Find Academic Supervisors

• Control Theory
• Fractional Calculus
• System Identification
• +3 more

Rachid Malti is a Professor in the Automatic Control research group at the University of Bordeaux, France, specifically working within the CRONE team at IMS (Laboratoire de l'intégration, du matériau au système). His academic career spans over two decades with significant contributions to fractional calculus applications in control engineering and system identification. Professor Malti's research focuses on: Development of fractional order system identification methods Stability analysis of fractional and time-delay systems Experimental design for fractional model validation Applications in energy systems, thermal networks, and battery modeling CRONE Toolbox development for fractional differential signal processing His publication record demonstrates consistent theoretical and applied contributions, with recent work expanding into district heating networks, lithium-ion batteries, and climate modeling while maintaining strong theoretical foundations in fractional calculus. Professor Malti frequently collaborates with researchers including Stéphane Victor, Abir Mayoufi, and Patrick Lanusse across international boundaries. Professor Malti has published extensively in top-tier journals including Automatica, Communications in Nonlinear Science and Numerical Simulation, and Fractional Calculus and Applied Analysis, establishing himself as a leading researcher in fractional order control systems.

Antti H. NiemiView profile

Professor

• Computational Solid Mechanics
• Structural Engineering
• Civil Engineering
• +5 more

Antti H. Niemi is a Professor and Dean at the University of Oulu 's Faculty of Technology , specializing in computational solid and structural mechanics. His research focuses on advanced numerical methods for engineering analysis and design. Research areas include computational mechanics, structural engineering, and metamaterials Develops innovative finite element methods for thin-body problems Current projects address snow structures, timber building envelopes, and machine learning applications in mechanical systems His recent work emphasizes discontinuous Petrov-Galerkin (DPG) methods for plates and shells, with applications in civil and mechanical engineering. Publications cover: Snow and ice vaults (2024) Machine learning for steel beam capacity prediction (2024) Hygrothermal analysis of timber structures (2024) DPG formulation for Reissner-Mindlin plates (2023) Shell element benchmarking (2018-2022)

• Flexible spacecraft
• Flight control systems
• Robotic systems
• +7 more

Elisa Capello is a Full Professor of Flight Mechanics at Politecnico di Torino, Department of Mechanical and Aerospace Engineering (DIMEAS). She serves as Contact person for internationalization of innovation and technology transfer, Member of the Interdepartmental Center PIC4SeR (PoliTO Interdepartmental Center for Service Robotics), and Deputy Coordinator of the Doctoral College in Aerospace Engineering. With over 100 publications, her work spans aerospace engineering, control systems, and robotics. Her research focuses on flexible spacecraft, flight control systems, robotic systems, and unmanned aerial vehicles. She designs guidance, control and navigation systems for aircraft and spacecraft, develops control systems for wind turbines and wind farms, studies flight mechanics of fixed and rotary wing aircraft, tests unmanned aerial systems, and plans mission control for autonomous systems. Her work bridges theoretical control systems with practical aerospace applications, with strong emphasis on experimental validation. Her recent publications demonstrate a strong focus on advanced control techniques for aerospace applications, particularly in UAV control, spacecraft formation flying, and robotic systems. There's a clear trend toward integrating machine learning with traditional control methods, as seen in transformer-based MPC and multimodal learning approaches. Her work spans theoretical development, simulation, and experimental validation across multiple platforms. Member of the Editorial Board of IEEE Control Systems Society (2019-) Member of the Scientific Committee - IEEE Technical Committee Aerospace Control (2016-) International FAI Judge for Helicopter Championship (2009-2015) Professor Capello supervises numerous PhD students working on topics including autonomous aerial vehicles, path planning, risk analysis, spacecraft dynamics, and control. She leads multiple research projects including CREATEFORUAS (2019-2022), Assessment of drag free control systems for L3 gravity wave observatory (2018-2019), and Guidance, Navigation and Control algorithms for in-Orbit servicing (2020-2021). Her international collaborations include institutions in the USA, Japan, and Germany. She is actively involved with the Flight Dynamics, Control and Simulation research group at DIMEAS and the DRAFT (DRones Autonomous Flight Team) at PoliTo, where she mentors students in developing autonomous flight capabilities for various applications.

