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Katrin LeschkeView profile

Associate Professor

• Surface Theory
• Integrable Systems
• Discrete Geometry
• +3 more

Dr. Katrin Leschke is an Associate Professor in Mathematics at the University of Leicester and Deputy Director for Postgraduate Research (PGR) in the College of Science and Engineering. She holds a Royal Society Short Industry Fellowship (2022–2023). Her research focuses on surface theory, integrable systems, and applications of discrete geometry to machine learning, engineering, and chemistry. She has held research positions at TU Berlin, University of Massachusetts Amherst, and University of Augsburg, where she earned her habilitation. She serves as an external examiner at the University of Manchester and participates in committees like European Women in Mathematics and the London Mathematical Society's SLAM committee. Education: Diplom and PhD in Geometry from TU Berlin Habilitation from University of Augsburg Her work bridges pure mathematics with applied fields, emphasizing geometric visualization and collaborations across disciplines. Key research areas include minimal surfaces, Darboux transformations, and non-axisymmetric turbine design optimization. She is affiliated with the Creative Computing Research Group and AIDAM, fostering interdisciplinary innovation. Notable contributions include studies on integrable systems linking CMC surfaces, isothermic surfaces, and constrained Willmore surfaces, alongside applications in engineering fluid dynamics. Awards highlight her industry-academia collaboration excellence.

Kerri CahoyView profile

Professor

• Atmospheric Sensing
• Exoplanet Detection
• Exoplanet Characterization
• +4 more

Kerri Cahoy is the Sheila Evans Widnall (1960) Professor in MIT's Department of Aeronautics and Astronautics, where she serves as Director of the Small Satellite Collaborative and Head of the Space Sector. Her work bridges electrical engineering and aerospace to advance space-based sensing and communication technologies through nanosatellite platforms. Her academic foundation includes: Ph.D. in Electrical Engineering, Stanford University (2008) M.S. in Electrical Engineering, Stanford University (2002) B.S. in Electrical Engineering, Cornell University (2000) Professor Cahoy's research integrates atmospheric sensing with exoplanet detection , pioneering laser communications and adaptive optics for space applications. She develops autonomy systems for nanosatellites to enable cost-effective Earth observation and astronomical missions, transforming how we study planetary atmospheres and distant worlds through innovative small satellite constellations. Her recent publications (2018-2020) demonstrate consistent focus on optical engineering for space systems, with core themes in CubeSat-based atmospheric tomography, laser communication terminal development, and wavefront correction techniques for exoplanet imaging. These works reveal interdisciplinary convergence of aerospace engineering, optics, and machine learning to solve extreme-environment challenges. Her scientific recognition includes: MIT Committed to Caring Award (2020) AIAA Associate Fellow (2018) MIT Outstanding UROP Mentor (2013) Cornell Co-Op Mentor of the Year (2008) As an educator, Cahoy champions hands-on satellite development through MIT's UROP program, with mentoring philosophy emphasizing technical rigor and mission-driven innovation. Her STAR Lab provides students direct experience in spacecraft design, laser communication testing, and orbital operations while securing research funding from NASA and aerospace industry partners for cutting-edge space technology development. She directs the Space Telecom, Astronomy & Radiation Lab (STAR Lab) and leads the Small Satellite Collaborative, driving projects in laser communication terminals, adaptive optics for space telescopes, and nanosatellite constellations for atmospheric science. These initiatives position MIT at the forefront of miniaturized space instrumentation and autonomous satellite operations.

Tom VerhoeffView profile

Assistant Professor

• Software Engineering
• Model-Driven Engineering
• Domain-Specific Languages
• +7 more

Tom Verhoeff is an Assistant Professor at the Faculty of Mathematics and Computing Science of Eindhoven University of Technology (TU/e) , working within the Software Engineering & Technology group. His research focuses on Model-Driven Engineering (MDE) , Domain-Specific Languages (DSLs) , and the intersection of mathematics, computing, and the arts . He teaches courses in data analytics, programming, algorithms, theoretical computer science , and logic . Verhoeff earned both his MSc and PhD in Technical Science (Mathematics and Computer Science) from TU/e. He is actively involved in promoting mathematics and informatics through initiatives like the annual Bridges conference , and serves as board member and treasurer of the Dutch Mathematics Olympiad , as well as chair of the Koos Verhoeff MathArt foundation . He has also held roles as guest lecturer in Lithuania and Finals Director for the ACM International Collegiate Programming Contest . Research Interests: Verhoeff’s work spans Model-Driven Engineering , domain-specific language development , and 3D geometric modeling . His scholarship often explores symmetry, recursion, and mathematical visualization , particularly through computational art and algorithmic puzzles . Recent publications highlight 3D rotation methods , knot theory , and mathematical art using lattice paths and geometric transformations . Scientific Awards: ACM ICPC European Founders Award (2004) IOI Distinguished Service Award (2007) Second Place in the 2022 Wolfram Computational Art Contest Notable Collaborations and Affiliations: He is affiliated with the Esprit Working Group on Asynchronous Circuit Design (ACiD-WG) , WIRE (TUE Mathematics Alumni) , ACM (Senior Member) , CSTA , IEEE Computer Society , and Royal Dutch Mathematical Society (KWG) .

