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• Nuclear Physics
• Pionic Atoms Spectroscopy
• Nuclear Structure
• +3 more

Dr. Furuno is a nuclear physics researcher at GSI Helmholtzzentrum für Schwerionenforschung GmbH in Darmstadt, Germany, specializing in pionic atoms spectroscopy and nuclear structure studies using advanced experimental techniques. His research interests include: Nuclear Physics Pionic Atoms Spectroscopy Nuclear Structure Heavy Ion Physics Chiral Symmetry Breaking Nuclear Spectroscopy Dr. Furuno has contributed to significant publications focusing on precision measurements of deeply bound pionic states and the development of experimental techniques for nuclear spectroscopy. His work involves the use of the Experimental Storage Ring (ESR) and BigRIPS spectrometer at GSI, often in collaboration with international research teams. His research provides crucial insights into the restoration of chiral symmetry breaking at finite density, which has implications for fundamental nuclear physics and astrophysical models. His publication record demonstrates expertise in: Precision measurement techniques for nuclear properties Spectroscopy of exotic nuclear systems Experimental methods for studying chiral symmetry breaking Development of advanced spectrometry instrumentation

Johannes KrebsView profile

Professor

• Topological Data Analysis
• Persistent Homology
• Spatial Statistics
• +3 more

Prof. Dr. Johannes Krebs holds the Chair of Mathematics - Statistics at the Faculty of Mathematics and Geography, Catholic University of Eichstätt-Ingolstadt since 2021. His academic service includes membership on the editorial board of Statistics , the tenure track board, examination committees for B.Sc. Mathematics and Data Science programs, and the faculty council. His research focuses on topological data analysis, persistent homology, and spatial statistics with applications in stochastic geometry. Funded by Deutsche Forschungsgemeinschaft (KR 4977/2-1 and KR 4977/1-1), his work bridges theoretical statistics with computational topology to develop novel methods for analyzing complex data structures. His methodological contributions span wavelet analysis, functional data, and bootstrap techniques for dependent data. Analysis of his recent publications reveals strong emphasis on topological inference (persistent homology, Betti numbers), spatial statistics, and wavelet methods across multiple high-impact journals including Bernoulli , Annals of Statistics , and Stochastic Processes and their Applications . His work demonstrates consistent innovation in applying topological concepts to statistical problems with theoretical guarantees. Academic service highlights include: Editorial Board Member, Statistics journal Member of Tenure Track Board Examination Committee for B.Sc. Mathematics & Data Science Faculty Council Member His research program is supported by significant DFG funding for projects on Topological Data Analysis (2021-2023) and Dynamic Objects on Random Fields (2017-2020), reflecting sustained contribution to advancing statistical methodology through topological frameworks. He maintains active collaborations with researchers at UC Davis, KU Leuven, and Heidelberg University.

Murat InalpolatView profile

Professor

• Structural Health Monitoring
• Diagnostics and Prognostics
• Structural Dynamics
• +8 more

Murat Inalpolat is a Professor and Associate Chair for Doctoral Studies in the Department of Mechanical and Industrial Engineering at the University of Massachusetts Lowell's Francis College of Engineering. He leads research projects related to wind energy, aerospace and automotive technologies and serves as an Associate Editor for the ASME Letters in Dynamic Systems and Controls Journal. In 2022, he was awarded the prestigious NASA Faculty Fellowship for work on aircraft electrification. His research focuses on structural health monitoring, diagnostics and prognostics of rotating machinery, damage detection and identification, probabilistic design and analysis, uncertainty quantification, reliability and sustainability, electric propulsion, and wind energy. His work combines theoretical modeling with experimental validation to address complex structural dynamics and acoustic challenges. His recent publications demonstrate a strong focus on wind turbine blade monitoring using acoustic sensing techniques, with several papers addressing damage detection methods, vibration analysis, and structural health monitoring systems for operational wind turbines. His research bridges theoretical modeling with practical engineering applications. NASA Fellow – Electrification of Aircrafts (2022) UML ME Department's Teaching Excellence Award (2020) Chancellor's recognition for Research Excellence and Productivity (2020) ASME Engineering Design Engineering Division Service Recognition Award (2019) CTI's Young Drive Experts award (2009) Professor Inalpolat has successfully advised numerous graduate students in mechanical engineering, with recent thesis topics focusing on structural health monitoring, wind turbine analysis, and dynamic systems. He leads significant research projects including a $1.4 million DOE grant for monitoring wind turbine blades and an NSF IUCRC WindStar project. His work has resulted in multiple patents related to turbomachinery design and clearance optimization. He is a core faculty member of the Structural Dynamics and Acoustic Systems Laboratory (SDASL), which he joined in 2014, significantly expanding the lab's capabilities in structural health monitoring, rotating machinery, and nonlinear dynamics. The lab is well-equipped for structural dynamic, acoustical, modal analysis, and control system experiments and modeling.