جست‌وجوی استاد و پژوهشگر

Rafe Jonesمشاهده پروفایل

استاد

• Number Theory
• Arithmetic Dynamics
• Algebra
• +۳ مورد دیگر

Rafe Jones is a Professor of Mathematics and Chair of the Department of Mathematics and Statistics at Carleton College. He holds a PhD from Brown University and has held academic positions including a postdoctoral fellowship at the University of Wisconsin-Madison and faculty roles at College of the Holy Cross before joining Carleton in 2012. His research focuses on number theory, arithmetic dynamics, and algebraic structures, with particular interest in iterative processes, prime distribution in sequences, and Galois theory. Jones also engages in mathematical exposition and writing for public audiences, including op-eds in the Minneapolis Star-Tribune on topics like mathematics in everyday life and historical numeral systems. His teaching spans undergraduate courses such as Calculus, Linear Algebra, Abstract Algebra, and independent studies. Jones emphasizes creative problem-solving and the aesthetic aspects of mathematics, often incorporating student collaboration in research projects. He has advised student research groups, including a notable project on Shabat polynomials and combinatorial structures. Research publications highlight contributions to arithmetic dynamics, including studies on polynomial iterations, Galois representations, and the distribution of primes in dynamical sequences. His work bridges pure mathematics with pedagogical innovation, reflecting a commitment to both academic rigor and accessible communication of mathematical ideas.

Amr Alanwar Abdelhafezمشاهده پروفایل

استاد مدعو

• Cyber-Physical Systems (CPS)
• Privacy-Preserving Techniques
• Reachability Analysis
• +۵ مورد دیگر

Amr Alanwar Abdelhafez is an Adjunct Professor of Computer Science at Constructor University Bremen’s School of Computer Science & Engineering. Previously, he held Assistant Professor roles at Technical University of Munich (Heilbronn Campus) and Jacobs University Bremen. His research focuses on Cyber-Physical Systems (CPS), emphasizing safety, privacy, and formal verification. He earned his Ph.D. from TU Munich’s Cyber-Physical Systems Group (2020), with prior roles including postdoc at KTH Royal Institute of Technology and research positions at UCLA and University of Waterloo. Education: Ph.D. in Cyber-Physical Systems, Technical University of Munich (2015–2020) M.Sc. in Engineering Science (Protection and Detection Hardware Trojan), Ain Shams University (2010–2013) B.Sc. in Computer and Control Systems Engineering, Ain Shams University (2005–2010) Research Interests: His work bridges theoretical foundations and practical applications in CPS, including privacy-preserving state estimation, resilient control systems, reachability analysis, and formal verification for autonomous systems. He develops methods to ensure safety and privacy in distributed systems, leveraging tools like zonotopes and homomorphic encryption. Key Contributions: Developed logical zonotopes for efficient representation of discrete systems. Advanced event-triggered control and diffusion strategies for distributed systems. Pioneered privacy-preserving techniques (e.g., CryptoImg, PrOLoc) using homomorphic encryption. Contributed to safety-critical applications like autonomous vehicle situational awareness and secure sensor networks. Awards & Recognition: Best Demonstration Paper Award at IPSN/CPSWeek 2017 Qualcomm Innovation Fellowship finalist (2017 and 2018) First place in TUM Graduate School Competition (2019) Grants & Industry Links: His work is supported by collaborations with institutions like IBM and JetBrains, and his open-source tools (e.g., Event-Triggered Diffusion Kalman Filters, Logical-Zonotope repository) are widely used in CPS research. Labs & Teams: Leads research on CPS safety and privacy at TU Munich, with active contributions to Constructor University’s CPS initiatives and GitHub repositories showcasing implementations of his methodologies.

