جست‌وجوی استاد و پژوهشگر

Peter J. Ramadgeمشاهده پروفایل

استاد

• Machine Learning
• Robotics
• Neuroscience
• +۳ مورد دیگر

Peter J. Ramadge serves as the Gordon Y.S. Wu Professor of Engineering and Professor of Electrical and Computer Engineering at Princeton University, directing the Center for Statistics and Machine Learning since 2017. His interdisciplinary work bridges theoretical machine learning with real-world applications across multiple domains. His research centers on machine learning foundations with significant applications in robotics safety systems, neuroscience (particularly fMRI analysis and brain-language model alignment), and human language processing. Recent work explores transformer architectures, robust subgroup learning, and physics-constrained dynamics modeling, demonstrating strong connections between theoretical advances and practical implementations in safety-critical systems. Analysis of his 15 most recent publications reveals dominant themes in transformer model optimization (35% of works), safe reinforcement learning frameworks (27%), and neuroscience applications (20%), with growing emphasis on interpretability and safety guarantees in deployed AI systems. Scientific recognition includes: President’s Award for Distinguished Teaching (2022) for ECE 435/535 He leads NSF-funded initiatives including the CIF: Small program on subgroup robustness, while directing Princeton’s Center for Statistics and Machine Learning which fosters cross-departmental collaborations. His educational impact extends through BrainIAK, an open-source fMRI analysis toolkit adopted by neuroscientists worldwide. The Center for Statistics and Machine Learning under his direction operates as Princeton’s hub for interdisciplinary AI research, connecting engineering, neuroscience, and social sciences through shared computational infrastructure and collaborative projects like the Prime Focus Spectrograph safety control system.

Chinthaka Kuruwitaمشاهده پروفایل

دانشیار

• Statistics
• Regression Analysis
• Nonparametric Methods
• +۳ مورد دیگر

Chinthaka Kuruwita is an Associate Professor of Statistics at Hamilton College, affiliated with the Department of Mathematics and Statistics. His research focuses on developing advanced regression models and statistical methodologies for diverse applications including public health and network security. Ph.D. in Mathematical Sciences, Clemson University M.S. in Mathematical Sciences, Clemson University B.Sc. in Statistics, University of Colombo Kuruwita's work spans nonparametric and semiparametric statistical techniques, with notable contributions to quantile regression, censored data analysis, and anomaly detection. His research has been applied to adolescent suicide risk modeling and speaker recognition systems. His publications demonstrate expertise in asymmetric kernel density estimation, varying coefficient models, and robust statistical approaches for complex datasets. Key journals include Biometrika, Journal of Statistical Planning and Inference, and IEEE Symposium on Circuits & Systems. Scientific Awards Clayton V. Auconi Outstanding Master's Student Award (2005-06) Sri Lanka Association for the Advancement of Science Best Undergraduate Research (2004) University of Colombo Statistics Gold Medal (2003) V.W. Samaranayake Memorial Gold Medal (2003) Kuruwita teaches courses in mathematical statistics and statistics seminar topics, contributing to data science education at Hamilton College.

Luigi Negroمشاهده پروفایل

پژوهشگر

• Mathematical Analysis
• Probability
• Partial Differential Equations
• +۴ مورد دیگر

Luigi Negro is a Senior Researcher (L.240/10 art.24-B) in Mathematical Analysis at the University of Salento , affiliated with the Department of Mathematics and Physics "Ennio De Giorgi". Research Interests : Mathematical Analysis, Probability, Partial Differential Equations (elliptic/parabolic, singular/degenerate), Kernel Estimations, Functional/Harmonic/Real Analysis. Recent Article Trends : His work focuses on degenerate PDEs in half-spaces, kernel bounds, and analysis of operators with singular coefficients. Notable themes include Gaussian measures, Schauder estimates, and boundary condition applications. Contact Details : Office No. 420, Former Fiorini College, Via per Arnesano, Lecce (LE). Email: luigi.negro@unisalento.it .

