جست‌وجوی استاد و پژوهشگر

Jack Marquezمشاهده پروفایل

عضو هیئت علمی

• High Performance Computing (HPC)
• Cloud Computing
• Heterogeneous Storage Systems
• +۳ مورد دیگر

Jack Marquez is a Research Assistant Professor at the University of Tennessee, Knoxville, affiliated with the College of Engineering and the Department of Electrical Engineering and Computer Science. He is a member of the Global Computing Laboratory directed by Michela Taufer. PhD in Software Engineering (2022), Universidad Autónoma de Occidente, Colombia BS in Software Engineering (2013), Universidad Autónoma de Occidente, Colombia His research focuses on High Performance Computing (HPC) and Cloud Computing, with a particular emphasis on heterogeneous storage systems, scientific workflows, and performance optimization techniques. He has developed scalable algorithms for motif counting, dynamic simulation management, and data fabric integration, bridging computational efficiency with data-intensive science. His recent publications highlight expertise in: Optimizing HPC performance in cloud environments In-situ analysis for molecular dynamics simulations Machine learning-driven resource allocation Checkpointing and fault tolerance mechanisms Community-driven scientific data infrastructure Previously, he served as a researcher and adjunct professor at Universidad Autónoma de Occidente (2013–2016), contributing to software engineering pedagogy and industry collaboration as a software developer. He is based in the Min H. Kao Building, Room 351, and can be reached at jmarque4@utk.edu .

Anthony Lagainمشاهده پروفایل

پژوهشگر ارشد

• Planetary Science
• Impact Cratering
• Mars Geology
• +۳ مورد دیگر

Dr. Anthony Lagain is an Adjunct Research Fellow at Curtin University's School of Earth and Planetary Sciences, affiliated with the Faculty of Science and Engineering and the Office of the Provost. His research focuses on planetary science, particularly impact cratering processes on Mars, the Moon, and other celestial bodies. He specializes in automated crater-counting techniques, Martian meteorite origins, and the geologic evolution of planetary surfaces. Key research interests include lunar and Martian chronology, asteroid impact dynamics, and the application of machine learning to planetary data analysis. He has contributed to projects such as the Mars Crater Database and the FRIPON meteor network. Recent work includes recalibrating lunar chronology using spatial cratering rates and identifying the ejection site of the oldest martian meteorite. His collaborative projects span international partnerships, emphasizing interdisciplinary approaches in astrogeology and planetary geophysics. Contributions include over 20 peer-reviewed articles in journals like Nature Communications , Icarus , and Science Advances .

• Transport Systems
• Rail Transport Systems
• Urban Transport Systems
• +۱۲ مورد دیگر

Bruno Dalla Chiara is a Full Professor in the Department of Environment, Land and Infrastructure Engineering (DIATI) at the Politecnico di Torino, where he has been a faculty member since 1999, progressing from university researcher to associate professor and full professor since 2019. He is affiliated with the Interdepartmental Center CARS@PoliTO for Automotive Research and Sustainable Mobility and serves as the Mobility Manager of the university since 2013. His leadership extends to coordinating the Mobility group within the RUS network (Network of Universities for Sustainable Development) for 2023–2026. Education: He earned his M.Sc. in Mechanical Engineering from the Polytechnic of Turin in 1993 and a PhD in Transport Engineering (administrative seat: University of Trieste) in 1997, specializing in technological innovation and telematics for transport. Research Interests: Bruno Dalla Chiara’s research focuses on sustainable and intelligent transport systems. His key areas include: Rail, urban, and cable-driven transport systems Intermodal and freight logistics Intelligent Transport Systems (ITS) Transport data analytics and modeling Electrification and energy efficiency in transport Mobility as a Service (MaaS) His work integrates engineering, policy, and sustainability, aligning with SDG Goals 9, 11, and 12. Publication Trends: His recent publications (2023–2025) emphasize sustainable urban mobility, rail innovation, MaaS governance, and data-driven transport solutions. There is a strong focus on decarbonization, electrification, and safety technologies like ADAS. His work spans journals and conference proceedings in transportation engineering, sustainability, and railway technology, often combining technical analysis with socioeconomic impact assessment. Scientific Awards: The IET Premium Awards (2014) Best Article Award from Ingegneria Ferroviaria (2014) Start Up Torino Piemonte (2006) Advising and Grants: He supervises PhD students in the Energetica program, including Flavio Cappelli and Simona Gurri’. He has led numerous research projects funded by national (PRIN), regional, EU (PNRR, Horizon), and corporate sources. He is the Scientific Director of multiple commercial and non-commercial research agreements, including the TorinoMaaS4Italy project. His grants focus on sustainable transport, intelligent systems, and infrastructure innovation. Labs and Teams: He leads the Transport Systems and Mobility research laboratory at DIATI and is a key member of CARS@PoliTO. His team works on simulation, data analytics, and technological innovation in transport, collaborating with industry and public agencies on real-world mobility challenges.