• Nonlinear Programming
• Optimization Methods
• Radiation Therapy Optimization
• +2 more

Anders Forsgren is a Professor of Optimization and Systems Theory at the Department of Mathematics, KTH Royal Institute of Technology since 2003. His research focuses on nonlinear programming, particularly Newton-type methods for smooth optimization, with applications in radiation therapy, cell biology, and telecommunications. PhD in Optimization and Systems Theory (KTH, 1990) MS in Operations Research (Stanford, 1987) MSc in Engineering Physics (KTH, 1985) Research Interests: Anders develops methods for constrained optimization and applies them to intensity-modulated radiation therapy, metabolic networks, and wireless communication systems. His work bridges algorithmic innovation with real-world clinical and engineering challenges. Recent Publications: Focus on robust optimization for radiation therapy under uncertainty, quasi-Newton methods, and applications in medical physics. His 2025 papers address interplay-robust optimization and scenario positioning in proton therapy. Scientific Leadership: Co-chair, 8th SIAM Conference on Optimization (2005) Editorial board member, Computational Optimization and Applications (since 1998) Member, Mathematical Optimization Society and SIAM Mentorship: Supervises PhD students in optimization and systems theory, with former advisees working on radiation therapy robustness, metabolic modeling, and network design.

Sverre A. C. KittelsenView profile

Professor

• Production theory
• Efficiency measurement
• Regulation
• +2 more

Sverre A. C. Kittelsen is a Senior Research Fellow at the Frisch Centre and holds a Professor II position at the Department of Health Management and Health Economics (HELED) within the Institute of Health and Society at the University of Oslo. His academic career spans over three decades with a Doctor Politicae (Dr.Polit.) in Economics from the University of Oslo (1998) and a Cand.Polit. in Economics from the University of Bergen (1985). His primary research interests include Production theory, Efficiency measurement, Regulation, Health Economics, and Energy Economics. Kittelsen has established himself as a leading researcher in Nordic healthcare efficiency analysis, particularly focusing on hospital productivity, quality assessment, and the economic implications of healthcare reforms across Scandinavian countries. He has also made significant contributions to energy economics, especially regarding European energy markets and climate policy. His recent publication record demonstrates remarkable productivity with 15+ publications since 2017, showing consistent scholarly output across health economics and energy economics. The research trends indicate a strong focus on empirical analysis of healthcare systems using advanced econometric methods, particularly data envelopment analysis (DEA) and productivity measurement techniques. His work frequently involves cross-national comparative studies within the Nordic region, examining how different healthcare organizational structures affect efficiency and quality outcomes. Kittelsen has been involved in numerous research projects related to public sector efficiency, including hospital productivity studies, tax office efficiency analysis, and energy market modeling. His work often bridges theoretical economic concepts with practical policy implications for healthcare and energy sectors. His institutional affiliations with both the Frisch Centre (a prominent Norwegian economic research institute) and the University of Oslo position him at the nexus of academic research and policy-relevant analysis. This dual affiliation enables him to contribute both to theoretical economic literature and to practical policy discussions in Norway and the broader Nordic region.

