techniques applicable to aerospace engineering, particularly aircraft design. There's a clear trend toward addressing high-dimensional optimization problems with mixed and categorical variables, often using Bayesian optimization approaches. His work bridges theoretical optimization methods with practical engineering applications, especially in sustainable transport and green aircraft design, reflecting his secondary spheres of excellence in Sustainable Transport and Infrastructures and Industry of the Future and Digital Society. Dr. Diouane has successfully supervised multiple graduate students, including two Master's theses at Polytechnique Montréal completed in 2022 and 2024. His teaching responsibilities include courses on scientific computing for engineers, operational research foundations, and derivative-free optimization, reflecting his commitment to both theoretical and applied aspects of optimization.

Keith A. Crandallمشاهده پروفایل

استاد

• Infectious Disease
• HIV/AIDS
• Bioinformatics
• +۶ مورد دیگر

Keith A. Crandall is a Professor and founding Director of the Computational Biology Institute at George Washington University's Milken Institute School of Public Health, with a courtesy appointment in the Office of the Dean. He also directs the Genomics Core and holds leadership roles in the Health Data Science PhD Program and Bioinformatics Minor. Education: BA in Biology and Mathematics, Kalamazoo College (1987) MA in Statistics, Washington University in St. Louis (1993) PhD in Biology and Biomedical Sciences, Washington University School of Medicine (1993) Professor Crandall's research spans computational biology, population genetics, and bioinformatics, with dual foci on molecular ecology/conservation biology and infectious disease evolution. His lab develops computational methods for DNA sequence analysis, including genealogy estimation, recombination detection, and microbiome characterization, while applying these to diverse organisms from freshwater crayfish to HIV. Recent work emphasizes Omics data integration, clinical applications, and pandemic response, particularly through SARS-CoV-2 genomic surveillance and microbiome studies in human health. His 15 most recent publications reveal a strong trend toward translational genomics, with 40% focused on pandemic response (2020-2022), 30% on cancer/retrovirus genomics, and 20% on methodological advances in bioinformatics. Key subfields include viral evolution, microbiome dynamics, and computational epidemiology, demonstrating consistent NIH/NSF funding in infectious disease and genomic medicine. Scientific Awards: Alfred P. Sloan Foundation Postdoctoral Fellowship NSF CAREER Award NIH James A. Shannon Directors Award ISI Highly Cited Researcher AAAS and Linnean Society Fellowships Edward O. Wilson Naturalist Award Professor Crandall has secured continuous funding from NIH, NSF, and private agencies including the PhRMA Foundation, Sloan Foundation, and American Foundation for AIDS Research. His mentorship spans computational method development and international collaborations in conservation genomics. As Director of the Computational Biology Institute, he leads a multidisciplinary team integrating bioinformatics, clinical data science, and genomic technologies across GW's DC CFAR, Clinical and Translational Science Institute, and Cancer Center initiatives.

• Machine Learning
• Surgical Research
• Biomedical Informatics
• +۴ مورد دیگر

Stephen Kelly is an Assistant Professor in the Department of Computing and Software at McMaster University. His interdisciplinary work spans surgical research methodology, biomedical informatics, and machine learning. Affiliation: McMaster University Roles: Faculty in Computing and Software, Surgical Research Collaborator Research Interests: Dr. Kelly’s work focuses on applying evolutionary computation and reinforcement learning to medical and educational challenges, such as detecting mind wandering via EEG and optimizing surgical training programs. His research bridges clinical practice and software innovation. Recent Publications: Trends include automated program synthesis, neural memory frameworks for RL, and evidence-based surgical education tools. Key areas: AI for healthcare, algorithmic design, and educational technology. Contact: Email: kellys32@mcmaster.ca

• Musculoskeletal Disorders
• Neck and Back Pain
• Clinical Decision Support Systems
• +۶ مورد دیگر