Tobias Wrigstadمشاهده پروفایل

استاد

• Type Systems
• Reference Capabilities
• Programming Languages
• +۲ مورد دیگر

Tobias Wrigstad is a faculty member at Uppsala University, Sweden, with research interests spanning type systems, reference capabilities, programming language design, scripting languages, and concurrent/parallel programming. His work focuses on memory management, concurrency safety, and language extensions for performance optimization. Education: Not explicitly mentioned in provided data Research Interests: Designing type systems to enforce concurrency safety and memory correctness Reference capabilities for manual and automatic memory management Actor model programming and garbage collection co-design Cache locality optimization without program restructuring Formal verification of language designs using Dafny Recent Publications (2025-2015): Explore concurrency safety through region ownership Develop parallel array programming models in Kappa Investigate energy-efficient garbage collection Design capability-based dynamic languages for data race freedom Create formal models for heap invariants and incorrectness Optimize memory allocation via load barriers Conference Involvement: 2025: IWACO Committee Member, OOPSLA Associate Chair 2024: Program Co-Chair for IWACO, Author in VIMPL, MPLR, ISMM 2023: SPLASH Steering Committee, ECOOP PC Member 2022-2015: Active in PLDI, ECOOP, ICFP, and related workshops

Guido Montúfarمشاهده پروفایل

استادیار

• Mathematical Machine Learning
• Deep Learning Theory
• Graphical Models
• +۷ مورد دیگر

Guido Montúfar is Assistant Professor at the University of California, Los Angeles (UCLA) in the Departments of Mathematics and Statistics, and Research Group Leader at the Max Planck Institute for Mathematics in the Sciences (MPI MIS). His work bridges mathematical machine learning, deep learning theory, and information geometry. Current affiliations: UCLA (since 2017) and MPI MIS (since 2018) ERC Starting Grant on Deep Learning Theory Research interests focus on the interplay between model capacity, optimization landscapes , and generalization in deep learning, combining tools from algebraic geometry , optimal transport , and information theory to analyze neural network behavior. Recent publications address tropical geometry of neural networks , algebraic optimization in reinforcement learning , and information-theoretic approaches to data representation . His work reveals connections between policy gradient methods and Wasserstein gradient flows . Scientific grants: ERC Starting Grant, DFG SPP 2298, NSF CAREER

Nathan Henryمشاهده پروفایل

پژوهشگر

• Psychology
• Addiction
• Human Factors
• +۶ مورد دیگر

Nathan Henry is a postdoctoral research associate at the University of Western Australia (UWA), affiliated with the School of Psychological Science and the Human Factors and Applied Cognition lab. His work focuses on developing attentional control training paradigms for submarine operators and exploring the psychological impacts of digital technologies like artificial intelligence. Previously trained in physics and medical physics, he holds a BTech from the University of Auckland (2012–2015), an MSc from the University of Canterbury (2016–2019), and a PhD in Psychology & Neuroscience from Auckland University of Technology (2021–2025). His research interests span behavioral addictions, computational modeling, and the intersection of human psychology with digital tools. Key areas include problematic pornography use, ecological momentary assessment for emotional dynamics, and AI ethics. He has contributed to stroke rehabilitation studies, digital transformation of medical research, and interventions for gambling addiction. Nathan has published 18 works in peer-reviewed journals and conferences, focusing on topics ranging from AI safety to clinical trial methodologies. His technical expertise includes R, Python, and statistical analysis frameworks. He maintains an active presence in academic networks and collaborates internationally on human factors and cognition research. His professional history includes roles as a Medical Physics Registrar at Auckland City Hospital and a data analyst at Auckland University of Technology's Faculty of Health and Environmental Sciences. He is committed to advancing adaptive digital interventions and ethical AI applications through rigorous empirical methods.