Laxman DhulipalaView profile

Assistant Professor

• Parallel Algorithms
• Graph Processing
• Parallel Graph Algorithms
• +7 more

Laxman Dhulipala serves as an Assistant Professor in the Department of Computer Science at the University of Maryland, College Park, while also working as a research scientist at Google Research with the Graph Mining team. Dr. Dhulipala earned his Ph.D. from Carnegie Mellon University under Guy Blelloch's supervision and completed a postdoctoral fellowship at MIT with Julian Shun. His research centers on efficient parallel algorithms, particularly for parallel clustering and graph processing, along with developing computational models for emerging hardware technologies. His scholarly output demonstrates significant expertise across parallel computing domains, with particular emphasis on scalable graph algorithms, dynamic data structures, and computational geometry. Dr. Dhulipala's work bridges theoretical computer science with practical systems implementation, producing algorithms that achieve both theoretical optimality and real-world performance. His research group has made substantial contributions to benchmarking frameworks including the Graph Based Benchmark Suite (GBBS) and ParClusterers Benchmark Suite, establishing standardized evaluation methods for graph processing systems. The collective work shows progression from theoretical foundations to practical implementations that handle massive-scale datasets. Best Paper Award at SPAA 2022 Best Paper Runner Up at VLDB 2022 Distinguished Paper Award at PLDI 2019 Memorable Paper Award Finalist at NVMW'20 CMU's SCS Dissertation Award Honorable Mention As an educator, Dr. Dhulipala mentors numerous graduate students while teaching advanced courses in algorithm design and parallel computing. His research collaborations span multiple institutions including Carnegie Mellon University, MIT, and Google Research, reflecting his position at the intersection of academia and industry research.

• Entrepreneurial Management
• Small Business Acquisition
• Private Equity
• +3 more

Royce G. Yudkoff serves as the MBA Class of 1975 Professor of Management Practice of Entrepreneurial Management at Harvard Business School. He is also a General Partner and co-founder of ABRY Partners, LLC, a Boston-based private equity firm. At Harvard Business School, Yudkoff co-teaches two courses with Professor Richard Ruback: 'The Financial Management of Smaller Firms' and 'Entrepreneurship through Acquisition,' which focus on acquiring, financing, and operating smaller firms. Yudkoff's research interests center on entrepreneurial management, particularly the acquisition of small businesses. His work explores the practical aspects of finding, evaluating, negotiating, and financing the purchase of established businesses, providing an alternative path to entrepreneurship. He has co-authored the book HBR Guide to Buying a Small Business: Think Big, Buy Small, Own Your Own Company (2017) and the Harvard Business Review article 'Buying Your Way into Entrepreneurship' (2017), which established him as a leading expert in the search fund and small business acquisition space. His recent scholarly output has been remarkably prolific, with numerous case studies published in 2025 covering diverse business acquisition scenarios across various industries including manufacturing, healthcare, technology, and consumer products. These works examine critical aspects of business acquisition including valuation, due diligence, financial modeling, and post-acquisition management. Baker Scholar (Harvard Business School, 1980) Yudkoff has significant practical experience to complement his academic work. In 1989, he co-founded ABRY Partners, a private equity firm specializing in media, communications, and business information services. Over his career, the firm has completed over $27 billion in leveraged transactions involving approximately 450 properties. Yudkoff has also served on numerous private and public corporate boards, bringing real-world perspective to his teaching and research. His educational background includes graduating from Harvard Business School in 1980 as a Baker Scholar and earning honors as an undergraduate at Dartmouth College. This combination of academic excellence and practical business experience informs his approach to entrepreneurial education.

• Information Hiding
• Steganography
• Steganalysis
• +4 more

Andrew D. Ker is Professor and Associate Professor of Computer Science at the University of Oxford's Department of Computer Science, and Tutorial Fellow in Computer Science at University College, Oxford since 2009. He received his BA in Mathematics & Computer Science (1994-1997) and DPhil in Computer Science (1997-2000) from Oxford, followed by academic appointments including Junior Research Fellow (2000-2003), Special Supernumerary Fellow (2003-2009), and Royal Society University Research Fellow (2003-2011). His research focuses on information hiding, particularly steganography (covert communication in digital media) and steganalysis (detection of hidden data), with additional interests in digital media forensics and programming language semantics. His foundational work includes the mathematical formalization of the 'square root law of steganographic capacity'. Recent publications explore practical implementations in social media platforms, GPU-accelerated steganalysis, and linguistic steganography techniques. He has received multiple scientific awards including Best Paper Awards at ACM Workshops on Information Hiding & Multimedia Security, SPIE conferences, and the International Workshop on Digital Watermarking. As Associate Editor for IEEE Transactions on Information Forensics and Security, he maintains active involvement in the academic community. Professor Ker has supervised numerous graduate students in computer security and steganography research, including doctoral candidates and master's students. He leads research within Cyber Security Oxford and has developed four major lecture series: Lambda Calculus and Types, Discrete Mathematics, Computer Security, and Advanced Security: Information Hiding. He remains active in teaching despite administrative responsibilities as Tutorial Fellow.