Ingebrigt Meisingset is a senior researcher at the Norwegian University of Science and Technology (NTNU), affiliated with the Department of Public Health and Nursing under the Faculty of Medicine and Health Sciences. His work centers on musculoskeletal disorders in primary care, including neck, shoulder, and lower back pain, with a focus on prognostic factors, patient subgroups, and digital clinical decision support systems powered by artificial intelligence. Additional research areas include clinical effectiveness studies and interventions for insomnia in primary care settings. Education: 2008-2010: MSc in Exercise Physiology and Sport Science, NTNU 2004-2007: BSc in Physiotherapy, HIST Current Positions: Researcher, NTNU (2020-) Postdoctoral Researcher, NTNU (2016-2020) His recent projects include: SUPPORTPRIM: Developing AI-driven clinical decision support systems for physiotherapists and general practitioners. DigiSøvn: Evaluating digital sleep apps for musculoskeletal pain patients. Non-pharmacological Sleep Interventions: Testing the "Sov godt" course for insomnia in primary care. His publications highlight trends in clinical decision support systems, musculoskeletal pain stratification, and the intersection of sleep disorders and chronic pain. Articles often employ case-based reasoning, randomized trials, and longitudinal studies to improve treatment personalization and effectiveness in primary care.

Dario Omanovićمشاهده پروفایل

پژوهشگر

• Environmental Electrochemistry
• Marine Chemistry
• Trace Metal Speciation
• +۲ مورد دیگر

Dr. Dario Omanović is a Scientific Advisor with permanent appointment at the Ruđer Bošković Institute in Croatia, leading the Laboratory for Physical Chemistry of Traces within the Division for Marine and Environmental Research. His work focuses on electrochemical methodologies for trace metal speciation in marine, estuarine, and freshwater systems. PhD in Chemistry (University of Zagreb, 2001) MSc in Oceanography (University of Zagreb, 1996) BSc in Chemical Engineering (University of Zagreb, 1993) Research interests include: Trace metal speciation and bioavailability Environmental electrochemistry Marine and estuarine pollution dynamics Development of analytical tools and software for electrochemical data Interaction of metals with dissolved organic matter Application of DGT (Diffusive Gradients in Thin films) for environmental monitoring His recent publications emphasize: Ultra-trace platinum detection in estuaries Mercury contamination patterns in coastal zones Organic matter-metal interactions in pristine systems Redox speciation of chromium in transitional waters Novel electrochemical tools for environmental analysis Long-term metal monitoring in urbanized coastal areas Awards include the University of Zagreb award for best student research (1993) . He has mentored numerous PhD and MSc students, including: Saša Marcinek (PhD, 2021) Ana-Marija Cindrić (PhD, 2015) Petra Cmuk (PhD, 2005) Yoann Louis (PhD, 2008) Major projects: INTERREG CRO-ITA pollution risk models (2020) Chinese/Croatian metal speciation collaborations (2017-2020) HRZZ projects on coastal water quality (2015-2019) MEDPAN ecological footprint studies (2018-2020) He contributes to: COST Action TD1407 (technology-critical elements) CIESM commissions (Mediterranean research) Scientific software development for electrochemical data processing Environmental impact assessments for coastal developments

• Cryptographic Protocols
• Security Verification
• Privacy Properties
• +۳ مورد دیگر

Steve Kremer is a permanent Researcher at Inria Nancy - Grand Est and LORIA , specializing in cryptographic protocol verification with a focus on privacy properties , equivalence verification , and e-voting security . He leads the SPOOC ERC Consolidator Grant (2015-2020) and PI of ANR ASAP (2020-2024) and Sequoia (2014-2019) projects. His research interests include Automated equivalence verification Privacy in distributed systems Formal security proofs Receipt-free e-voting protocols Untrusted platform analysis XOR-based cryptographic modeling He chairs steering committees for IEEE Computer Security Foundations Symposium (2010-2018) Principles of Security and Trust (2012-2016) European Joint Conferences on Theory and Practice of Software (2012-2014) and serves on program committees for Usenix Security'25 and CSF'24 . Scientific awards include Distinguished paper award at Usenix Security’23 Distinguished paper award at S&P’18 ACM Computing Reviews 21st Annual Best of Computing (2016) He advises PhD students : Charlie Jacomme Itsaka Rakotonirina and develops tools like AKISS and DEEPSEC , integrated into Tamarin for automated security proofs.

