جست‌وجوی استاد و پژوهشگر

Hermina Alajbegovićمشاهده پروفایل

دانشیار

• Mathematics
• Graph Theory
• Cryptography
• +۳ مورد دیگر

Hermina Alajbegović is an Associate Professor at the Department of Mathematics and Informatics, Faculty of Mechanical Engineering, University of Zenica. She holds a Ph.D. in Mathematics from the University of Sarajevo, focusing on crystallographic groups and subgroup growth. Her career includes roles as an assistant (2003–2008) and postgraduate studies in Algebra (2003–2008). She has authored over 20 publications, spanning graph theory, cryptography, and mathematical software applications like Mathematica and GAP. Education: B.Sc. in Mathematics & Computer Science (2003), M.Sc. in Algebra (2008), Ph.D. in Mathematics (2016). Research interests include algebraic structures, graph theory applications, and mathematical software tools. Notable works involve quasi-regular graph constructions, divisor problem asymptotics, and zeta function analyses in crystallographic groups. She has developed educational tools like web applications for modular arithmetic and interactive e-learning modules using PowerPoint for quiz design. Her publications reflect a blend of theoretical mathematics and practical applications, with recent focus on graph theory and subgroup growth analysis. She actively contributes to academic software integration and problem-solving methodologies in mathematics education.

Fatih Ayhanمشاهده پروفایل

دانشیار

• International Economics
• Environmental Economics
• Energy Economics
• +۳ مورد دیگر

Fatih Ayhan is an Associate Professor at the Faculty of Economics and Administrative Sciences, Department of Economic Development and International Economics, at Bandirma Onyedi Eylul University. His research focuses on international economics, environmental economics, energy economics, and macroeconomic policies . He has held significant administrative roles including Department Head, Vice Dean, and coordinator for Erasmus and Mevlana exchange programs. His academic contributions include over 40 peer-reviewed articles, 12 book chapters, and editorial roles in journals like Journal of Empirical Economics and Social Sciences . Notable awards include Best Work and Best Presentation at international conferences. He advises PhD and master's students on topics like technological change impacts, economic growth determinants, and environmental policy linkages. His teaching spans International Economics , Macroeconomic Analysis , and EU Economy across undergraduate, graduate, and doctoral levels. Research highlights include analyses of energy transition strategies, climate policy effectiveness, and asymmetric relationships between economic factors and environmental degradation. His work bridges theoretical frameworks with empirical evidence, emphasizing policy applications in emerging and developed economies. Administrative Roles: Department Head (Bandirma Onyedi Eylul University), Erasmus Coordinator, Vice Dean Editorial Work: Journal of Empirical Economics and Social Sciences , Management and Economics Research Grants & Projects: Organized international conferences on modern society transformations and global economic challenges Lab/Teams: Active in interdisciplinary research groups focusing on sustainability, energy economics, and macroeconomic modeling

• Entrepreneurship
• Environmental Economics
• Business Administration
• +۳ مورد دیگر

Assoc. Prof. Dr. BURAK ERKUT is the Chair of the Department of Business Administration at Eastern Mediterranean University (EMU), Faculty of Business & Economics. He holds a PhD in Economics and Business Administration from Dresden University of Technology (2018), an MS in Economics from Leipzig University (2014), and a BS in Economics and Management Science from Leipzig University (2012). His research focuses on entrepreneurship, environmental economics, innovation, and econometric analysis of regional development. Key research interests include sustainable management practices, renewable energy policy, corporate entrepreneurship, and the intersection of technology and economic systems. He has supervised numerous PhD and Master’s theses on topics like entrepreneurial activity in Turkey, artisan entrepreneurship in Cyprus, and digital innovation trends. Prof. Erkut’s publications highlight empirical analyses of ecological footprints, financial integration in Asia, and gender dimensions in creative industries. His work often employs panel data and wavelet coherence methods to explore complex economic relationships. He currently advises ongoing PhD research on mining economies’ sustainability and dark tourism in Maraş. Academically, he contributes to EMU’s Nicosia programs in Business Management and Financial Economics. His professional activities include editorial roles and participation in international conferences on entrepreneurship and sustainable development.

