Find Academic Supervisors

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.

Tillman WeydeView profile

Academic

• Machine Learning
• Signal Processing
• Data Analysis
• +5 more

Dr. Tillman Weyde is a Reader in the Department of Computer Science at City, University of London , where he has been employed since 2021. He leads the Machine Intelligence and Media Informatics Research Group and is a member of the Machine Learning Group . Prior to this, he served as Senior Lecturer (2009–2021) and Lecturer (2005–2009) at City, and worked as a researcher at the University of Osnabrück (2001–2005), coordinating the MUSITECH project. His academic background includes PhD in Music Technology (2002), MSc in Computer Science (1999), and MSc in Mathematics, Music, Philosophy & Pedagogy (1994), all from the University of Osnabrück. Research Focus: Machine learning and signal processing methods for data analysis with applications in finance, audio, NLP, music, health, security, and education. His recent work emphasizes inductive biases in neural networks for rule-learning, extrapolation, generalization, and interpretability. Grants & Projects: Principal Investigator for the AHRC-funded Digital Music Lab (2012–2017) and Integrated Audio-Symbolic Model of Music Similarity (2017–present). Co-investigator in Innovate UK and EPSRC projects on safer gambling ( Advancing Consumer Protection , 2015–2018) and Raven (2012–2021). Collaborations: Affiliated with the Institute of Cognitive Science (Osnabrück), Intelligent Systems Research Laboratory (Reading), and the MPEG Ad-Hoc Group on Symbolic Music Representation. Awards: Co-author of the 2000 Comenius Medal-winning educational software Computer Courses in Music Ear Training and co-editor of the Osnabrück Series on Music and Computation . Publications: Over 150 peer-reviewed works including conference papers, journal articles, and book chapters, focusing on interdisciplinary applications of machine learning in music, health, and finance. Students: Supervised 13 PhD students across topics like grammar bias in neural networks, emotion recognition from audio, extrapolation behavior in neural networks, relation-based patterns, legal text parsing, and more.

• Signal Processing
• Machine Learning
• Neural Networks
• +3 more

Professor Danilo P. Mandic, affiliated with Imperial College London, UK, is a leading researcher in signal processing, machine learning, and biomedical signal analysis. His work spans quaternion algebra, tensor networks, and neural networks for real-world applications. 2025: Published 11+ works on EEG/PPG analysis, quantum learning, and tensor-based LLM compression 2024: Active in interpretable transformers, graph learning for financial data, and hearable devices Research focuses on hypercomplex signal processing, graph neural networks, and medical AI applications. Recent work explores quaternion calculus for signal processing, tensor network structures for LLMs, and hearable device optimization. Key publication trends include: 2025 emphasis on quantum-aware learning, 2024 graph-based time series clustering, and 2023 foundational work on graph CNNs and matched filtering approaches. Collaborates extensively with Dongpo Xu, Sayed Pouria Talebi, Clive Cheong Took, and Tobias Reichenbach on projects involving ear-EEG, ECG enhancement, and financial sentiment analysis.

• History of Mathematics
• 19th Century Mathematics
• Mathematics Education
• +3 more

Adrian C. Rice is Professor of Mathematics and current Chair of the Department of Mathematics at Randolph-Macon College, holding the Dorothy and Muscoe Garnett Professorship. He joined the institution in 1999 as an assistant professor, earned tenure in 2005, and achieved full professorship in 2010. Previously, he held visiting positions at the University of Virginia (1998-99) and University of Oxford (2014-15). His educational background includes: PhD in Mathematics, Middlesex University (1997) MSc in History & Philosophy of Science and Mathematics, King's College London (1993) BS in Mathematics, University College London (1992) Professor Rice specializes in the history of 19th-century mathematics with particular focus on British mathematicians. His research examines conceptual developments in algebra, calculus, and numeracy through biographical studies of figures like Augustus De Morgan, Ada Lovelace, and James Joseph Sylvester. He actively bridges historical scholarship with contemporary mathematics education, creating classroom resources based on historical problems and analyzing mathematical eponymy. His 13 recent publications (2019-2024) reveal consistent emphasis on historical analysis of mathematical concepts, with growing attention to gender studies in mathematics through Ada Lovelace research. The work demonstrates interdisciplinary connections between mathematical history, education theory, and social contexts of 19th-century science. Award highlights include: Paul R. Halmos – Lester R. Ford Award (2019, 2025) Catherine Richards Prize (2021, 2025) George Pólya Award (2022) Corresponding membership, International Academy of the History of Science (2019) As department chair and frequent course developer, Professor Rice mentors undergraduate researchers through independent studies while teaching diverse courses from Introductory Logic to History of Mathematics. His collaborative projects with international scholars advance historical scholarship through editorial work and cross-institutional research initiatives.