• Number Theory
• Automorphic Forms
• Representation Theory
• +3 more

Jennifer Johnson-Leung serves as Professor in the Department of Mathematics and Statistical Science within the College of Science at the University of Idaho, with additional affiliation as Participating Faculty at the Institute for Modeling Collaboration and Innovation under the Office of Research and Economic Development. Her academic credentials include: PhD in Mathematics from the California Institute of Technology (2005) BS in Chemistry and Mathematics from the College of William and Mary (1998) Professor Johnson-Leung maintains a dual research focus bridging pure mathematics and applied epidemiology. In theoretical mathematics, she investigates Siegel modular forms, paramodular forms, Hecke algebras, and representation theory, advancing understanding of automorphic forms and their connections to algebraic geometry. Her applied work develops spatial statistical models for sociodemographic risk assessment in public health crises, particularly during the COVID-19 pandemic, utilizing techniques like elastic net regression to analyze vaccination behavior and mortality patterns. Analysis of her recent publications reveals equal emphasis on deep theoretical number theory problems and urgent public health applications. The mathematical works explore structural properties of modular forms and representation theory, while epidemiological studies dissect complex interactions between political ideology, social vulnerability, and pandemic outcomes across U.S. populations. No specific scientific awards were documented in the provided materials. Information regarding graduate student advising and research grant funding remains unspecified in the available documentation. No dedicated research laboratories or specialized collaborative teams were mentioned in the source materials.

• Arithmetic Algebraic Geometry
• Algebraic Number Theory
• Modular Forms
• +3 more

John Voight is a Professor in the School of Mathematics and Statistics at the University of Sydney, where he is also a member of the Algebra and Computational Algebra groups. His research focuses on arithmetic algebraic geometry, modular forms, and computational number theory. He collaborates with the Magma computational algebra system development team and contributes to databases like the LMFDB. Affiliations: University of Sydney (2024–present), Dartmouth College (2007–2024), University of Vermont (2007–2013). Key research interests include modular curves, Shimura varieties, elliptic curves, and abelian varieties. He explores algorithmic methods for computing with algebraic structures, such as quaternion algebras and ideal class groups. Publications span over 90 articles, including works on Hilbert modular forms, Belyi maps, and paramodular varieties. Notable achievements include the Selfridge Prize (2010 and 2018) and Simons Foundation grants. He advises numerous PhD students and has contributed to major projects like the LMFDB, advancing computational tools for number theory.

Stefan Petrov IvanovView profile

Professor

• Differential Geometry
• Quaternionic Geometry
• String Theory
• +4 more

Stefan Petrov Ivanov is a Professor of Mathematics at the Department of Geometry, Faculty of Mathematics and Informatics, University of Sofia 'St. Kliment Ohridski'. He holds a Dr.Sci. (Doctor of Mathematical Sciences) from the same institution (2006) and has been a faculty member since 1988. His academic career includes significant collaborations through the European Differential Geometry Endeavour (EDGE) network and multiple visiting professorships at institutions including Humboldt University, University of Pennsylvania, and ICTP Trieste. Dr.Sci. (2006), University of Sofia Ph.D. (1987), University of Sofia (Thesis: Linear connections on a smooth manifold with structures) M.S. (1982) and B.S. (1980), University of Sofia Ivanov's research spans differential geometry with emphasis on quaternionic geometry, CR structures, and applications to string theory. His work on the quaternionic contact Yamabe problem represents a major contribution to geometric analysis. He has developed novel connections between exceptional holonomy manifolds, Dirac operators, and heterotic string compactifications, particularly focusing on non-Kähler solutions with fluxes and non-constant dilaton fields. His research integrates deep geometric insights with mathematical physics applications, especially in supersymmetric string backgrounds. Professor Ivanov has supervised 14 Master's dissertations and 5 Ph.D. theses, including prominent students like Bogdan Alexandrov and Ivan Minchev. His research has been supported by major grants including the EU EDGE network, NSF Bulgaria contracts (DO 02-257/2008, DID 02-39/2009), and collaborations with US institutions like the University of Pennsylvania and University of New Mexico. He serves as editor for Annals of Global Analysis and Geometry and has organized significant conferences including the Black Sea EDGE-Workshop (2003) and Geometric Structures in Mathematical Physics (2011).