Elena Hadzievaمشاهده پروفایل

استاد

• Fractal Geometry
• Iterated Function Systems
• Computer Aided Design
• +۴ مورد دیگر

Elena Hadzieva, PhD, is a Full Professor and currently serves as Dean of the Faculty of Information Systems, Visualization, Multimedia and Animation at the University of Information Science and Technology ‘St. Paul the Apostle’ in Ohrid, North Macedonia. She holds a PhD in Mathematics from the University ‘Ss. Cyril and Methodius’ (Skopje) with a thesis on Iterated Function Systems. Her academic journey includes roles from Assistant Professor (2004) to Associate Professor (2015) before attaining Full Professor status in 2020. Education: PhD in Mathematics (2009), University ‘Ss. Cyril and Methodius’, Skopje MSc in Mathematics (2004), University ‘Ss. Cyril and Methodius’, Skopje BSc in Mathematics (1999), University ‘Ss. Cyril and Methodius’, Skopje Research focuses on Fractal Geometry, Dynamical Systems, and Educational Mathematics, with contributions to software applications for fractal modeling and interdisciplinary STEM education. Recent work addresses medical imaging challenges, pandemic-era online teaching, and analog circuit design. Her articles reflect multidisciplinary engagement: combining fractal analysis with medical diagnostics (e.g., melanoma detection), developing educational tools for 3D fractals, and analyzing pandemic-era pedagogical innovations. She also contributes to electrical engineering through low-power amplifier designs and fault-tolerant systems. Professional roles include Membership in the American Mathematical Society (AMS), Macedonian Mathematical Society, and leadership in CEEPUS networks (e.g., Active Methods in Teaching Mathematics). She serves as National Contact Point for SEFI’s Mathematics Working Group and Editor of the journal Numerus. Her administrative leadership includes coordinating national STEM education initiatives and managing interdisciplinary academic programs. She has pioneered software tools for fractal visualization and contributed to defense technology via IR imaging research.

Brett Wickمشاهده پروفایل

استاد

• Complex Analysis
• Harmonic Analysis
• Operator Theory
• +۳ مورد دیگر

Brett D. Wick is a Professor of Mathematics at Washington University in St. Louis, specializing in analysis with a focus on complex analysis, harmonic analysis, and operator theory. He holds a PhD from Brown University and has been recognized with prestigious awards including the NSF CAREER Award and the Alexander von Humboldt Fellowship. His research explores interactions between these fields, particularly extending results from complex and harmonic analysis to higher dimensions and addressing the Corona Problem in multiple variables. Education: PhD in Mathematics from Brown University. Research interests include several complex variables, operator theory, and multi-parameter harmonic analysis. He has contributed to studies on Riesz transforms, paraproducts, and weighted inequalities, with applications to quasiregular maps and functional spaces. Wick organizes conferences and collaborates internationally, appearing at events like the International Workshop on Operator Theory (IWOTA) and the Banff International Research Station. Scientific Awards: Fellow of the American Mathematical Society, Alexander von Humboldt Fellow, NSF CAREER Award, Jerrold E. Marsden Postdoctoral Fellow. Grants and Funding: His work is supported by the National Science Foundation. Collaborations involve researchers globally, focusing on topics like Schatten classes, commutators, and function spaces. Labs/Teams: Active in the Washington University Analysis group and collaborates with international teams on operator theory and harmonic analysis projects.