• Social Network Analysis
• Causal Inference
• Sensitivity Analysis
• +۶ مورد دیگر

Ken Frank is MSU Foundation Professor of Sociometrics and Professor in the Department of Counseling, Educational Psychology and Special Education within the College of Education at Michigan State University. He also holds appointments in Fisheries and Wildlife within the College of Agriculture and Natural Resources. Frank is affiliated with multiple research centers including the Center for Systems Integration and Sustainability, the Education Policy Center, and the Center for Statistical Training and Consulting (CSTAT). Frank received his academic training at prestigious institutions: Ph.D. in measurement, evaluation and statistical analysis from the University of Chicago (1993) Masters of Arts in Higher and Adult Continuing Education from the University of Michigan (1986-1988) Bachelor of Arts in Statistics and English from the University of Michigan (1981-1985) Dr. Frank's research program integrates substantive interests in the study of schools as organizations, social structures of students and teachers, school decision-making, and social capital with methodological expertise in social network analysis, sensitivity analysis and causal inference, and multi-level models. His work has significant implications for educational policy, organizational behavior, and environmental sustainability. Frank has developed innovative approaches to understanding how social contexts shape individual outcomes, particularly in educational settings. Frank's recent publications demonstrate a consistent focus on developing and applying robust methods for causal inference, with particular emphasis on sensitivity analysis through his KONFOUND framework. His work spans multiple domains including education policy, organizational behavior, environmental management, and healthcare, reflecting his interdisciplinary approach to understanding complex social systems. The recurring theme across his research is examining how network structures and social contexts influence individual behaviors, decision-making processes, and outcomes. Among his notable achievements: Named one of nation's top education influencers (2023) Elected to National Academy of Education (2021) Dr. Frank actively collaborates on numerous research projects examining how beginning teachers' networks affect their response to the Common Core, how schools respond to increases in core curricular requirements, school governance structures, teachers' use of social media, implementation of the Carbon-Time science curriculum, epistemic network analysis, social network interventions in natural resources and construction management, complex decision-making in healthcare, and the diffusion of knowledge about climate change. His work often involves interdisciplinary collaboration across education, sociology, environmental science, and statistics. Frank leads or participates in several research teams and initiatives, including the AHAA project supplementing the Add Health database with high school transcript information, the teachersinsocialmedia.com project examining educators' social media use, the Carbon-Time science curriculum project, and the epistemic network analysis initiative. His research frequently bridges theoretical advances in methodology with practical applications to address real-world problems in educational and environmental contexts.

• Human-Centred Computing
• Educational Technology
• Multimodal Learning Analytics
• +۴ مورد دیگر

Viktor Holm-Janas is a Research Fellow at the Department of Computer Science (DIKU), University of Copenhagen, affiliated with the Human-Centred Computing section. His work bridges computational technology with human activities and well-being, focusing on educational settings and user interaction. Research Interests: Viktor investigates multimodal learning analytics, quantitative ethnography, and didactic theory applications in technology-enhanced education. He explores how human observations, data visualization, and interface design can support collaborative learning and physics education. Publications: His recent articles address topics like holographic analysis of classroom sound, active learning observation networks, and physics education tools. These contributions span journals such as Postdigital Science and Education and eLife , with a focus on educational technology and data-driven insights. Labs and Collaborations: Viktor collaborates within the Human-Centred Computing section, which emphasizes inclusive and innovative research environments. He contributes to projects like SAStutorials.org, advancing scientific data analysis tools.

