جستجوی استاد راهنمای دانشگاهی

Mihhail Berezovskiمشاهده پروفایل

دانشیار

• Data Science
• Industrial Mathematics
• Numerical Methods
• +۷ مورد دیگر

Dr. Mihhail Berezovski is a tenured Associate Professor of Mathematical Sciences and Program Coordinator for the B.S. in Data Science at Embry-Riddle Aeronautical University's College of Arts & Sciences. With over ten years of experience, he has pioneered data science applications and cross-disciplinary engagement strategies that connect academic research with real-world industry problems. His innovative approach provides students with authentic data-enabled research experiences through partnerships with businesses, government agencies, and non-profit organizations. Dr. Berezovski earned his Ph.D. in Applied Mechanics from Tallin Technological University. His academic journey includes positions as a Postdoctoral Scholar at Worcester Polytechnic Institute (2011-2015) and Researcher at the Institute of Cybernetics at TUT, Estonia (2011-2015). Dr. Berezovski's research spans Data Science, Industrial Mathematics, Numerical Methods, and Material Science . He specializes in developing data-enabled solutions for complex problems across diverse domains including aviation, child welfare systems, and material science. His work bridges theoretical mathematics with practical applications, focusing on adaptive algorithms for wave propagation in heterogeneous materials and predictive analytics for real-world systems. He has established a sustainable model where students engage directly with industry-provided problems, creating meaningful research experiences that prepare them for data science careers. His publication record demonstrates a clear evolution from theoretical work in elastic wave propagation toward applied data science projects addressing real-world challenges. Recent publications show increasing focus on interdisciplinary applications in aviation, social services, and media literacy, reflecting his commitment to solving practical problems through mathematical and computational approaches. Dr. Berezovski's contributions to mentoring have been recognized with numerous prestigious awards: 2024 Faculty Mentor Award from the Mathematical, Computing, and Statistical Sciences Division of CUR 2023 ERAU College of Arts & Sciences Award for Undergraduate Student Mentorship 2022 ERAU College of Arts & Sciences Dean's Award for Leadership and Innovation 2022 ERAU Faculty Mentor of the Year Award With over 200 students from 26 universities participating in 70+ research projects, Dr. Berezovski has established a highly successful undergraduate research program. His funding portfolio includes support from the National Science Foundation and the Mathematical Association of America, and he has served as co-PI on projects with METIS Solutions and DHS. His innovative model connects students directly with industry partners, providing authentic research experiences that result in publications, conference presentations, and valuable career preparation. Dr. Berezovski leads initiatives that foster cross-disciplinary collaboration across Embry-Riddle, working with departments including Security Studies, Human Factors, Aviation Maintenance Science, and Civil Engineering. His research group focuses on applied data science projects that address real-world challenges while providing students with hands-on experience. The program has established long-term partnerships with over ten organizations, businesses, and government labs, creating a sustainable ecosystem for data science research and education.

Wenbin Zhouمشاهده پروفایل

استادیار

• Mechanics of Materials
• Sustainable Manufacturing
• Lightweight Materials
• +۷ مورد دیگر

Dr. Wenbin Zhou is a Lecturer (Assistant Professor) in Mechanical and Industrial Engineering at the University of Dundee's School of Science and Engineering, where he joined in January 2023. He holds a PhD from Imperial College London's Department of Mechanical Engineering (2015-2019), where his thesis received the Unwin Postgraduate Prize as the best thesis of 2019. Previously, he earned an MSc in Solid Mechanics from Peking University and a BEng in Engineering Mechanics from Huazhong University of Science and Technology. Dr. Zhou's research spans mechanics of materials, sustainable manufacturing, and lightweight structures with applications in aerospace and automotive industries. His work focuses on three main areas: developing novel flexible metal forming techniques (notably the patented Flextrude® technology), designing porous functionally graded materials for aerospace thermal protection systems, and studying diffusion-induced stress in Li-ion battery electrodes for electric vehicles. His research contributes significantly to UN Sustainable Development Goals related to sustainable manufacturing and clean energy. With an h-index of 23 and 1358 citations, Dr. Zhou has published 58 research outputs, showing increasing productivity with 13 publications in 2024 and several more in 2025. His recent work spans sustainable manufacturing, advanced composites, battery technology, and electric vehicles, demonstrating both theoretical depth and practical applications. His publications appear in high-impact journals across materials science and mechanical engineering. Unwin Postgraduate Prize (best thesis, Imperial College London, 2019) The Institute of Physics (IOP) Outstanding Reviewer Awards 2023 & 2024 Materials 2022 Outstanding Reviewer Award The Institute of Physics (IOP) Trusted Reviewer designation Dr. Zhou actively supervises PhD students and has secured research funding including a current project with Shenyang University of Technology on Characterisation Of Anisotropic Behaviour In Aluminium Alloys (2024-2026). He serves on editorial boards for multiple journals including Scientific Reports and Heliyon. His teaching includes Mechanical Engineering Project II (3D Printing) and Thermodynamics I, connecting his research expertise with undergraduate education. He is also involved in innovative sustainability projects, including research on turning whisky waste into compostable packaging.