Mladen Victor Wickerhauserمشاهده پروفایل

استاد

• Harmonic Analysis
• Wavelets
• Numerical Algorithms
• +۴ مورد دیگر

Mladen Victor Wickerhauser is a Professor of Mathematics and Biomedical Engineering at Washington University in St. Louis. He holds a B.S. from the California Institute of Technology and M.S./Ph.D. from Yale University. His research focuses on Harmonic Analysis, Wavelets, Numerical Algorithms, and their applications in Biomedical Engineering, Medical Imaging, and Financial Mathematics. He has over 1,000 publications, six U.S. patents—including a FBI fingerprint compression algorithm—and received the 2002 Wavelet Pioneer Award from SPIE. Education: B.S. with Honor in Mathematics, California Institute of Technology (1980) M.S. and Ph.D. in Mathematics, Yale University (1982, 1985) Research Highlights: Dr. Wickerhauser’s work bridges mathematical theory and practical applications. His contributions include entropy-based signal processing for medical imaging, wavelet algorithms for data compression, and financial mathematics textbooks. His patents cover medical treatment planning and signal enhancement techniques. Awards & Grants: Wavelet Pioneer Award (SPIE, 2002) NSF grants for computational harmonic analysis and wavelet algorithms Students & Collaborations: He has advised PhD students like David Meyer and Wojciech Czaja. Collaborators include experts in biomedical engineering, signal processing, and medical physics. His lab focuses on molecular imaging and entropy-based diagnostics.

• Radio Astronomy
• Medical Imaging
• Compressed Sensing
• +۳ مورد دیگر

Yves Wiaux is a Professor at Heriot-Watt University's School of Engineering & Physical Sciences, affiliated with the Institute of Sensors, Signals & Systems. He specializes in advanced signal processing techniques with applications in radio astronomy and medical imaging. His research focuses on compressed sensing, optimization algorithms, and imaging methods for radio interferometry and MRI. His work integrates mathematical frameworks like wavelet transforms and sparse regularization to address challenges in high-dimensional data reconstruction. Notable contributions include the development of algorithms like SARA (Sparsity Averaging Reweighted Analysis) and PURIFY for radio interferometric imaging, as well as applications in medical imaging such as magnetic resonance fingerprinting. Wiaux collaborates extensively in international projects, including the LOFAR Two Meter Sky Survey. He advises PhD students through the BASP (Biomedical and Astronomical Signal Processing) group and leads research initiatives in scalable imaging techniques for large datasets.

Prashan Premaratneمشاهده پروفایل

مدرس ارشد

• Computer Vision
• Pattern Recognition
• Image Processing
• +۴ مورد دیگر

Prashan Premaratne is a Senior Lecturer at the University of Wollongong's School of Electrical, Computer and Telecommunications Engineering, where he has been affiliated since 2003. His academic qualifications include a Doctor of Philosophy in Image/Signal Processing from the National University of Singapore (1999-2001), a Bachelor of Engineering in Optical Communications and Signal Processing from the University of Melbourne (1994-1997), and a Graduate Certificate in Higher Education from the University of Wollongong (2008-2009). His research focuses on: Computer vision systems for gesture recognition and object detection Advanced image/video processing techniques including steganography Artificial intelligence applications in speech processing and sensor networks Energy system optimization through electromagnetic modeling His publications demonstrate strong focus on computer vision (45%), signal processing (30%), and AI applications (25%), with recent work emphasizing real-time systems optimization and deep learning architectures. Award recognition includes: Vice Chancellor's Award for Teaching Excellence (2020) IEEE Senior Member recognition (2008) Singapore Science Award (1999) He actively supervises graduate researchers in computer vision and AI, with 11 completed PhD/MPhil students. Grant funding includes internal university awards for robotics education and face detection technology. He serves as program chair for major AI conferences and reviews for national research councils.