Christian Haaseمشاهده پروفایل

استاد

• Lattice Polytopes
• Toric Algebra
• Tropical Geometry
• +۳ مورد دیگر

Prof. Dr. Christian Haase is a Professor at the Department of Mathematics within the School of Mathematics and Computer Science at Freie Universität Berlin. He leads the Discrete Algebraic Geometry & Math for Teaching Post workgroup. His research focuses on lattice polytopes, toric algebra, tropical geometry, combinatorial commutative algebra, algorithmic algebra, and geometric/topological combinatorics. He has held a permanent academic position since at least 2008, as evidenced by his extensive publication record from that period onward. His work includes collaborations on foundational topics like Ehrhart theory, integer decomposition properties, and convex polytope decompositions. His research contributions span theoretical advances in algebraic geometry and discrete mathematics, with applications to computational algebra and geometric combinatorics. Notable works include studies on the finiteness threshold width of lattice polytopes and the exploration of Gaussian mixture models' mode counts. He maintains an active role in mentoring PhD students and postdoctoral researchers in his workgroup, though specific advisee names are not listed here. His research has been published in top journals such as Advances in Mathematics, Mathematische Zeitschrift, and the Annals of Combinatorics. Haase's academic activities include organizing research projects and conferences, and he serves as a key contributor to the mathematical community through his editorial work and collaborative research initiatives.

John Fairweatherمشاهده پروفایل

پژوهشگر ارشد

• Geochemistry
• Archaeological geology
• Palaeoclimate reconstruction
• +۵ مورد دیگر

John Fairweather is a Research Fellow in Archaeology at the School of Social Sciences, The University of Western Australia. He holds a PhD in Geology from Curtin University, awarded on July 1, 2024, for his dissertation "Mapping Planetary Surface Ages at Ultimate Resolutions with Machine Learning: The Moon." Dr. Fairweather is a geologist whose research focuses on geochemical processes and their applications in archaeology and palaeoclimate studies. His current work centers on the analysis of manganese-rich desert varnish, aiming to develop it as a proxy for reconstructing past climate in arid regions. His methodology combines electron microprobe analysis and computational data processing to explore environmental change over long timescales. His broader research interests span multiple disciplines, including surface processes on other planets and moons, machine learning applications for improving geological analysis tasks, and the development of geochemical methods for cross-disciplinary research. His work contributes to several UN Sustainable Development Goals related to environmental protection and scientific advancement. Dr. Fairweather's publications demonstrate expertise in Western Australia archaeology, machine learning applications in planetary science, rock art dating, and impact crater analysis. His recent work shows a strong trend toward interdisciplinary research combining geological methods with archaeological questions, particularly in the Murujuga (Dampier Archipelago) region. Geology Impact craters Provenance analysis Rock art dating Machine learning applications in geology Dr. Fairweather collaborates closely with archaeologists, planetary scientists, and geomorphologists to utilize advanced tools for geochemical data analysis. His research has been featured in numerous publications and has garnered attention from news outlets and academic platforms.

• Longitudinal Data Analysis
• Bayesian Analysis
• Joint Modeling
• +۵ مورد دیگر

Taban Baghfalaki is a Lecturer in Statistics with a focus on advanced statistical methodologies applied to longitudinal data analysis, Bayesian inference, and joint modeling. His work integrates complex statistical techniques to address challenges in health sciences, genetics, and epidemiology. He has contributed to developing Bayesian approaches for handling zero-inflated data, competing risks, and pleiotropy in genomic studies. Key research areas include dynamic prediction in longitudinal studies, variable selection in high-dimensional datasets, and the application of copula models for multivariate data analysis. He has pioneered tools like the GCPBayes pipeline for cross-phenotype genetic association studies, demonstrating expertise in both theoretical and applied statistics. His publications span 2011–2025, emphasizing Bayesian methods, survival analysis, and longitudinal modeling. Notable contributions include frameworks for joint modeling of longitudinal and survival outcomes, methods for analyzing skewed mixed responses, and computational tools for genomic data. Awards and grants are not explicitly mentioned in the provided texts, but his prolific publication record reflects sustained research activity. He collaborates on projects involving healthcare data (e.g., Tehran Lipid and Glucose Study) and genetic epidemiology.