Alexey Evgenievich OsadchiyView profile

Professor

• digital signal processing
• magnetoencephalography
• electroencephalography
• +9 more

Alexey Evgenievich Osadchiy is a Professor at the National Research University Higher School of Economics (HSE University), where he serves as Director of the Center for Bioelectric Interfaces at the Institute of Cognitive Neuroscience. He has been working at HSE since 2013 with 21 years of scientific and teaching experience. His academic appointments include Professor at the Faculty of Computer Science in the Department of Data Analysis and Artificial Intelligence. 2023 - Doctor of Science: National Research University Higher School of Economics 2003 - PhD: University of Southern California, specialty "Physical and Mathematical Sciences" and "Neurobiology" 1997 - Specialty: Bauman Moscow State Technical University, major in Autonomous Information and Control Systems Professor Osadchiy's research focuses on digital signal processing, magnetoencephalography (MEG), electroencephalography, inverse problems, synchronization, non-invasive detection, and brain mapping. His work bridges neuroscience, computer science, and medical applications, with particular emphasis on brain-computer interfaces, neurofeedback systems, and precision medicine applications for neurological disorders. He has pioneered methods for real-time brain activity monitoring and developed novel approaches for functional connectivity estimation in neural networks. His recent publications demonstrate a strong trend toward developing hardware-enabled low-latency systems for brain-state dependent stimulation, improving MEG technology with optically pumped magnetometers, and advancing speech mapping techniques for neurosurgical applications. His work increasingly integrates AI and deep learning approaches with traditional neuroimaging techniques to create more precise and accessible brain measurement and modulation systems. Scientific Awards and Recognition HSE University "Recognition - 10 Years of Successful Work" Medal (July 2025) Letter of Gratitude from the Higher School of Economics (September 2021) Letter of Gratitude from the Faculty of Computer Science at HSE (August 2018) Allowance for defending a doctoral dissertation (2023–2026) Bonuses for publications in international peer-reviewed journals (2015–2029) Professor Osadchiy has successfully advised numerous graduate students and doctoral candidates, with eight dissertation research projects currently under his supervision. His research has been supported by significant grants including a Russian Ministry of Education and Science contract for "System for registration and decoding of human brain bioelectric activity" (2014-2017), RFBR grants for "New non-invasive experimental-mathematical paradigm for preoperative magnetoencephalographic mapping of speech cortex" (14-02-00917, 16-04-01863), and projects on "Endogenous enhancement of brain-computer interface efficiency." As Director of the Center for Bioelectric Interfaces at the Institute of Cognitive Neuroscience, Professor Osadchiy leads a multidisciplinary team working on cutting-edge neurotechnology. His center collaborates with the Federal Brain and Neural Technology Centre at the Federal Medical and Biological Agency, where they established the Laboratory of Medical Neural Interfaces and Artificial Intelligence for Clinical Applications. The center is actively involved in developing brain-computer interfaces for rehabilitation, particularly for stroke patients and those with locomotor function disorders, and has created Russia's first neurointerface for controlling exoskeletons using imagined lower limb movements.