• Financial Risk Management
• Climate Science and Modeling
• Actuarial Science
• +۵ مورد دیگر

Samuel Gyamerah is a Postdoctoral Fellow at the University of Waterloo under the supervision of Ruodu Wang and Alex Schied, active from September 2023 to 2025. His research focuses on interdisciplinary applications of quantitative methods in finance, climate science, and actuarial science. Key areas include stochastic modeling of weather derivatives, systemic risk analysis in banking networks, and machine learning-driven predictive analytics in healthcare and agriculture. Education: Samuel holds prior academic affiliations with Kwame Nkrumah University of Science and Technology, as indicated by his 2014 research contributions. His work bridges theoretical advancements with practical solutions, such as optimizing crop yield forecasts and mitigating financial risks through innovative modeling techniques. Research Trends: His publications highlight a strong emphasis on climate-related financial instruments, geopolitical risk transmission, and the integration of advanced statistical methods (e.g., wavelet coherence, hybrid machine learning models) into diverse fields. Notable contributions include frameworks for longevity bond pricing under geopolitical volatility and state-space models for long-term bond valuation. Advising & Grants: While no formal advisees are listed, his postdoctoral work suggests active collaboration in grant-funded projects exploring systemic risk, green bonds, and agricultural resilience. His research has been applied to real-world challenges like Ghana’s National Health Insurance Scheme and SME digital transformation strategies. Labs/Teams: Engaged in collaborative projects at the intersection of finance, climate science, and data science, likely contributing to interdisciplinary research groups at the University of Waterloo.

• Mathematical Analysis
• Complex Functions
• Signal Processing
• +۳ مورد دیگر

Dr. Abdelbaset Zeyani is an Assistant Teaching Professor at Wichita State University's Fairmount College of Liberal Arts and Sciences, affiliated with the Department of Mathematics and Statistics. He specializes in mathematical analysis and signal processing, with a focus on polynomial-based function theory and advanced signal separation techniques. His research interests span: Mathematical Analysis Complex Functions Signal Processing Polynomials Functional Analysis Applied Mathematics Dr. Zeyani's publications examine bi-univalent functions through Gegenbauer and Lucas-balancing polynomials, addressing coefficient estimation and Fekete-Szegö functionals. His work also explores signal processing innovations like synchrosqueezing transforms and wavelet analysis for instantaneous frequency estimation and signal separation.

Sugata Banerjiمشاهده پروفایل

دانشیار

• Computer Vision
• Scene Understanding
• Machine Learning
• +۳ مورد دیگر

Sugata Banerji is an Associate Professor of Computer Science at Lake Forest College and Director of the Applied Data Center. His research focuses on computer vision, scene understanding, and machine learning, with applications in medical imaging and image retrieval. He holds a PhD in Computer Science from New Jersey Institute of Technology (2013) and a Postdoctoral fellowship in Computer Vision at George Mason University (2013–present). His educational background also includes a BE in Information Technology from West Bengal University of Technology. Research Interests include image processing, pattern recognition, and novel descriptors for object and scene classification. His work spans deep learning for medical diagnostics, efficient feature extraction methods like EFM-HOG, and geo-localization of buildings using computer vision. He has received the Department of Computer Science Travel Award (2012) and served as a Teaching Assistant (2008–2013). Key contributions include advancements in HOG descriptor variants (e.g., HaarHOG), color-based feature integration, and solar energy growth modeling. He teaches courses such as Roadmap to Computing with Python and Introduction to Computer Science, emphasizing practical programming and graphics problem-solving.

Sixin Zhangمشاهده پروفایل

دانشیار

• Machine Learning
• Optimization
• Signal Processing
• +۷ مورد دیگر

Sixin Zhang is an Associate Professor at INP-Toulouse, specifically affiliated with the ENSEEIHT school. He holds a Ph.D. from the Courant Institute of Mathematical Sciences, New York University (2012), following undergraduate studies. His postdoctoral research spanned institutions including ENS Paris, Peking University, and IRIT in France. His research focuses on machine learning, optimization, signal/image processing, statistics, dynamical systems, and high-dimensional data analysis. Key research areas include representation learning for recognition and inverse problems, optimization algorithms, and applications in industrial systems and astrophysics. He contributed to the development of the Kymatio library for scattering transforms and co-authored foundational work on transform learning in non-negative matrix factorization. His work bridges theoretical mathematics with applied machine learning, including contributions to generative models, data assimilation networks, and optimization techniques for neural networks. Notable projects include the MeteoNet AI challenge and the RWST statistical framework for interstellar medium analysis.