Nader SadeghView profile

Professor

• Robotics
• Controls
• Automation
• +8 more

Nader Sadegh is a Professor in the Woodruff School of Mechanical Engineering at the Georgia Institute of Technology's College of Engineering, where he also serves as Associate Director and Education Director of the Robotics Ph.D. Program. His research spans robotics, control theory, and artificial intelligence with applications in industrial automation and public health. Dr. Sadegh's educational background includes: B.S. from University of California, Santa Barbara (1982) M.S. from University of California, Berkeley (1984) Ph.D. from University of California, Berkeley (1987) His research evolved from pioneering work on adaptive learning controllers for robotic manipulators—which enable robots to learn repetitive tasks without precise models—to neural network applications and nonlinear system identification. Current work focuses on barrier state theory for safety-critical control systems, safe trajectory optimization in robotics, and epidemiological modeling for disease transmission control. His methodologies consistently bridge theoretical control frameworks with industrial implementations to enhance system accuracy and autonomy while reducing hardware complexity. Analysis of his recent publications reveals a dominant trend toward safety-critical control architectures using barrier states and functions, with expanding applications in quadrotor navigation, agricultural robotics, and pandemic response systems. The interdisciplinary nature of his work connects control theory with machine learning, epidemiology, and industrial automation. Scientific distinctions include: Associate Editor, Journal of Dynamic Systems, Measurement, and Control (1993-1997) Registered Professional Engineer in Georgia U.S. Patent 5,946,449 for precision apparatus with non-rigid structures Dr. Sadegh has secured significant industry-sponsored research including Xerox Corporation projects on photoreceptor speed regulation, Ford Motor Company collaborations on assembly operations and continuously variable transmissions, and Visteon-funded work on high-precision manufacturing systems. His grants consistently target practical implementations where theoretical control methods solve real-world problems in automotive systems, electro-hydraulic valves, and glass forming processes. Based at the Georgia Tech Manufacturing Institute (GTMI), his lab develops integrated control solutions for complex mechanical systems, with recent emphasis on safety-guaranteed autonomous operations in unstructured environments and data-driven modeling for biological processes.

• Wavelets and Frames
• Harmonic and Functional Analysis
• Fractal Geometry
• +3 more

Peter Massopust is a Privatdozent at the Technical University of Munich (TUM), where he is affiliated with the School of Computation, Information and Technology and the Department of Mathematics. His research spans multiple areas of mathematical analysis with a focus on fractal geometry, wavelet theory, and approximation methods. His educational background includes: Habilitation in 2011 from Technical University of Munich Ph.D. in Applied Mathematics from Georgia Institute of Technology (1986) MS in Mathematics from Georgia Institute of Technology (1985) MS in Physics from Georgia Institute of Technology (1981) Dr. Massopust's research interests primarily focus on Wavelets and Frames, Harmonic and Functional Analysis, Fractal Geometry and Fractal Interpolation Theory, and Splines and Approximation Theory. His work bridges theoretical mathematics with practical applications in signal processing, image analysis, and computational methods. His approach often combines classical mathematical techniques with innovative fractal-based methods to solve complex problems in approximation theory and functional analysis. His research has significantly contributed to the development of fractal interpolation functions, complex splines, and wavelet theory, with applications spanning from pure mathematics to engineering problems. His publication record demonstrates a consistent focus on fractal-based mathematical methods, with recent work expanding into quaternionic analysis, complex B-splines, and applications in signal processing. His research shows a clear trajectory from foundational work in fractal geometry to increasingly sophisticated applications in multidimensional signal analysis and computational mathematics. His scientific achievements have been recognized through several prestigious awards: Fulbright Scholarship (1980-1981) GIAN (Global Initiative for Academic Network) Award from the Republic of India (2016, 2017) Dr. Massopust has secured substantial research funding from various national and international sources, including the German Research Foundation (DFG), Bayerische Forschungsallianz, VolkswagenStiftung, and collaborations with Sandia National Laboratories and the National Science Foundation. His research program has consistently focused on advancing mathematical methods for signal and image processing, with particular emphasis on fractal-based approaches and wavelet theory. He has also been instrumental in fostering international collaborations, particularly through the EuroTech network and with institutions in Australia and India. Among his notable contributions is the GHM (Geronimo-Hardin-Massopust) Scaling Vector and DGHM (Donovan-Geronimo-Hardin-Massopust) Multiwavelet, developed at the Georgia Tech Research Institute in 1995. This work has had significant impact in the field of wavelet analysis and its applications.