• Magnetic Resonance Imaging
• Advanced Image Reconstruction
• Quantitative MRI Methods
• +۵ مورد دیگر

Tobias Wood serves as a Senior Lecturer in Magnetic Resonance Imaging within Neuroimaging, leading multiple externally funded research initiatives focused on advancing quantitative MRI methodologies. His primary institutional affiliation remains implied through project leadership but is not explicitly stated in available documentation. Research interests span the full spectrum of Magnetic Resonance Imaging with particular emphasis on advanced image reconstruction techniques and quantitative biomarker development . His work bridges engineering innovation with clinical applications in neurological disorders including multiple sclerosis, Parkinson's disease, and Huntington's disease, while also exploring novel frontiers like the neurocutaneous axis in inflammatory skin conditions. The research fingerprint reveals strong concentration in Myelin Imaging (49%), In Vivo Neuroscience (32%), and Parkinson's Disease research (31%). Recent publications demonstrate consistent output in high-impact journals including Magnetic Resonance in Medicine and Neuropsychopharmacology , with emerging focus on ultra-low-field MRI applications and multi-modal biomarker validation. Key trends include methodological innovation in silent scanning protocols, pediatric coil development, and translation of quantitative techniques to clinical monitoring. Current funding portfolio includes five major projects totaling approximately £2.5M, with leadership roles in EPSRC and CHDI Foundation grants. Collaborative networks span 11 similar research profiles with strong connections to multiple sclerosis research, neurodegenerative disorders, and advanced imaging physics communities. Lab resources include access to high-field MRI systems, specialized computational infrastructure, and clinical validation partnerships. Supervision approach emphasizes interdisciplinary training with strong publication expectations and industry-academic career pathways.

• Flow boiling
• Pool boiling
• Microchannel heat transfer
• +۵ مورد دیگر

Satish Kandlikar is the Gleason Professor of Mechanical Engineering at Rochester Institute of Technology (RIT), where he has been a faculty member since 1980. He is affiliated with the Kate Gleason College of Engineering and the Department of Mechanical Engineering. Previously, he served as faculty at the Indian Institute of Technology in Bombay before joining RIT. Professor Kandlikar's research focuses on flow boiling phenomena, developing ultra-high performance pool and flow boiling heat transfer surfaces, stabilizing flow boiling in microchannels, interface mechanics during rapid evaporation, and advanced chip cooling with single-phase liquid flow. His work has evolved from empirical studies that produced widely accepted correlations for different geometries to fundamental investigations using high-speed photography techniques to understand bubble dynamics. Recently, he has expanded into biomedical applications, particularly using infrared imaging technology for breast cancer detection. His research output shows a clear progression from fundamental boiling mechanisms to practical applications in electronics cooling and biomedical diagnostics. Recent publications (2019-2021) demonstrate continued innovation in surface engineering for boiling enhancement using graphene and other nanomaterials, while simultaneously branching into medical applications of thermal imaging. Scientific Awards: Eisenhart Award for Outstanding from RIT Trustees Scholarship Award from RIT Engineer of the Year Award from Rochester Engineering Society Heat Transfer Memorial Award from the American Society of Mechanical Engineers Professor Kandlikar advises numerous graduate students, with recent publications showing strong student involvement as lead authors. His lab appears well-funded with active research in both traditional thermal engineering and innovative biomedical applications. He has founded significant professional initiatives including the ASME Heat Transfer chapter in Rochester and the E-cubed science and engineering fair for middle school students, demonstrating strong commitment to mentoring and community engagement. His laboratory focuses on experimental thermal science with capabilities in high-speed imaging of bubble dynamics, nanofabrication for surface modification, thermal testing of microchannel systems, and potentially clinical thermal imaging equipment for the biomedical applications. The lab culture appears collaborative, with students taking lead roles in publications and presenting at major conferences.

• Computational mechanics
• Finite element method
• Uncertainty quantification
• +۶ مورد دیگر

Prof. Dr.-Ing. habil. Kai Willner is a distinguished Professor at the Chair of Engineering Mechanics within the Department of Mechanical Engineering at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). His research spans multiple domains of computational mechanics with significant contributions to structural dynamics, uncertainty quantification, and biomechanics. His current work focuses on innovative applications of fuzzy arithmetic in engineering systems and the mechanics of brain tissue. Principal Investigator for SFB 1540 EBM (Erforschung der Mechanik des Gehirns) Lead researcher on multiple DFG-funded projects including polymorphic uncertainty modeling Active participant in international collaborations on structural dynamics Member of the research group FOR 2271 on process-oriented tolerance management Willner's research interests center on computational mechanics with emphasis on uncertainty quantification , fuzzy-stochastic finite element methods , contact mechanics , and brain biomechanics . His work addresses fundamental challenges in modeling systems with uncertain parameters, particularly in heterogeneous materials and biological systems. His research group develops advanced computational frameworks that integrate fuzzy arithmetic with traditional finite element methods to handle epistemic and aleatoric uncertainties simultaneously, with applications ranging from microstructural analysis to brain mechanics. Analysis of his recent publications reveals a strong trend toward interdisciplinary research, particularly at the intersection of computational mechanics and neuroscience. His work on brain mechanics within the SFB 1540 EBM project represents a significant shift toward biomedical applications of traditional mechanical engineering methods. His publications consistently demonstrate expertise in vibration analysis, structural dynamics, and uncertainty quantification, with increasing focus on applying these methods to biological systems and complex material behaviors. Prof. Willner has secured substantial third-party funding from the German Research Foundation (DFG), including multiple collaborative research center (SFB/TRR) projects, research units (FOR), and individual grants. His current major projects include the SFB 1540 EBM (2023-2026) investigating brain mechanics, and continuing work on polymorphic uncertainty modeling in heterogeneous materials. Within the SFB 1540 EBM consortium, Willner leads research on model-based matching of ex vivo and in vivo test data (project X01), focusing on resolving contradictions in mechanical properties of ultraweak brain tissue materials across different testing modalities. His team develops continuum-based simulation models to unify various experimental observations into a coherent mechanical framework for brain tissue.