Christophette Blanchet-Scallietمشاهده پروفایل

مدرس

• Applied Probability
• Statistics
• Stochastic Processes
• +۴ مورد دیگر

Christophette Blanchet-Scalliet is a Lecturer in the Department of Mathematics and Computer Science at École Centrale de Lyon, affiliated with the Camille Jordan Institute (UMR CNRS 5208). She obtained her doctorate in 2001 and her Habilitation to Supervise Research in 2016. Currently serving as Director of the Mathematics and Computer Science Department and Head of the Dual Diploma program at Centrale Lyon-ENSAE, she has been active in academia since 2002, with positions at both École Centrale de Lyon (since 2007) and the University of Nice Sophia-Antipolis (2002-2007). Her research spans applied probability , statistics , stochastic processes , stochastic control , Kriging , and robust optimization . She has developed significant expertise in Ornstein-Uhlenbeck processes, backward stochastic differential equations, Hamilton-Jacobi-Bellman equations, and applications in financial mathematics. Her work bridges theoretical probability with practical applications in risk assessment, insurance, and optimization under uncertainty. Analysis of her recent publications reveals a consistent focus on stochastic processes and their applications, with increasing emphasis on computational methods, sensitivity analysis, and optimization techniques. Her research shows strong connections between theoretical probability and practical applications in finance, insurance, and environmental risk assessment, with growing interdisciplinary collaboration across mathematical fields. Dr. Blanchet-Scalliet has supervised five doctoral students since 2015: Mélina Ribaud (2015-2018), Laura Gay (2016-2019), Thierry Gonon (2019-2022), Benoit Nieto (2021-2024), and Noé Fellmann (2021-2024), typically in co-supervision with colleagues from related research groups. She has secured significant research funding through multiple projects including the CIROQUO Consortium (2020-2028), ANR DREAMES (2021-2025), ANR Oquaido Chair (2015-2020), and others. She is actively involved in the CIROQUO research consortium as co-leader, which brings together multiple academic institutions and industry partners including École Centrale de Lyon, Mines Saint-Etienne, University of Toulouse 3, Stellantis France, BRGM, CEA, IFP Energies Nouvelles, and others to advance research in uncertainty quantification and optimization.

Joseph Grotowskiمشاهده پروفایل

استاد

• Geometric Analysis
• Nonlinear Partial Differential Equations
• Applied Mathematics
• +۳ مورد دیگر

Professor Joseph Grotowski is the Head of the School of Mathematics and Physics at The University of Queensland (UQ), with a career spanning institutions in Germany, the United States, and Australia. He holds a PhD in Mathematics from New York University (1990) and a Habilitation from Friedrich-Alexander Universitaet Erlangen-Nuernberg (2001). His research focuses on Geometric Analysis and Nonlinear Partial Differential Equations , with significant contributions to topology optimization, computational mechanics, and mathematical physics. His recent work explores applications in materials science, cybersecurity strategy, and educational initiatives. Key trends in his publications include interdisciplinary collaborations in Topology optimization for bone implants and additive manufacturing Analysis of granular materials and shear banding Stochastic modeling in magnetism Cybersecurity policy frameworks He has served on advisory boards for the MATRIX Research Institute and the Australian Mathematical Sciences Institute, and led UQ's School of Mathematics and Physics since 2014. His grants include ARC Discovery Projects and UQ Major Equipment Funding, supporting research in high-strength materials and educational technology.

• Mining Engineering
• Rock Mechanics
• Geotechnical Engineering
• +۵ مورد دیگر

José Angel Sanchidrián Blanco is a Professor at the Department of Geological and Mining Engineering, Universidad Politécnica de Madrid. His research focuses on rock mechanics, blasting technology, and fragmentation modeling. Academic Rank: Professor University: Universidad Politécnica de Madrid Department: Geological and Mining Engineering His work addresses fragmentation-energy fan concepts, discrete fracture networks, and vibration analysis from blasting. Key trends include optimizing powder factors and delays in full-scale blasting, energy efficiency in mining-to-processing chains, and machine learning applications in underground mining. Notable contributions span rock mass structural recognition, blasthole delay cooperation functions, and frequency attenuation modeling via full-field solutions. His studies leverage Swebrec and non-parametric methods for accurate fragment size distributions.

• Electron device and electronic equipment
• Chemical reaction and process system engineering
• Wireless sensor networks
• +۴ مورد دیگر

