Find Academic Supervisors

Senthil Balaji GirimuruganView profile

Professor

• High Dimensional Statistics
• Bioinformatics
• Genomics
• +5 more

Senthil Balaji Girimurugan is an Associate Dean of the Honors College at Florida Gulf Coast University (FGCU), holding a Ph.D. in Statistics from Florida State University (2014). His academic focus lies in high-dimensional statistics, wavelet transforms, and their applications in bioinformatics, genomics, and neuroimaging. He teaches advanced statistics and mathematics courses, including Applied Mathematical Statistics and Time Series Analysis. Education: Ph.D., Statistics, Florida State University, 2014 Research Interests: Dr. Girimurugan develops statistical methods for analyzing genomic and neuroimaging data, leveraging wavelet transforms and machine learning. His work includes projects such as the NUPRIME epigenomics initiative and Human Connectome Project neuroimaging analysis. He emphasizes innovative teaching methods like Team-Based Learning and integrates computational tools (Python/R, MySQL) into research. Conference Contributions: Presented on topics including wavelet-based bioinformatics, statistical education innovations, and genomic data segmentation at institutions like Dartmouth College and the Maize Genomics Conference. Labs/Teams: Collaborates with interdisciplinary teams in genomics and computational biology, mentoring over 15 students in research projects across disciplines.

Raymond O. WellsView profile

Professor

• Complex Analysis
• Wavelet Analysis
• Differential Geometry
• +3 more

Raymond O. Wells is a Distinguished Professor of Mathematics at the School of Computer Science & Engineering, Constructor University. Previously, he held roles as Professor of Mathematics and Vice President for External Affairs at Jacobs University Bremen, and served as Professor Emeritus at Rice University. His academic journey includes a BA in Mathematics from Rice University (1962) and a PhD from New York University (1965). His research focuses on complex analysis, wavelet theory, differential geometry, and the history of mathematics. Notable contributions include foundational work on complex manifolds, cohomology in theoretical physics, and applications of wavelet analysis in signal processing. He has authored influential books such as *Differential Analysis on Complex Manifolds* and *Wavelet Analysis: The Scalable Structure of Information*. Wells has received prestigious awards including the Guggenheim Fellowship (1974–1975) and Humboldt Senior Scientist Award. Beyond academia, he has served as President of the Boulder Philharmonic Orchestra and the Boulder Ensemble Theatre Company. His career reflects a blend of mathematical rigor and interdisciplinary engagement, spanning academic leadership, research innovation, and cultural contributions.

Chung Hao ChenView profile

Associate Professor

• Robotics
• Automated Surveillance Systems
• Computer Vision
• +7 more

Dr. Chung Hao Chen is an Associate Professor in the Department of Electrical and Computer Engineering at Old Dominion University (ODU), part of the Batten College of Engineering and Technology. He holds a Ph.D. in Electrical Engineering from the University of Tennessee, Knoxville (2009), and B.S./M.S. degrees in Computer Science and Information Engineering from Fu-Jen Catholic University, Taiwan (1997/1999). Prior to academia, he worked at Panasonic Taiwan Laboratory (2001–2003) and served in the National Military Academy (1999–2001). His research focuses on robotics, automated surveillance systems, computer vision, image processing, intelligent systems, data mining, and network analysis . Notable projects include developing multi-camera tracking systems, UAV-based object retrieval, and dynamic environment testing facilities for watercrafts. He has secured grants such as the NSF-funded 'State of the Art in Target Handoff' (2012–2015). Dr. Chen has published extensively in journals like IEEE Transactions on Image Processing , Computer Vision and Image Understanding , and Physics of Plasmas . His work spans technical areas including plasma chemistry, strain analysis in materials, and sensor fusion. Awards include Sigma Xi membership (2009) and travel grants from IEEE and TECRO. Education: Ph.D., Electrical Engineering, University of Tennessee, Knoxville (2009) M.S., Computer Science & Engineering, Fu-Jen Catholic University (1999) B.S., Computer Science & Engineering, Fu-Jen Catholic University (1997) Affiliations: Old Dominion University (2011–present) North Carolina Central University (2009–2011) He leads efforts in modular robotics, unmanned systems, and intelligent imaging , with applications in security, healthcare, and environmental monitoring. Current openings exist for Ph.D./MS students in computer vision, statistical analysis, and robotics.