Amaresh SahuView profile

Assistant Professor

• Soft Matter Physics
• Biological Membranes
• Continuum Mechanics
• +5 more

Amaresh Sahu serves as an Assistant Professor in the Chemical Engineering Department at the University of Texas at Austin, leading the Sahu Lab which focuses on theoretical investigations of soft and living matter systems across multiple length and time scales. His research integrates concepts from chemical engineering, physics, computer science, and applied mathematics to address fundamental questions about how microscopic interactions produce emergent phenomena at larger scales. Dr. Sahu's educational background includes a Ph.D. in Chemical Engineering from the University of California at Berkeley (2022), where he worked with Professor Kranthi Mandadapu, followed by a postdoctoral fellowship in Physiology & Biophysics at Weill Cornell Medicine (2022-2023) with Professor Emre Aksay. He completed his undergraduate studies at Princeton University (2013) with a B.S.E. in Chemical Engineering and minors in Engineering Physics and Applied Mathematics, working with Professor Howard Stone. His research methodology combines analytical theory development with advanced numerical techniques including the finite element method and molecular dynamics simulations. A distinctive aspect of his work involves creating physics-based machine learning approaches that strictly adhere to fundamental physical laws and balance equations. The group frequently draws from continuum mechanics (both fluid and solid mechanics), transport phenomena, statistical mechanics, irreversible thermodynamics, and electrodynamics. Dr. Sahu's publication record demonstrates significant contributions to understanding biological membranes, with multiple papers in Physical Review Letters addressing membrane instabilities, non-equilibrium fluctuations, and computational methods. His recent work on the Arbitrary Lagrangian-Eulerian finite element method represents an important advancement in computational techniques for membrane dynamics. The Sahu Lab actively recruits graduate students through the UT Austin Chemical Engineering program and welcomes postdoctoral scholars and undergraduate researchers interested in theoretical and computational approaches to soft matter physics. The lab emphasizes deep scientific thinking over prior research experience, particularly for undergraduate students.

• Numerical Analysis
• Scientific Computing
• Data Science
• +4 more

Per-Gunnar J. Martinsson serves as Deputy Director of the Oden Institute and Professor of Mathematics at the University of Texas at Austin, holding the W. A. "Tex" Moncrief, Jr. Endowment in Simulation-Based Engineering and Sciences. He maintains an affiliated professorship at the Royal Institute of Technology (KTH) in Stockholm, where he chairs the MathDataLab scientific advisory board. Previous appointments include faculty positions at the University of Oxford, University of Colorado Boulder (2005-2017), and Yale University. His educational background includes: Ph.D. in Computational and Applied Mathematics, University of Texas at Austin, 2002 Dr. Martinsson's research spans numerical analysis, scientific computing, and data science, with emphasis on randomized linear algebra methods, accelerated direct solvers for elliptic PDEs, structured matrix computations, and numerical techniques for scattering problems, computational fluid dynamics, and acoustics. His work extends to applied harmonic analysis, fast multipole methods, boundary integral equations, and modeling of heterogeneous materials and bandgap phenomena. His notable recognition includes: Germund Dahlquist Prize by SIAM (2017) He actively contributes to the Center for Numerical Analysis and Center for Scientific Machine Learning at the Oden Institute, while providing strategic leadership to KTH's MathDataLab through its scientific advisory board.

Enoch YeungView profile

Associate Professor

• Systems Biology
• Control Systems
• Machine Learning
• +7 more

Enoch Yeung is an Associate Professor in the Department of Mechanical Engineering at the University of California, Santa Barbara (UCSB). His research focuses on systems biology, control systems, machine learning, and data mining, with a particular emphasis on understanding how mechanical forces in DNA regulate gene dynamics and cell fate. He leads projects on distributed biological computing, data-driven control architectures, and synthetic biological systems design, supported by funding from DARPA, NSF, and the U.S. Army. Yeung holds a PhD in Control and Dynamical Systems from the California Institute of Technology and a BS in Mathematics from Brigham Young University. His work integrates methods from DNA biophysics, synthetic biology, microfluidics, and control theory to study genome organization and cellular decision-making. Recent projects include the DARPA Living Foundries program, the NSF Molecular Programming Project, and the AFOSR Biological Research Initiative. He has received numerous awards, including the NSF Early CAREER Award and Young Investigator Award from the U.S. Army. His lab conducts interdisciplinary research, including a 2024 Summer Synthetic Biology Workshop for high school students. Key research themes include DNA supercoiling dynamics, biophysical feedback control in cells, and scalable Koopman operator methods for analyzing complex biological systems. Lab Focus: Biological Control Lab explores DNA mechanics, synthetic biology, and data-driven modeling. Grants & Collaborations: PI on multi-institutional programs involving PNNL, DARPA, and NSF. Advisory Roles: Served on panels for DARPA, NIST, and the National Defense University.