Brent EverittView profile

Professor

• Algebra
• Topology
• Combinatorics
• +3 more

Brent Everitt is a Professor in the Department of Mathematics at the University of York, where he has been since 1999. He holds a Readership position and has previously held roles such as Senior Lecturer. His academic journey includes undergraduate studies at the University of Auckland, followed by postgraduate degrees at the University of Toronto and the University of Auckland. Before joining York, he held positions at the Universities of Aberdeen, Warwick, and Durham. Everitt’s research focuses on algebra, topology, and combinatorics, with a particular emphasis on homological methods in algebra, partial symmetry through reflection monoids, representation theory of groups and monoids, and geometric manifolds. Collaborators include Paul Turner, John Fountain, and James East. His work on hyperplane arrangements, matroids, and Coxeter groups has led to significant contributions in algebraic topology and geometric group theory. He has supervised eight PhD students, including Majed Albaity and Jim Woodward. His research projects include exploring sheaf homology, minimal hyperbolic manifold volumes, and the interplay between combinatorial structures and algebraic frameworks. He has been involved in grants such as the Heilbronn small grant scheme on diagrammatic intuition and deep learning in mathematics. Everitt is actively engaged in academic outreach, delivering invited talks globally on topics like reflection monoids, Khovanov homology, and hyperbolic manifolds. His teaching contributions include courses on Galois theory and algebraic topology, reflecting his dedication to both research and education.

Andreas WinterView profile

Professor

• Quantum Shannon theory
• Classical Shannon theory
• Entropy and applications
• +5 more

Andreas Winter is an ICREA Research Professor at Universitat Autònoma de Barcelona and holds a Hans Fischer Senior Fellowship at TUM-IAS, Technical University of Munich. He specializes in quantum and classical information theory with affiliations at the University of Cologne's Department of Quantum Information and Computation. His research examines fundamental limits in quantum communication, entropy applications, and quantum computing foundations. Education: Diploma in Mathematics, Freie Universität Berlin Ph.D. in Mathematics, Universität Bielefeld Research: His interdisciplinary work bridges quantum Shannon theory, thermodynamics, and discrete mathematics, exploring quantum channel capacities, information tradeoffs, and cryptographic protocols. Recent publications demonstrate advances in quantum coding efficiency and high-dimensional quantum systems. Awards: 2022: Hans Fischer Senior Fellowship, Alexander von Humboldt Prize, QCMC Quantum Award 2017: IEEE Information Theory Paper Award 2012: Whitehead Prize (LMS) 2007: Philipp Leverhulme Prize Leadership: Leads the Quantum Information Theory Focus Group at TUM-IAS, collaborating with Prof. Holger Boche on quantum communication frameworks.

Philip CollinsView profile

Senior Lecturer

• Soil mechanics
• Ice growth impacts on soil properties
• Quaternary geology and landforms
• +2 more

Dr Philip Collins is Deputy Dean (Academic Affairs) and Senior Lecturer in Geology & Geotechnical Engineering at Brunel University London's College of Engineering, Design and Physical Sciences. His responsibilities include oversight of international partnerships, student recruitment, and equity & inclusivity initiatives, while maintaining active research in geological and geotechnical domains. College-level committee leadership: Senate, Education Committee (Chair), Postgraduate Research Directors Panel (Chair) Professional affiliations: Fellow of Geological Society of London, Royal Geographical Society; Graduate Member of Institution of Civil Engineers 25+ years of industry engagement with Engineering and industrial partners Research focuses on soil mechanics, ice growth impacts on soil properties, Quaternary geology, sea level change, and engineering materials. His recent work explores heat and mass transfer in freezing soils, brittle rock failure modeling, and soil-structure interaction under extreme loads, with significant open-access publications since 2022. As an active PhD supervisor, he has guided students through topics including alkali-activated concrete behavior, dam stability on problematic substrates, and geophysical assessments of coastal aquifers. He has also contributed to 40+ total publications and participated in media outreach regarding engineering and earth science issues like sinkholes and flooding.