Nina Deliuمشاهده پروفایل

استادیار

• Bayesian Inference
• Reinforcement Learning
• Multi-armed Bandits
• +۶ مورد دیگر

Nina Deliu is a Tenure-track Assistant Professor in Statistics at Sapienza University of Rome's MEMOTEF Department, with joint appointments as a Visiting Faculty Researcher at Google and Visiting Researcher at the MRC-Biostatistics Unit, University of Cambridge. She holds editorial roles at Trials journal and YoungStatS, and maintains active collaborations with institutions including the University of Toronto, National University of Singapore, ISTAT, NADO Italia, and FAO. Education: PhD in Methodological Statistics, Sapienza University of Rome (2021) MSc in Statistics and Decisions, Sapienza University of Rome (2017) MSc in Mathématiques, Informatique, Décision et Organisation, Université Paris Dauphine (2016) Research spans Bayesian inference, reinforcement learning, multi-armed bandits, adaptive experimental design, copula models, and uncertainty quantification, with applications in healthcare, education, and public health. Her work bridges theoretical statistics with real-world challenges in biostatistics, mobile health interventions, and digital education platforms. Publications focus on adaptive experimentation frameworks, response-adaptive clinical trials, reinforcement learning in healthcare, and copula-based statistical methods. Recent work emphasizes finite-sample error control, zero-inflated count data modeling, and multivariate dependency analysis. Awards: XPRIZE $1M Digital Learning Challenge (2023) for the Adaptive Experimentation Accelerator project Research Projects: The role of self-reported health outcomes in cancer risk prediction using UK Biobank data Contextual Multi-armed Bandits for Developing Personalized Mobile Health Interventions Leads collaborations through the IAI Lab (University of Toronto) and coordinates interdisciplinary teams for projects in statistical methodology, health interventions, and official statistics innovation.

• Mathematical Modelling
• Combustion Reactions
• Scientometrics
• +۳ مورد دیگر

Nabeil Maflahi is a Senior Lecturer in Mathematics at the School of Mathematics & Computer Science, University of Wolverhampton, UK. His academic career spans over 15 years, with a focus on mathematical modeling and scientometrics. BSc in Mathematics & Computer Science (University of Birmingham) PhD in Applied Mathematics (University of Birmingham) PGCert in Learning & Teaching in Higher Education (University of Wolverhampton) His research bridges mathematical modeling of combustion reactions and cybermetrics/scientometrics/altmetrics. Recent publications analyze collaboration patterns, citation dynamics, and Mendeley readership metrics across disciplines. Professional activities include peer reviewing for journals like Scientometrics and the COLLNET Journal . Teaching responsibilities cover modules from calculus to advanced operational research techniques.

Melissa S.A.M. Beversمشاهده پروفایل

پژوهشگر ارشد

• Biomedical Engineering
• Orthopaedic Biomechanics
• Computed Tomography
• +۳ مورد دیگر

Melissa S.A.M. Bevers is a Research Fellow at the School of Biomedical Engineering , Eindhoven University of Technology , specializing in Orthopaedic Biomechanics . Her work focuses on advanced imaging techniques for bone microarchitecture analysis. External affiliation: VieCuri Medical Center Contributions to UN Sustainable Development Goals: Good Health and Well-being Research Interests: Utilizing high-resolution peripheral quantitative CT (HR-pQCT) and photon-counting CT to study bone structure, strength, and remodeling. Key areas include motion correction algorithms, radiation dose optimization, and disease-specific bone analysis (e.g., osteogenesis imperfecta). Recent Publications: Advancements in CT imaging accuracy (2025), comparative studies on bone remodeling detection (2024), and clinical applications in fracture liaison services (2024). Collaborations: Active partnerships with institutions like VieCuri Medical Center and researchers in bone health and imaging.