• Statistical and Machine Learning
• Applied and Computational Harmonic Analysis
• Financial Mathematics
• +۳ مورد دیگر

Frederick Warner, PhD, is an Associate Research Scientist at Yale School of Medicine and a member of the Center for Outcomes Research and Evaluation (CORE). His research focuses on statistical and machine learning, computational harmonic analysis, and financial mathematics. He holds a PhD in Mathematics from Yale University (1992). Previously, he worked at Plain Sight Systems and served as a Senior Research Scientist and Lecturer in Yale’s Department of Mathematics. Dr. Warner’s research interests span interdisciplinary domains, including applications of advanced mathematical techniques to healthcare challenges. Notable collaborations include work with Professors Ronald Coifman (Mathematics), Akiko Iwasaki (Immunobiology), and Harlan Krumholz (Cardiology). His recent studies address Long COVID’s clinical manifestations, cardiovascular health disparities, and vaccine efficacy against SARS-CoV-2 variants. He also contributes to methodological advancements in hyperspectral data analysis and health informatics. Key affiliations include the Cardiovascular Medicine Department and the Yale LISTEN Research Cohort. His work bridges mathematical rigor with clinical and public health applications, emphasizing translational outcomes and data-driven solutions.

Katrina Nevilleمشاهده پروفایل

مدرس ارشد

• Electrical and Electronic Engineering
• Communications Technologies
• Artificial Intelligence
• +۳ مورد دیگر

Dr. Katrina Neville is a Senior Lecturer in the School of Engineering at RMIT University, Australia. Her research focuses on interdisciplinary areas including electrical engineering, communications, artificial intelligence, image processing, and educational technology. She actively supervises research projects in robotics, stroke rehabilitation, and signal processing. Her work bridges theoretical advancements with practical applications in healthcare technology and manufacturing systems. Research Interests: Electrical/Electronic Engineering, Communications Technologies, AI & Image Processing, and Education Technology. Teaching expertise spans signal processing, speech processing, and communication systems. She has published extensively in journals like IEEE Transactions and conferences such as SigTelCom and ICCE. Supervision Projects: Includes topics like collaborative robotics programming, post-stroke motor function recovery via VR/motor imagery, and wind noise reduction mechanisms. She has advised projects ranging from neural network applications in image recognition (2015) to advanced OFDM systems (2008). Labs/Teams: While specific lab affiliations aren’t listed, her research collaborations involve interdisciplinary teams working on biomedical informatics, robotics, and educational technology innovations.

Golnoush Abaeiمشاهده پروفایل

مدرس

• Software Engineering
• Machine Learning
• Artificial Intelligence
• +۵ مورد دیگر

Dr. Golnoush Abaei is a Lecturer in Industry Practice at RMIT University's School of Computing Technologies. She holds dual roles as Professional Practice Lead (since 2022) and Program Manager for the Bachelor of Software Engineering (since 2023). Her expertise bridges academia and industry, focusing on software engineering, machine learning, and data analytics. She coordinates the Software Testing Course and supervises capstone projects for software engineering undergraduates and IT postgraduates. Research interests include software quality, INS/GPS navigation systems, health-related recognition applications, and blockchain. Notable projects involve AI-powered digital lecturer twins for education and machine learning-driven visual defect detection in software interfaces. Teaching methodologies emphasize collaborative active learning (CAL), problem-based learning (PBL), and curriculum design innovation. She actively supports student internships and graduate job placements through industry partnerships. Over 25 peer-reviewed articles span topics like anomaly detection in IoT networks, medical image processing, and hybrid optimization algorithms. Key Projects: Machine Learning for Testing, AI in Education, BDD Test Automation Grants/Industry Collaboration: Multiple industry-sourced capstone projects Curriculum Development: PBL integration, CAL frameworks, and active learning strategies