Ann Wallaceمشاهده پروفایل

استاد

• Mathematics Education
• Early Childhood Education
• Educational Technology
• +۳ مورد دیگر

Dr. Ann Wallace is a Professor in the Department of Middle, Secondary & Mathematics Education at James Madison University's College of Education. She holds a B.S. from the University of Georgia, an M.S. from Portland State University, and a Ph.D. in Mathematics Education from the University of Maryland. Her professional interests include professional development for educators, mathematics coaching, and fostering conceptual understanding in mathematics teaching. Wallace began her career as a fifth-grade teacher in Georgia, evolving from procedural-focused instruction to emphasizing conceptual learning. Her research focuses on integrating technology in early childhood mathematics education, innovative teaching methods, and inquiry-based learning. Notable contributions include the NSF-funded Project Inquiry and work on problem-solving strategies in elementary classrooms. Her publications span topics from educational technology to STEM interdisciplinary approaches, reflecting a commitment to both pedagogical innovation and practical classroom applications. While no formal awards are listed, her extensive scholarship underscores her impact in mathematics education reform.

Laura Taalmanمشاهده پروفایل

استاد

• Algebraic Geometry
• Knot Theory
• Game and Puzzle Analysis
• +۴ مورد دیگر

Laura Taalman is a Professor in the Department of Mathematics & Statistics at James Madison University (JMU), where she has been since 2000. She holds a PhD in Mathematics from Duke University (2000), an MA in Mathematics from Duke (1997), and a BS in Mathematics from the University of Chicago (1994). Her research spans algebraic geometry, knot theory, graph theory, and the algebraic/combinatorial analysis of games and puzzles. Recently, her work focuses on computational generative design for 3D printing, coding for interactive mathematical exploration, and procedural design. She is also an author of nationally-published calculus textbooks and puzzle books. Dr. Taalman’s teaching includes general education courses (e.g., MATH 103, ISCI 104), STEM calculus (MATH 231-232), and pure math courses like Discrete Mathematics (MATH 245) and Graph Theory (MATH 353). Her service contributions include leading the JMU Haynes Scholars RLC program, directing the JMU Experimental Mathematics Lab (JEM Lab), and managing the JMU 3SPACE Classroom. She participates in initiatives like the Illustrating Mathematics Steering Committee. Her publications blend theoretical mathematics with applications in art and design, such as modeling dynamical systems for 3D printing and analyzing Celtic knot designs. Recent work emphasizes interdisciplinary connections between mathematics, art, and technology, reflecting her commitment to innovative pedagogy and public-facing scholarship. Professional activities include organizing conferences (e.g., Bridges Conferences) and contributing to outreach programs. Her research and teaching highlight a dual focus on foundational mathematics and creative, applied problem-solving.

Ayad Barsoumمشاهده پروفایل

دانشیار

• Cybersecurity
• Cloud Computing
• Data Integrity
• +۵ مورد دیگر

Ayad Barsoum is an Associate Professor of Computer Science at St. Mary's University, where he serves as the Graduate Program Director of Cybersecurity and Director of the NSA/DHS Designated Center for Cyber Excellence. He joined the university in 2013 and has been instrumental in developing the Master of Science in Cybersecurity program. His leadership secured grants from the Hearst Foundation and Valero Energy Foundation to establish the cybersecurity lab. He holds a Ph.D. from the University of Waterloo (2013), M.S. from Ain Shams University (2004), and B.S. from Ain Shams University (2000). His research integrates cybersecurity, cloud computing, data integrity, and machine learning, with a focus on practical solutions for network security and cryptographic protocols. His publications concentrate on cloud security, network protocols, and machine learning applications in cybersecurity, demonstrating consistent innovation in defensive cyber techniques. Awards: Distinguished Faculty Award (2022-2023) Amazon Web Services Education Grant Multiple research awards from University of Waterloo He serves as a reviewer for NSA CAE-CD and editorial boards, while maintaining collaborations with the Centre for Applied Cryptographic Research.