• Image Processing
• Computer Science
• Electrical Engineering
• +4 more

Dr. Ayman Elmesalami is a Senior Lecturer and University Distinguished Teacher at Old Dominion University (ODU), where he serves as Undergraduate Program Director in the Computer Science Department. He has extensive teaching experience across institutions in the U.S. and Canada, including Kansas State University, University of Guelph, and McMaster University. His work focuses on project-based learning with Raspberry Pi platforms to enhance undergraduate education. Ph.D. (2004) from Kansas State University His research spans image processing, parallel computing, and education technology, often integrating low-cost hardware for practical applications. Publications highlight Raspberry Pi clusters, color restoration techniques, and societal problem-solving projects addressing parking control, flood detection, and accessibility systems. Notable awards include the University Distinguished Teacher, Teaching with Technology Award, and Faculty Innovator Grant at ODU. He mentors students in projects like Diabetic Foot Exam Systems and COVID-19 Classroom Occupancy Detection , many of which are presented at IEEE and ODU symposiums. STEM Ed. - Project-Based Exploration (2022) ODU Undergraduate Students Addressing... (2022) Movement Controlled Snake Game (2022) Parallelization with a RasPi Cluster (2022) Color Restoration Survey (2019) Dr. Elmesalami leads curriculum development initiatives, advises ACM and Muslim Students Associations at ODU, and contributes to ABET accreditation. His projects frequently involve Raspberry Pi for education, security systems, and societal challenges.

Patrick FlandrinView profile

Researcher

• Signal Processing
• Time-Frequency Analysis
• Wavelet Analysis
• +3 more

Patrick Flandrin is a physicist and senior researcher affiliated with the Department of Physics at École Normale Supérieure de Lyon, where he leads contributions to the SiSyPhe research team within the physics laboratory. His work bridges theoretical signal processing and experimental data analysis across domains including acoustics, mechanics, and biomedical science. His research focuses on time-frequency analysis , wavelet theory , and non-stationary signal processing , developing mathematical frameworks to interpret complex signals where traditional Fourier analysis fails. He explores scale invariance, data-driven analytics, and the application of time-frequency methods to real-world phenomena, often drawing analogies to musical notation for conceptual clarity. Key recognitions include the CNRS Silver Medal and elevation to Fellow of EURASIP (European Association for Signal Processing) in 2009 for pioneering contributions to time-frequency analysis. His theoretical work reconciles quantum-mechanical uncertainty principles with signal processing constraints, advancing methods for multi-component signal decomposition. Flandrin maintains active collaborations across mathematics and engineering disciplines, with emphasis on translating theoretical advances into practical algorithms. His SiSyPhe team operates at the intersection of physics-driven signal analysis and computational innovation, leveraging both experimental data and abstract mathematical modeling.

Maryke van der WaltView profile

Associate Professor

• Data Science
• Computational Harmonic Analysis
• Approximation Theory
• +1 more

Maryke van der Walt is an Associate Professor of Mathematics in the Department of Mathematics and Computer Science at Westmont College. She joined Westmont in 2017 after serving as an assistant professor at Vanderbilt University. Her academic journey spans multiple continents, reflecting her South African origins and international educational background. Her educational background includes: PhD in Applied Mathematics (2015) from University of Missouri-St. Louis MSc in Mathematics (2012) from Stellenbosch University, South Africa BSc in Mathematical Sciences (2009) from Stellenbosch University, South Africa Professor van der Walt's research focuses on applying advanced mathematical techniques to real-world problems, particularly in medical applications. Her work bridges theoretical mathematics with practical implementation, with special emphasis on computational harmonic analysis, approximation theory, and spline theory. She develops mathematical models that have direct applications in signal processing and medical data analysis, creating solutions that can be implemented in real-time systems for healthcare monitoring and prediction. Her publication record demonstrates consistent contributions to applied mathematics, with recent work focusing on diabetic blood glucose prediction using deep learning approaches, real-time spline interpolation techniques, and advanced signal analysis methods. These publications appear in reputable journals including Frontiers in Applied Mathematics and Statistics, Applied Mathematical Sciences, and GEM - International Journal on Geomathematics. Professor van der Walt maintains an active teaching schedule at Westmont College, instructing courses ranging from Calculus and Linear Algebra to specialized topics like Introduction to Subdivision Methods. Her teaching experience spans multiple institutions including Vanderbilt University and the University of Missouri-St. Louis, covering both undergraduate and graduate level mathematics courses.