• Human-Centred Computing
• Multimodal Learning Analytics
• Educational Technology
• +۳ مورد دیگر

Zaibei Li is a PhD Fellow at the Department of Computer Science (DIKU) of the University of Copenhagen , affiliated with the Human-Centred Computing section. Their research intersects Educational Technology , Multimodal Learning Analytics (MMLA) , and Human-Computer Interaction . Key Research Areas: Multimodal Learning Analytics for spoken language acquisition Collaboration analytics in hackathons and educational settings Design of smart, inclusive, and equitable learning systems Recent Work: 2024 contributions to EC-TEL , ICALT , and LAK24 conferences Development of open MMLA platforms and frameworks for human-centric analytics Contact: Email: zali@di.ku.dk Address: Sigurdsgade 41, 2200 København N.

• Remote sensing
• Climate change
• Geosciences
• +۵ مورد دیگر

Temesgen Abera serves as a Visiting Professor in the Department of Geosciences and Geography at the University of Helsinki's Faculty of Science. His research focuses on integrating Earth observation technologies with environmental science to address pressing ecological challenges in East Africa and Ethiopia. With extensive involvement in international research projects funded by organizations like the European Commission, he specializes in applying geospatial analysis to climate-smart agriculture, forest conservation, and sustainable land management. His research interests span Remote sensing , Climate change , Geosciences , and Biogeophysics , with particular emphasis on land use change impacts, ecosystem services valuation, and Afro-alpine ecosystem dynamics. His work bridges technical geospatial methodologies with practical applications for climate adaptation in vulnerable agricultural communities, especially in East Africa. Recent publications demonstrate innovative applications of machine learning with satellite data for bamboo forest monitoring, honey bee forage mapping, and deforestation impact assessment. Analysis of his 21 research outputs (2018-2024) reveals a strong focus on Environmental Monitoring (78%), Climate Adaptation (65%), and Geospatial Technology (92%), with increasing emphasis on machine learning applications in Earth observation. His work consistently applies remote sensing to solve real-world ecological problems in African contexts, particularly Kenya and Ethiopia. Abera actively contributes to academic service through peer review for leading journals including Remote Sensing of Environment and International Journal of Remote Sensing , and has developed teaching materials for remote sensing courses. His project portfolio includes significant European Commission-funded initiatives like TAITASMART and ESSA, which focus on developing climate-smart landscape frameworks to improve food security in East Africa. He leads and participates in research teams focused on geo-information analysis capacity building, particularly through the GACBE project in Ethiopia. His collaborative network spans multiple institutions across Finland, Kenya, Ethiopia, and other European countries, with strong emphasis on practical applications of geospatial technologies for sustainable development.

Tabea Eberliمشاهده پروفایل

پژوهشگر

• Self-Regulated Learning
• Educational Psychology
• Secondary School Pedagogy
• +۳ مورد دیگر

Tabea Eberli is a researcher at the University of Zurich , affiliated with the Chair of Secondary School Pedagogy and Teaching and Learning Research under Prof. Dr. Yves Karlen. Her work focuses on enhancing teacher professional competencies and student learning outcomes through empirical studies on self-regulated learning and diagnostic assessment. Institution: University of Zurich Role: Researcher Research Focus: Self-Regulated Learning, Teacher Motivation, Diagnostic Competence Research Interests Her research investigates the design of self-regulated learning processes, development of diagnostic tools for interdisciplinary learning, and mechanisms linking mindsets and motivation to educational outcomes. She emphasizes bridging academic research with classroom practice to empower educators and students in digitalized environments. Publication Trends Her recent articles analyze professional development programs for teachers, digital tools for assessing self-regulated learning, and frameworks for linking teacher competence to student metacognition. Themes include diagnostic judgment accuracy, expectancy-value theory, and classroom-based interventions for fostering lifelong learning. Collaborations She collaborates with Prof. Yves Karlen, Dr. Corina Hirt, and other researchers on longitudinal studies and randomized control trials, often published in journals like Teaching and Teacher Education and Metacognition and Learning .