John JunkinsView profile

Professor

• Aerospace Engineering
• Astrodynamics
• Spacecraft Dynamics and Control
• +3 more

John Junkins is a distinguished academic and researcher in aerospace engineering, holding the Royce E. Wisenbaker Chair and serving as Director of the Hagler Institute for Advanced Study at Texas A&M University's College of Engineering. He has been affiliated with the Department of Aerospace Engineering since at least 1993. Junkins' roles include being a Distinguished Professor (mapped to Professor rank), a Regents Professor, and an Honorary Fellow of the American Institute of Aeronautics and Astronautics (AIAA). His educational background includes a B.A.E. from Auburn University (1965), and M.S. and Ph.D. in Aerospace Engineering from UCLA (1967, 1969). His research focuses on spacecraft dynamics and control, guidance systems, analytical methods, and smart sensor technologies. Notable contributions include work on trajectory optimization, orbital mechanics, and nonlinear control systems. Key awards include the Kay Bailey Hutchinson Distinguished Service Award (2022), Robert H. Goddard Astronautics Award (2019), and TYCHO BRAHE Medal (2004). His publications span textbooks like 'Analytical Mechanics of Aerospace Systems' and pioneering research in astrodynamics. Junkins' work emphasizes interdisciplinary collaboration through the Hagler Institute, advancing computational methods for space mission design and autonomous systems.

Lamine M. MiliView profile

Professor

• Power Systems
• Signal Processing
• Robust Estimation Theory
• +7 more

Lamine M. Mili is a Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. His expertise spans power systems, signal processing, and robust estimation theory. He holds an IEEE Fellowship (2016) for contributions to robust state estimation in power systems. Mili's research focuses on advancing methodologies for power system reliability, control, and integration of renewable energy sources. His work includes studies on dynamic state estimation, nonlinear dynamics, bifurcation theory, and quantum computing applications. He has contributed extensively to resilience engineering and computational social science in power systems. Mili’s recent articles address challenges in smart grids, quantum circuit error prediction, and multifractal signal analysis in EEG. His research often combines advanced statistical techniques with real-world grid data, emphasizing robustness and adaptability in dynamic environments. Education: Ph.D., University of Liège, 1987 M.S., University of Tunis, 1983 B.S., Swiss Federal Institute of Technology, Lausanne, 1976 Research Interests: Power system stability and control State estimation and robust filtering Quantum computing for power systems Resilience and cyber-physical-social systems Nonlinear dynamics and bifurcation analysis His recent publications reflect a focus on hybrid power systems, probabilistic methods, and data-driven approaches for grid optimization. The 2025 articles highlight advancements in photovoltaic state estimation, quantum error prediction, and robust modulation techniques. Mili’s work often bridges theoretical models with practical grid applications, emphasizing uncertainty quantification and real-time monitoring.

Juan Antonio Corrales RamónView profile

Research Fellow

• Robotics
• Human-Robot Interaction
• Robotic Manipulation
• +3 more

Juan Antonio Corrales Ramón is a Research Fellow at the University of Santiago de Compostela's CiTIUS laboratory under the prestigious Beatriz Galindo program. Previously, he served as an Associate Professor at Sigma Clermont Engineering School (2014-2020) and conducted research at UPMC/ISIR in France. His academic credentials include a PhD in Automatic Control and Robotics (2011) and a Computer Engineering degree (2005) from the University of Alicante. Dr. Corrales' research centers on robotics with specialized interests in: Human-robot physical interaction for industrial applications Deformable object manipulation and control theory Tactile sensing technologies and sensor fusion Robotic grasping and in-hand manipulation Multi-robot coordination systems His recent publications demonstrate strong focus on adaptive control systems for deformable objects, tactile sensor development, and human-robot collaboration frameworks. He has participated in significant EU projects including: H2020 SoftManBot (soft material handling) H2020 Bots2Rec (recycling robotics) FUI Aerostrip (aerospace applications) Sudoe Commandia (service robotics) Honors include competitive fellowships: FPU Program Fellowship (Spanish Ministry of Education) Beatriz Galindo Program Fellowship (research excellence) At CiTIUS laboratory, he contributes to advanced robotics research with applications in industrial automation, healthcare, and agricultural robotics.