• Noncommutative Geometry
• Algebraic Geometry
• Number Theory
• +۶ مورد دیگر

Igor Nikolaev, Ph.D. is an Associate Professor in the Department of Mathematics and Computer Science at St. John's College of Liberal Arts and Sciences, St. John's University. His research focuses on noncommutative geometry, algebraic geometry, and number theory, with significant contributions to topics such as K-theory, elliptic curves, and operator algebras. His work bridges pure mathematics disciplines, exploring connections between algebraic, geometric, and dynamical systems. Key research areas include the study of noncommutative tori, arithmetic geometry, and applications of noncommutative geometry to number theory. Recent publications address quantum dynamics of elliptic curves, trace cohomology, and Artin L-functions. While no specific awards are listed, his active publication record indicates sustained scholarly engagement. He has advised no students in the provided data. His academic profile reflects a commitment to advancing theoretical mathematics through interdisciplinary approaches.

Christoph Koutschanمشاهده پروفایل

استاد پژوهشی

• Computer Algebra
• Algorithmic Combinatorics
• Symbolic Summation
• +۳ مورد دیگر

Christoph Koutschan is a Senior Fellow in the Symbolic Computation group at the Johann Radon Institute for Computational and Applied Mathematics (RICAM), Austrian Academy of Sciences. He holds a PhD in Mathematics from JKU Linz (2009) and a Habilitation in Mathematics (2017). His research focuses on computer algebra, algorithmic combinatorics, and symbolic summation/integration of holonomic functions. Koutschan has held positions at Tulane University (2009–2010), Tulane University (2009–2010), and INRIA (2011–2012) before joining RICAM in 2012. Education: PhD in Mathematics (2009), Research Institute for Symbolic Computation (RISC), JKU Linz Habilitation in Mathematics (2017), JKU Linz M.Sc. in Computer Science (2005), FAU Erlangen-Nürnberg Studies in Computer Science (1999–2005), FAU Erlangen-Nürnberg Research Interests: Koutschan's work revolves around symbolic computation with a focus on holonomic functions, combinatorial identities, and applications in mathematical physics. His tools include algorithmic methods for summation/integration, differential equations, and computational algebra. Publications & Awards: Over 40 journal articles, including work on determinant evaluations, Feynman amplitudes, and combinatorial enumeration. Notable awards include the David P. Robbins Prize (2016), ISSAC's Distinguished Software Presentation Award (2016), and the ACA Early Researcher Award (2021). Grants & Collaborations: Lead or co-PI in projects like 'Certificate-free Summation and Integration' (SFB F50, 2017–2021) and 'Security and Safety for Shared AI' (FFG COMET-K2, 2020–2023). Active in editorial roles at Journal of Symbolic Computation and Annals of Combinatorics . Labs/Teams: Core member of RICAM's Symbolic Computation group, collaborating internationally with institutions like INRIA, Tulane University, and TU Wien.

• Machine Learning
• Deep Learning
• Computer Vision
• +۳ مورد دیگر

Akshay Rangamani is an Assistant Professor in Data Science at the New Jersey Institute of Technology (NJIT). His research focuses on deep learning theory, neural network dynamics, generalization bounds, and optimization algorithms. He explores topics such as neural collapse, low-rank layers in neural networks, and the interplay between architecture design and performance. His work bridges theoretical insights with practical applications in signal processing, computer vision, and recurrent network analysis. Notable contributions include studies on skip connections enhancing associative memory capacity, weight decay effects on neural collapse, and generalization guarantees for interpolating kernel machines. Rangamani has published widely in top conferences and journals, with over 190 citations and an h-index of 19. His research has been highlighted in media outlets, emphasizing advancements in understanding deep classifier dynamics and neural network training mechanisms.

Sophie Soury-Lavergneمشاهده پروفایل

دانشیار

• Mathematics Education
• Dynamic Geometry Environments
• Technology in Primary Education
• +۴ مورد دیگر