Pascal HitzlerView profile

Professor

• Neurosymbolic Artificial Intelligence
• Semantic Web
• Knowledge Graphs
• +7 more

Pascal Hitzler is a University Distinguished Professor and holds the endowed Lloyd T. Smith Creativity in Engineering Chair at Kansas State University's Department of Computer Science, Carl R. Ice College of Engineering. He directs the Center for Artificial Intelligence and Data Science (CAIDS) and the Institute for Digital Agriculture and Advanced Analytics (ID3A). Previously, he held roles at Wright State University, Karlsruhe Institute of Technology, and TU Dresden. His research focuses on neuro-symbolic AI, semantic web technologies, knowledge graphs, and ontology engineering. Education: PhD in Mathematics (2001, University College Cork), Diplom in Mathematics (1998, University of Tübingen). Academic achievements include over 400 publications, founding editor roles for journals like Neurosymbolic Artificial Intelligence , and leadership in organizations like the Neural-Symbolic Learning and Reasoning Association. Research interests include AI explainability, knowledge representation, and interdisciplinary applications of semantic technologies. He leads the DaSe Lab for Data Semantics, advancing projects like the KnowWhereGraph and Enslaved.org Hub Knowledge Graph. His work bridges symbolic AI with neural networks, emphasizing practical applications in agriculture, environmental science, and historical data preservation. Grants and collaborations span academic, industrial, and international partners. He has advised numerous students and researchers, contributing to both theoretical advancements and real-world semantic systems deployments.

Federico NutarelliView profile

Assistant Professor

• International Trade
• Health Economics
• Machine Learning
• +3 more

Federico Nutarelli is an Assistant Professor of Economics at the IMT School for Advanced Studies Lucca, Italy. His research focuses on the intersection of machine learning and economic analysis, particularly in international trade, health economics, and industrial organization. He holds a Ph.D. in Economics from IMT Lucca, and previously conducted postdoctoral research at Bocconi University. In 2024, he was a Visiting Scholar at MIT Sloan School of Management. Key research interests include causal machine learning methods to analyze heterogeneous firm responses to economic shocks, pharmaceutical market pricing strategies, and structural demand models. His work bridges methodological rigor with applied relevance, contributing to health economics, trade dynamics, and innovation policy. Recent publications (2020–2025) explore topics such as matrix completion for world trade analysis, machine learning applications in economic complexity, and modeling innovation ecosystems. His work often employs advanced statistical techniques like Shapley values and reinforced Bernoulli processes. No scientific awards were explicitly mentioned in the provided texts. Federico collaborates with institutions like Bocconi University and MIT Sloan, reflecting his interdisciplinary network in economics and data science.

• Optimal Control of Partial Differential Equations
• Variational Inequalities
• Nonsmooth Infinite-dimensional Optimization
• +5 more

Dr. Constantin Christof is a Lecturer (Akademischer Rat auf Zeit) at the Department of Mathematics , Technische Universität München , with prior roles as a W2 Stand-in Professor at Universität Augsburg and Research Associate at TUM and TU Dortmund. His research focuses on Optimal Control of PDEs , Variational Inequalities , and Nonsmooth Optimization , with applications in Non-Newtonian Fluids and Neural Networks . May 2015 - July 2018: Dr. rer. nat. in Mathematics, TU Dortmund Oct. 2013 - July 2014: MAST (Part III of Mathematical Tripos), University of Cambridge Oct. 2009 - Sept. 2012: B.Sc. in Technomathematics and Mathematics, TU Dortmund Christof's work bridges Finite Element Error Analysis , Sensitivity Analysis , and Physics-Guided Machine Learning , particularly in problems involving Contact Mechanics and Parabolic PDE Constraints . His recent publications address challenges in Semilinear Elliptic PDEs , Obstacle Problems , and Nonsmooth Superposition Operators , with a focus on theoretical and numerical advancements. Scientific awards include the Dissertation Award and Best Graduate Award from TU Dortmund, and the Award for Academic Excellence by the Minister President of North Rhine-Westphalia. He has supervised 11 theses at the Master's and Bachelor's levels, covering topics from Neural Network Surrogate Models to Bingham Fluid Simulations .