Joseph M. Mahoneyمشاهده پروفایل

دانشیار

• Biomechanics
• Machine Learning
• Human Movement Analysis
• +۴ مورد دیگر

Joseph M. Mahoney serves as the Chair of Engineering and Associate Professor of Mechanical Engineering at Alvernia University , where he leads engineering program development, ABET accreditation efforts, and laboratory design. He previously held Associate Professor positions at Penn State Berks in both Mechanical Engineering and Kinesiology. His research at the intersection of Biomechanics and Machine Learning focuses on cost-effective data collection tools for human movement analysis, with recent attention to stroller running biomechanics and overuse injury prevention . His professional memberships include the American Society of Engineering Education (ASEE), American Society of Biomechanics (ASB), Institute of Industrial and Systems Engineers (IISE), and American Society of Mechanical Engineers (ASME). At Alvernia, he oversees five engineering programs, designs cutting-edge labs, and builds industry partnerships for real-world engineering projects and internships. As an educator, he teaches engineering design , statics , and computer programming while mentoring undergraduate researchers. His Biomechanics and Gait Evaluation Laboratory (BaGEL) at Penn State Berks utilized motion capture and force plate technologies to study running mechanics. Current research explores hills and uneven terrain effects on stroller running, alternative stroller designs, and movement pattern analysis using inertial measurement units .

Volker Kaibelمشاهده پروفایل

استاد

• Discrete Optimization
• Polyhedral Combinatorics
• Extended Formulations
• +۵ مورد دیگر

Prof. Dr. Volker Kaibel is a full-time Professor for Mathematical Optimization at Otto-von-Guericke Universität Magdeburg since 2007. His research focuses on Discrete Optimization , Polyhedral Combinatorics , and Extended Formulations , with applications in combinatorial optimization , quantum computing , and genomic epidemiology . His recent work includes studies on Polytope Extensions with Linear Diameters , Steiner Cut Dominants , and Scale-Free Spanning Trees . Publications span journals like SIAM Journal on Discrete Mathematics , Mathematics of Operations Research , and Journal of Computational Biology , emphasizing theoretical advancements in mathematical programming and polyhedral theory . Key projects include the long-running Mathematical Complexity Reduction (2017–2026) and earlier DFG-funded initiatives on Extended Formulations and Orbitopes . His collaborations extend to institutions like the Zuse-Institute Berlin and DFG Research Center MATHEON .

Emiliano Valdezمشاهده پروفایل

استاد

• Actuarial Science
• Financial Mathematics
• Risk Modeling
• +۳ مورد دیگر

Emiliano Valdez is a Professor at the University of Connecticut in the Department of Accountancy, Finance and Insurance (AFI), specializing in actuarial and financial mathematics. His academic profile shows consistent scholarly activity through 2025 with a focus on bridging theoretical mathematics with practical insurance applications. Dr. Valdez maintains an active research program with regular office hours (Mondays 10am-1pm during Spring 2023) and can be reached at MONT 439. Dr. Valdez's research program demonstrates deep expertise in risk modeling and insurance analytics, with particular strengths in developing mathematical frameworks for risk-sharing mechanisms and applying advanced machine learning techniques to traditional actuarial problems. His work spans theoretical characterizations of risk allocation principles and practical implementations of classification algorithms for imbalanced insurance datasets. The interdisciplinary nature of his research connects financial mathematics, statistical theory, and computational methods to address complex challenges in insurance pricing, risk assessment, and financial modeling. Analysis of Dr. Valdez's recent publications reveals a clear evolution toward integrating sophisticated machine learning approaches with classical actuarial science. His work on SAMME.C2 algorithms addresses critical challenges in imbalanced classification common in insurance contexts, while his research on flexible distribution modeling provides innovative solutions for complex claim patterns. The international scope of his work, including analysis of Colombian healthcare systems, demonstrates his ability to apply actuarial principles across diverse regulatory environments and insurance markets. Dr. Valdez maintains active engagement with both academic and industry communities through his scholarly publications and likely professional affiliations. His research output shows consistent productivity with publications appearing through 2025, indicating an active research program with ongoing projects in risk modeling, insurance analytics, and financial mathematics. His work has practical implications for insurance pricing models, risk management frameworks, and regulatory compliance methodologies.