Alex WaldronView profile

Assistant Professor

• Differential Geometry
• Geometric Analysis
• Gauge Theory
• +4 more

Alex Waldron is an Assistant Professor in the Department of Mathematics at the University of Wisconsin–Madison. His research focuses on geometric analysis, particularly the interplay between differential geometry and nonlinear PDEs. His recent work includes studies on Yang-Mills flow, harmonic maps, and G2-instantons on the 7-sphere. He has delivered lectures on topics such as the quaternionic Hopf fibration and developments in Yang-Mills flow. Research areas: Differential Geometry, Special Holonomy, Geometric PDEs Key lectures: G2-instantons on S^7 , Recent developments in Yang-Mills flow His publications highlight advancements in Uhlenbeck compactness, Lojasiewicz inequalities, and regularity theory for geometric flows.

Martin ReissleinView profile

Professor

• Communication Networks
• Engineering Education
• Multimedia Networking
• +5 more

Dr. Martin Reisslein is a Professor in the School of Electrical, Computer, and Energy Engineering at Arizona State University (ASU), where he also serves as Program Chair of Computer Engineering. He earned his Ph.D. in Systems Engineering from the University of Pennsylvania (1998) and holds degrees from the University of Pennsylvania and Fachhochschule Dieburg, Germany. His research focuses on communication networks (e.g., 5G, optical networks, software-defined networking) and engineering education, with over 200 journal articles and 60 conference papers. He has led NSF-funded projects on network architecture optimization and K-12 engineering education. Education : Ph.D. (Systems Engineering, UPenn, 1998), M.S.E. (Electrical Engineering, UPenn, 1996), Dipl.-Ing. (FH) (Electrical Engineering, Fachhochschule Dieburg, 1994) Awards : NSF Career Award (2002), IEEE Fellow (2014), Bessel Research Award (2015), DRESDEN Fellowship (2016) Editorial Roles : Co-Editor-in-Chief of Optical Switching and Networking , Associate Editor for multiple IEEE journals His research spans communication networks (e.g., multimedia networking, optical systems) and engineering education (e.g., K-12 outreach, instructional design). Recent articles address cloud computing, 5G architectures, and cybersecurity in satellite systems. He teaches courses such as Communication Networks and oversees graduate research.

• Differential Geometry

Craig van Coevering is an Associate Professor in the Department of Mathematics at Boğaziçi University. He holds a Ph.D. from Stony Brook University (2006), an M.S. from Portland State University (1998), and a B.A. from Reed College (1993). His primary research focuses on differential geometry, particularly complex and Riemannian geometries. His work explores deformation theory, stability analysis, and geometric structures including Calabi-Yau metrics, Sasakian manifolds, and extremal Kähler metrics. Research integrates techniques from partial differential equations, geometric analysis, and algebraic geometry to investigate Ricci-flat spaces, toric varieties, and hyperkähler manifolds. Publications demonstrate consistent focus on geometric flows, Einstein metrics, and non-compact manifolds, with recent emphasis on variational methods and CR geometry. No awards or student advising details are provided.

Hakan TemeltaşView profile

Professor

• Robotics
• Autonomous Systems
• Control Engineering
• +6 more

Professor Hakan Temeltaş is affiliated with Istanbul Technical University , where he serves in the Department of Control and Automation Engineering . His research focuses on robotics, control systems, and autonomous technologies. He has contributed to advancements in motion planning, localization, and deep reinforcement learning for robotic systems. Research Interests: Robotics, Autonomous Systems, Control Engineering, Machine Learning Current Projects: Deep reinforcement learning for quadrupedal robots, localization frameworks, multi-agent systems His recent work includes autonomous exploration strategies using Rapidly-Exploring Random Trees (RRT), multi-stage localization for mobile robots, and quaternion-based orientation estimation in robot manipulators. He supervises projects involving adversarial attack mitigation and self-recovery mechanisms in quadrupedal robots. Publications highlight applications of deep reinforcement learning in robotics, with a focus on dynamic stability, sensor fusion, and simulation environments. His research outputs span conferences like IEEE RAAI and journals such as Robotica and Unmanned Systems . Scientific Awards : None explicitly mentioned in the provided data. As a principal investigator, he leads projects on ground reaction force balancing, autonomous navigation, and swarm robotics. His collaborations extend to simulation frameworks and real-time control systems for mobile robots.