Stéphane MallatView profile

Professor

• Signal Processing
• Wavelet Theory
• Machine Learning
• +4 more

Stéphane Mallat is a Professor at the Collège de France, holding the Chair of Data Sciences. He is also affiliated with the École normale supérieure in Paris, where his address is located. His research focuses on signal processing, wavelet theory, and their applications in machine learning and data sciences. Mallat pioneered wavelet transforms for signal decomposition and has contributed to scattering transforms for invariant feature extraction in deep learning. His work bridges applied mathematics, harmonic analysis, and computational methods, with impactful applications in image processing, audio analysis, and quantum chemistry. Publicly listed articles span from foundational wavelet theory (1989) to recent advances in scattering networks (2020). His research trends emphasize geometric signal representations, sparse approximations, and interdisciplinary applications across physics and engineering. His CV and publications are available through institutional links, though specific awards or grants are not explicitly detailed in the provided texts. He collaborates extensively with researchers in mathematics and computer science, advancing theoretical frameworks with practical implementations.

• Wavelet Analysis
• Distributed Computing
• Machine Learning
• +5 more

Dixon Vimalajeewa is an Assistant Professor in the Department of Statistics at the University of Nebraska-Lincoln, joining in August 2023. His expertise spans wavelet-based signal processing, distributed computing, and machine learning for complex data applications. PhD in Computer Science (2020), South-East Technological University (SETU), Ireland Postdoctoral Research Associate (2021-2023), Texas A&M University Postdoctoral Researcher (2020-2021), Walton Institute, Ireland Dr. Vimalajeewa develops scalable methodologies rooted in mathematical modeling and machine learning, with applications in agriculture , healthcare , and biomedicine . His work addresses challenges in unstructured data analysis, emphasizing robust theoretical frameworks and statistical guarantees. His recent publications highlight trends in wavelet domain analysis for medical diagnostics, self-similarity metrics in time series modeling, and distributed learning systems for smart agriculture. These align with his interests in biomedical signal processing , IoT , and healthcare analytics . Dr. Vimalajeewa's research bridges computational innovation with real-world applications, focusing on adaptability and scalability in data science solutions.

Jonathan HealeyView profile

Professor

• Fluid Dynamics
• Boundary Layer Instability
• Hydrodynamic Stability
• +3 more

Jonathan Healey is a Professor in the School of Computer Science and Mathematics at Keele University, Department of Mathematics. He holds a DPhil in Physics from Oxford University (1991) and has held academic positions including lectureships at Brunel and Keele Universities, becoming a Reader in 1998. His research focuses on fluid dynamics instabilities, time series analysis, and boundary layer transitions. He has contributed to understanding absolute/convective instabilities and their implications in engineering applications. Educations: Bachelor of Science in Physics, Oxford University, 1987 Doctor of Philosophy (DPhil) in Physics, Oxford University, 1991 (supervised by Tom Mullin and Dave Broomhead) Research Interests: He investigates fluid dynamics phenomena such as boundary layer instability mechanisms, time series analysis for dynamical systems, and the mathematical modeling of convective vs absolute instabilities. His work applies asymptotic methods and numerical techniques to predict transition in laminar-turbulent flows. Teaching: Teaches MAT-10041 (Calculus II) and MAT-30002 (Nonlinear Ordinary Differential Equations). His homepage provides further academic resources. Administration: Serves as Seminar Coordinator within the School. His research group contributes to the Fluid Dynamics and Acoustics theme at Keele.

• OLAP and data warehousing
• data mining
• Sensor/P2P networks
• +8 more

Kotidis Ioannis serves as an Associate Professor in the Department of Informatics at the Athens University of Economics and Business (AUEB). His academic journey began with a Diploma in Electrical and Computer Engineering from the National Technical University of Athens, followed by Master's and Ph.D. degrees from the University of Maryland. His research focuses on several critical areas of database systems and data management, including On Line Analytical Processing (OLAP) and data warehousing, data mining, Sensor/P2P networks, mobile data management, data fusion & dissemination, data streams, RFID data management, approximate query answering, ranking, and database preservation and integration. His work bridges theoretical database concepts with practical applications in emerging technologies. Professor Kotidis' publication record demonstrates consistent contributions to database research over two decades, with notable work in dynamic view management, stream processing, sensor network data management, and more recently, blockchain-based OLAP view management and complex event processing. His research has evolved from traditional data warehousing to address challenges in modern data-intensive applications. best paper award at ACM SIGMOD International Conference on Management of Data for DynaMat paper Throughout his career, Professor Kotidis has supervised numerous students on projects related to database systems, including work on complex event processing, decentralized OLAP view management using blockchains, and graph similarity learning. His research projects include DeLorean (time-series management), RECOST (complex stream management), DBSENSE (wireless sensor networks), and INFORE (extreme-scale analytics). His laboratory work focuses on creating efficient, scalable solutions for data management challenges across various domains, with particular emphasis on making advanced data processing techniques accessible and practical for real-world applications.