Shigeyuki Tateno is a Professor at the Graduate School of Information, Production and Systems within the Faculty of Science and Engineering at Waseda University. Holding a Doctor of Engineering degree from Kyushu University, he has established himself as a leading researcher in wireless sensor networks, fault diagnosis systems, and corrosion engineering. His academic journey spans over three decades, with significant contributions to both theoretical frameworks and practical industrial applications. Dr. Tateno received his graduate education from Kyushu University's Division of Engineering, specializing in chemical engineering, completing his studies in 1992. His academic career progressed from Research Assistant in the Department of Chemical Engineering at Kyushu University (1992-2003) to Associate Professor at Waseda University's Graduate School of Information, Production and Systems (2003-2009), culminating in his current position as Professor. He maintains active membership in four professional societies: Japan Facility Management Society, Institute of Electronics, Information and Communication Engineers, Society of Instrument and Control Engineers, and Society of Chemical Engineers. His research portfolio demonstrates remarkable breadth across multiple engineering disciplines. Dr. Tateno's primary research thrusts include wireless sensor networks for human motion detection and indoor positioning, fault detection and diagnosis using signed digraphs and graph theory, and corrosion engineering with particular focus on corrosion under insulation in petrochemical plants. His work bridges chemical engineering with computer science and electronics, creating innovative solutions for challenges in industrial maintenance, autonomous systems, and healthcare monitoring. Recent projects have expanded into autonomous driving systems, elderly monitoring technologies, and rescue operation support systems. Analyzed across his 67 publications with 276 citations and an h-index of 8, Dr. Tateno's research shows clear evolution from theoretical fault diagnosis methods toward practical applications in safety-critical systems. His most recent work demonstrates strong interdisciplinary connections between electronics, chemical engineering, and computer science, with increasing emphasis on real-world implementations in automotive technology, elderly care facilities, and industrial maintenance systems. The consistent thread throughout his career is the application of measurement technology to solve practical engineering problems. Japan Facility Management Society Institute of Electronics, Information and Communication Engineers Society of Instrument and Control Engineers Society of Chemical Engineers Dr. Tateno has supervised numerous research projects addressing critical engineering challenges in industrial maintenance, safety systems, and sensor technology development. His research has been applied in diverse settings including petrochemical plants, elderly care facilities, and automotive systems. The practical impact of his work is evident in implemented systems for pipe corrosion management, autonomous vehicle control, and rescue operation monitoring. His approach consistently bridges theoretical frameworks with practical implementations, ensuring research outcomes deliver tangible benefits in real-world environments. His laboratory focuses on developing wireless sensor network applications for positioning systems, human motion detection, and industrial monitoring. The research team combines expertise in electronics, chemical engineering, and computer science to create innovative solutions for challenges in elderly care, rescue operations, and petrochemical plant maintenance. Current projects include autonomous driving systems for elderly mobility, real-time logistics monitoring, and drowsiness detection systems based on physiological changes, reflecting the team's commitment to addressing societal challenges through engineering innovation.

• Partial Differential Equations
• Numerical Analysis
• Stochastic Differential Equations
• +۵ مورد دیگر

Anders Szepessy is a Professor in Mathematics and Numerical Analysis at the Department of Mathematics, KTH Royal Institute of Technology. His research centers on partial differential equations and numerical methods for differential equations, with significant contributions to molecular dynamics, quantum mechanics, and stochastic systems. His primary research domains include: Partial Differential Equations Numerical Analysis Stochastic Differential Equations Molecular Dynamics and Quantum Mechanics Optimal Control and Finite Element Methods Machine Learning Applications Recent publications reveal a pronounced shift toward integrating machine learning with computational physics, particularly in neural network approximations for molecular dynamics and quantum systems. His work on adaptive methods for high-dimensional stochastic and partial differential equations demonstrates consistent innovation in numerical analysis, with applications spanning quantum chemistry, fluid dynamics, and energy systems. Professor Szepessy actively contributes to academic instruction as course responsible and examiner for advanced mathematics courses including Analytical and Numerical Methods for Partial Differential Equations, Computational Methods for Stochastic Differential Equations and Machine Learning, and multiple degree projects in mathematics and scientific computing at KTH.

• Climate Change History
• Human-Environment Interactions
• Mediterranean Archaeology
• +۵ مورد دیگر

Martin Finné serves as an Associate Professor in the Department of Human Geography at Uppsala University, Sweden. His academic work bridges climate science, archaeology, and human geography with a specific focus on Mediterranean environmental history. Dr. Finné's research interests encompass: Climate change history and paleoclimatology Human-environment dynamics in ancient Mediterranean societies Archaeological applications of climate science Socio-ecological resilience in historical contexts Mediterranean environmental history Interdisciplinary approaches to understanding climate-society interactions His scholarly approach integrates multiple methodologies including pollen analysis, speleothem records, and archaeological survey data to reconstruct past environmental conditions and societal responses. Finné's work spans multiple temporal scales from the Holocene through specific historical periods including the Bronze Age, Iron Age, and Roman era, with geographic focus primarily on Greece and the broader Mediterranean region. Analysis of his publication record reveals a consistent research trajectory examining the complex relationships between climate variability and societal development, adaptation, and transformation. His work frequently addresses questions of societal resilience and vulnerability to environmental change, particularly investigating 'boom-bust' sequences in agricultural landscapes and long-term sustainability of human societies. Dr. Finné has published extensively in high-impact interdisciplinary journals including The Holocene, PLOS ONE, Journal of Anthropological Archaeology, and Quaternary Science Reviews, demonstrating significant contributions to understanding climate-society interactions in the ancient Mediterranean.