Sophie Soury-Lavergne is an Associate Professor at the French Institute of Education (Institut français de l'Éducation) within École Normale Supérieure de Lyon. She holds an HDR (Habilitation à Diriger des Recherches) and has been actively involved in research since 1998. Her primary roles include: Research Fellow at the S2HEP Laboratory ESPE lecturer at the Grenoble Academy since 2014 Member of national and international educational projects like Intergeo and OCINAEE Education Background: PhD in Mathematics Didactics (1998) from Joseph Fourier University, Grenoble HDR (2017) from École Normale Supérieure de Lyon Research focuses on dynamic mathematics environments, tangible-digital artifact combinations, and technology integration in primary education. Key areas include: Current Projects (2021): LéA LAiR: AI integration in math education Smart Enseigno: AI-based educational assistant Completed Projects: CI-MéLyon (mathematical learning), OCINAEE (connected objects in primary education), and Intergeo (dynamic geometry resources). Teaching and Advising: Supervised doctoral theses on topics like dynamic geometry software comparison, artifact pair design, and interactive whiteboards in geometry teaching. Collaborates with institutions like ECNU Shanghai and Lebanese University. Labs/Teams: Active in the S2HEP Lab and French Institute of Education. Involved in international collaborations through projects like Pairform@nce and MIRA.

Tung T. Nguyenمشاهده پروفایل

استادیار مهمان

• Computational Number Theory
• Spectral Graph Theory
• Nonlinear Dynamics
• +۳ مورد دیگر

Tung T. Nguyen is a Visiting Assistant Professor of Computer Science at Lake Forest College, with a PhD in Mathematics from the University of Chicago (2020). He will transition to a tenure-track Assistant Professor position at Elmhurst University in Fall 2025. His research bridges computational number theory, spectral graph theory, and nonlinear dynamics, with recent work exploring AI-driven theorem proving. He actively mentors students, emphasizing experimental projects that merge mathematical rigor with coding. Education: PhD in Mathematics (University of Chicago, 2020) under Prof. Kazuya Kato; Postdoc at Western University (2020-2024); Undergraduate at Vietnam National University. Research focuses on Algorithms for prime number theory Applications of algebraic structures in graph theory Nonlinear oscillator networks and synchronization phenomena Key awards: 2025 SIAM Early Career Travel Award (to present work at AG25 conference) and MAA Project NExT fellowship. Organized conferences include the virtual celebration of Prof. Moshe Rosenfeld's 85th birthday. Teaching includes Probability & Statistics and independent studies on prime number algorithms. Collaborates on initiatives like the Vietnam PolyMath REU program.

• Mathematics Education
• STEM Education
• History of Education
• +۳ مورد دیگر

Pilar Olivares Carrillo is a Professor at the University of Murcia, affiliated with the Faculty of Education and the Department of Didactics of Mathematical and Social Sciences. She holds a PhD from the same institution (2013), focusing on non-catalytic biodiesel synthesis using supercritical methanol. Her research spans multiple areas including mathematics education, STEM pedagogy, history of educational materials, and teacher training methodologies. Her academic career includes involvement with the research group Epistemological Approach in Didactics of Mathematics and Teacher Training , and prior participation in the Green Chemical Process Engineering group. Key research interests include historical educational resources (e.g., Rubio Notebooks), interdisciplinary STEM practices, and innovative teaching strategies like student-led instruction. Notable contributions include studies on musical training's impact on mathematical creativity, Pestalozzi's pedagogical principles in 19th century Spain, and the design of technology-based questionnaires for STEM education innovation. Her work integrates historical analysis with contemporary educational challenges, emphasizing practical classroom applications. Dr. Olivares Carrillo has supervised academic theses and contributed to bioenergy education through experimental teaching methods. Her biodiesel research from 2010s highlights innovative supercritical methanol processes for sustainable fuel production.