• Renewable Energy Systems
• Smart Grid Technology
• Machine Learning Applications in Energy
• +3 more

Goyal Awagan is a researcher affiliated with Northumbria University, contributing to advancements in smart grid technologies and renewable energy systems. His work focuses on hybrid microgrid protection, machine learning applications for energy systems, and distributed energy resource management. Key research themes include fault detection, resilient grid design, and stochastic optimization for virtual power plants. His notable publications explore topics such as protection frameworks for hybrid microgrids, demand response programs leveraging machine learning, and fault detection using LSTM networks. Goyal's research addresses challenges in grid reliability under weather intermittency and communication disruptions. Despite his prolific output, no specific academic awards or student advising roles are explicitly mentioned in the provided texts. His contributions are primarily centered on interdisciplinary energy systems, emphasizing both theoretical and applied aspects of modern power infrastructure.

Michel DiamentView profile

Professor

• Marine geosciences
• Tectonics
• Applied geophysics
• +5 more

Michel Diament is a Professor at the Institut de Physique du Globe de Paris (IPGP), where he has been serving since October 1990. He currently serves as director of the French national data and services centre for Solid Earth (ForM@Ter) since 2015. Throughout his distinguished career, he has held significant leadership positions including Acting Director of the French national institute for Earth Sciences and Astronomy (CNRS-INSU) in 2014 and Scientific deputy director for Solid Earth at CNRS-INSU from 2011 to 2014. His academic journey began as a Lecturer in Geophysics at University Paris-Sud (Orsay) from 1982 to 1990 before advancing to his professorship at IPGP in 1990. Professor Diament's research spans multiple areas of Earth sciences with a particular focus on gravimetry and satellite geodesy . His work integrates geophysical measurements with geological understanding to address fundamental questions about Earth's structure and dynamics. He has made significant contributions to understanding the mechanical behavior of the lithosphere through tectonic studies, and has applied geophysical methods to interpret potential fields in various geological settings. His research extends to volcanology , where he has used temporal gravity measurements to understand volcanic behavior during crises, as demonstrated in his work on Merapi volcano. He has also contributed to marine geosciences , utilizing satellite altimetry data to investigate structural trends in Pacific archipelagoes and the geodynamics of regions like Western Indonesia. Analysis of his publication record reveals a consistent trajectory of research focused on using gravity data and geodetic measurements to understand Earth processes. His work has evolved from structural analysis of Pacific regions in the 1980s to sophisticated satellite-based gravity measurements for studying earthquakes, mantle structure, and volcanic processes in recent decades. A notable pattern is his leadership in integrating multiple data sources and developing methodologies like wavelet transforms for geological boundary characterization. Medal '100 years of international geophysics' of the Geophysical Committee of the Russian Academy of Sciences (2002) Corresponding member of the 'Bureau des Longitudes' (2010) Professor Diament has been deeply involved in academic mentoring and scientific leadership. He has served as thesis adviser or co-adviser for 29 PhD students from various countries including France, Indonesia, Brazil, Cameroon, Tunisia, and Chile since 1986. Additionally, he has advised 6 post-doctoral researchers and served on 111 PhD committees across France, the UK, Ireland, and Cameroon. His leadership extends to numerous scientific committees including the IODP-ECORD Council, the European Space Agency's Earth Science Advisory Committee, and various committees of the French space agency CNES. He directs the French national data and services centre ForM@Ter, which focuses on Solid Earth data, and has been involved with the EPOS TCS 'satellite data' initiative since 2015. His editorial roles include serving as Editor of Geophysical Journal International (2008-2011) and on the editorial board of Tectonophysics (2002-2011), demonstrating his commitment to advancing scientific communication in his field.

• Computer Sciences
• Biomedical Engineering
• Electrical and Electronics Engineering
• +7 more

Lecturer Furkan Balci is affiliated with the Faculty of Technology at Gazi University, specifically within the Electrical and Electronics Engineering Department. His academic positions include membership in the Department's Research and Development Commission, Infrastructure and Planning Commission, and Internship Committee. He holds a Doctorate from Ankara University (in progress), a Postgraduate degree from Nuh Naci Yazgan University (2023-2025), and multiple other qualifications including an undergraduate degree in Electrical and Electronics Engineering from Erciyes University (2015-2018). His research focuses on interdisciplinary areas such as biomedical engineering, machine learning applications in signal processing, and deep learning for medical diagnostics. Specific interests include EEG-based biometric authentication systems, tumor classification using neural networks, and computer vision for infrastructure monitoring. He has contributed to over a dozen peer-reviewed publications, including SCI-Expanded indexed articles on topics like melanoma detection and hybrid learning models for atrial fibrillation detection. Dr. Balci has led or collaborated on six funded projects with TUBITAK, including initiatives on AI-driven target detection systems, optimization algorithms for electromagnetic launchers, and biometric identification via vein pattern analysis. His teaching activities include Python programming courses for certificate programs since 2021. His work bridges theoretical advancements with practical applications in healthcare technology and engineering systems.

• Numerical Analysis
• Optimization on Manifolds
• Riemannian Geometry
• +3 more

Ronny Bergmann is an Associate Professor at the Department of Mathematical Sciences, Norwegian University of Science and Technology (NTNU) since March 2021. Previously, he held research positions at TU Chemnitz (2018–2021) and TU Kaiserslautern (2013–2018), where he completed his habilitation in 2018. He earned his PhD in 2013 from Universität zu Lübeck under the supervision of Jürgen Prestin. His research focuses on numerical optimization on Riemannian manifolds, geometric computing, and manifold-valued data analysis. Key contributions include the development of the Manifolds.jl and Manopt.jl packages in Julia, which provide frameworks for optimization and data analysis on manifolds. He also works on applications in imaging, inverse problems, and geometric inverse methods. Recent work emphasizes non-smooth optimization on manifolds, Fenchel duality in non-Euclidean spaces, and geometric algorithms for shape analysis. His publications span journals like SIAM Journal on Scientific Computing , Journal of Optimization Theory and Applications , and Applied and Computational Harmonic Analysis . Bergmann teaches courses such as TMA4125 Mathematics 4N and actively promotes reproducible research through tools like Quarto. He collaborates on projects involving Lie groups, mesh denoising, and geometric deep learning.

Sina Rezaei GomariView profile

Associate Professor

• Carbon Capture, Storage, and Utilisation
• Hydrogen Production, Transportation, and Storage
• Geological Hydrogen Storage
• +7 more

Dr. Sina Rezaei Gomari is an Associate Professor of Research in Energy and Environmental Engineering at Teesside University, leading the Energy Lab. He holds a PhD in Wettability Alteration from the University of Stavanger and over 12 years of industry experience with the National Iranian Oil Company and Statoil (Equinor). His research focuses on carbon capture and storage (CCS), hydrogen technologies, fluid flow in porous media, and digitalization using AI/ML. He directs multiple international projects, including the £7.6M MEVOCRETE initiative for net-zero concrete and the StoreH2Safe project for hydrogen storage safety. Key roles include Editor-in-Chief of journals, External Examiner at Coventry and Robert Gordon Universities, and Chartered Engineer with the Energy Institute. His work bridges academia and industry through partnerships with firms like Scott Bros Ltd and Material Evolution Ltd. Education: PhD (2006, University of Stavanger), MSc (2003, NTNU Norway), BSc (1996, Petroleum University of Technology). Research Interests: Carbon Capture, Utilization, and Storage (CCUS) Hydrogen Production/Storage Geological Storage Solutions Fluid Flow in Porous Media AI-Driven Energy Systems Waste Valorization via Geopolymers and Clay Minerals Funding: Principal Investigator for projects totaling over £8M from Innovate UK, Qatar NPRP, Saudi Arabia, and industry partners. Notable grants include £7.6M MEVOCRETE (concrete innovation), £263K Dauson Environmental Group (low-carbon materials), and £271K Digital Soil Carbon MRV system. Awards & Recognition: Chartered Engineer (Energy Institute), Editor-in-Chief roles, and leadership in global initiatives like the EAGE Geochemistry Committee. Lab Facilities: Advanced core analysis labs supporting industry partnerships, including hydraulic fracturing studies and multiphase flow experiments.