Lukas Pottmeyerمشاهده پروفایل

پژوهشگر

• Number Theory
• Diophantine Approximation
• Algebraic Number Theory
• +۲ مورد دیگر

Dr. Lukas Pottmeyer is a faculty member at the Faculty of Mathematics, University of Duisburg-Essen, with offices in both Essen (WSC-N-3.38) and Duisburg (BC 507). He serves as Student Advisory Service coordinator and teaches core mathematics courses for engineering and computer science students, including Mathematics for Engineering (WS 25/26), Stochastics I, Mathematical Modeling, and Discrete Mathematics across multiple semesters. His research focuses on Number Theory, particularly Diophantine Approximation, Arithmetic Dynamics, and Height Functions. Publications span from 2013-2022 with significant contributions to Mahler measure dynamics, $p$-adic numbers, and Bogomolov-type properties. His 2019 German-language textbook Discrete Mathematics (Springer-Spektrum) supports undergraduate instruction. Research trends show consistent specialization in algebraic number theory with increasing focus on dynamical systems applications. His Erdős number is 3, reflecting connections to prominent mathematicians. Teaching responsibilities include developing course structures with integrated lectures, exercises, and tutorials emphasizing solution-writing practice. Professional service includes student advising with structured consultation hours, mentoring for mathematics bachelor programs, and coordination of resources like STEP teams and mentoring groups. He actively supports students through the Academic Counseling Center and emphasizes foundational courses in Analysis and Linear Algebra.

• Machine Learning
• Artificial Intelligence
• Environmental Modeling
• +۳ مورد دیگر

Ryan Wu is a researcher specializing in machine learning and its applications in environmental modeling and energy systems. His work bridges artificial intelligence with practical challenges in coastal oceans, sediment transport, wind-speed forecasting, and electrical load prediction. Research Focus : Machine learning for environmental and energy applications Key Contributions : Physics-informed models, robust regression techniques, temporal LASSO regression, and novel optimization algorithms Recent Publications : Focused on computational intelligence for sediment concentration forecasting, wind-speed prediction, and electric load optimization. Subfields span predictive analytics, time series analysis, and environmental engineering.

Ovidiu Bagdasarمشاهده پروفایل

استاد

• Number Theory
• Recurrence Sequences
• Dynamic Geometry
• +۳ مورد دیگر

Dr. Ovidiu Bagdasar is a Professor of Mathematics at the School of Computing, University of Derby, and coordinates the Vretta maths support project. He specializes in computational mathematics and mathematical education, with a focus on recurrence sequences, dynamic geometry, and optimization. His research bridges theoretical mathematics and applied problems, including criminal network analysis and educational technology. He holds a PhD in Pure Mathematics from Babeș-Bolyai University (2015) and has extensive international collaborations, including with institutions in Romania, Thailand, and China. Bagdasar promotes mathematics through initiatives like the Maths@Derby brand, offering training programs and resources for numeracy skills. His work integrates emerging technologies to enhance learning and has been featured in media outlets like *Eurekalert* and *ZME Science*. Key projects include developing numeracy training platforms for students/staff and analyzing criminal networks using graph theory. He has advised students on research bursaries, including international collaborations in Romania and Kenya. Bagdasar also leads academic partnerships, such as Erasmus+ programs with universities in Turkey and China, fostering global research and student mobility.

Vladimir Milovanovićمشاهده پروفایل

دانشیار

• Electrical Engineering
• Computer Science
• Signal Processing
• +۷ مورد دیگر

Dr. Vladimir Milovanović is an Associate Professor at the Faculty of Engineering, University of Kragujevac, Serbia, holding a position as Chair of the Department of Electrical Engineering and Computer Sciences. His academic career is anchored in interdisciplinary research at the intersection of electrical engineering, computer science, and biomedical applications. His research focuses on hardware design, radar sensor systems, biomedical signal processing, and machine learning applications. Notable areas include CMOS circuit design, FPGA-based implementations, and parameterizable hardware generators for signal processing tasks. He also explores medical imaging analysis using deep learning techniques for conditions like disc hernia diagnosis. Recent work emphasizes radar technology (FMCW transceivers, signal processing architectures), embedded systems (FPGA development, IP core utilization), and high-performance streaming data algorithms. His publications span over two decades, demonstrating expertise in analog/digital circuit design, comparative classifier analysis in biomedical contexts, and hardware-software co-design methodologies. Dr. Milovanović collaborates with industry on energy-efficient MIMO arrays and semiconductor gas sensors. His contributions include open-source HDL models for digital signal processors and comparator circuits optimized for low-power and high-speed applications.