• Integral Geometry
• Finsler Geometry
• Riemannian Geometry
• +2 more

Prof. Andreas Bernig is a faculty member at Goethe University Frankfurt am Main, affiliated with the Department of Computer Science and Mathematics. He has held a W3 professorship in Differential Geometry since October 2009 and served as Dean of the Faculty (2017-2019) and Director of the Institute for Mathematics (2022-2024). His research spans Integral Geometry, Finsler Geometry, Riemannian Geometry, Geometric Inequalities, and Geometric Measure Theory, with a focus on valuations, kinematic formulas, and curvature measures in singular and pseudo-Riemannian settings. His recent publications explore topics such as the Hard Lefschetz theorem in convex valuation theory Weyl principle for Kähler manifolds Kinematic formulas in pseudo-Riemannian space forms Dual area measures in Hermitian integral geometry Invariant valuations on complex and quaternionic spaces These works often involve collaborations with leading mathematicians like J.H.G. Fu, Gil Solanes, and Thomas Wannerer. Prof. Bernig has received notable scientific recognition, including First prize at the German Mathematical Olympiad (1991, 1992) DFG and SNFS funding for projects like "Invariants of Singular Spaces" and "Tensor Valuations" He has supervised doctoral and Master’s students such as Luca Iffland, Frederik Herget, and Frank Steinke, and actively participates in international conferences and workshops in integral geometry, convex geometry, and geometric analysis.

• Artificial Intelligence
• Machine Learning
• Neural Networks
• +3 more

Călin-Adrian POPA is a Full Professor at the Department of Computer and Software Engineering, Politehnica University of Timişoara. He holds a Ph.D. in Computer Science and Information Technology (2015) from Politehnica University Timişoara, and additional degrees in Mathematics from West University of Timişoara (B.Sc. 2013, M.Sc. 2015). His research focuses on artificial intelligence, machine learning, and neural networks, with specializations in complex-valued systems (octonion, quaternion, Clifford algebra), stability analysis, and synchronization of neural networks. He has been awarded the 'Profesor Bologna' Distinction (2017). Research interests include: Advanced neural network architectures Deep learning for computer vision Fractional-order systems Nonlinear dynamics and control Applications in robotics and astrophysics His publications span 2014–2025, emphasizing theoretical contributions to neural networks and practical applications in computer vision and robotics. He supervises a large cohort of PhD students in AI-related fields.

• Differential Geometry
• Riemannian Submanifold Geometry
• Symmetry in Mathematics
• +2 more

Miguel Domínguez Vázquez is an Associate Professor at the Department of Mathematics, Faculty of Mathematics, University of Santiago de Compostela. He is also a researcher at the Galician Center for Mathematical Research and Technology (CITMAga). His research focuses on symmetry and shape from the viewpoint of differential geometry and Riemannian submanifold geometry. He obtained his PhD from the University of Santiago de Compostela in 2013 with the thesis "Isoparametric foliations and polar actions on complex space forms" under the supervision of Dr. José Carlos Díaz-Ramos. Research Interests: Domínguez Vázquez's work spans several areas of differential geometry including: Isoparametric hypersurfaces and foliations in symmetric spaces Polar and cohomogeneity one actions Homogeneous submanifolds in complex space forms Geometric analysis of overdetermined boundary problems Ricci curvature properties in Riemannian geometry Publication Trends: His recent articles (2021-2024) demonstrate a consistent focus on geometric structures in symmetric spaces, with particular emphasis on isoparametric hypersurfaces, homogeneous submanifolds, and curvature properties. The works frequently combine Riemannian geometry with Lie group theory and geometric analysis. PhD Supervision: He has supervised several doctoral students including: Ángel Cidre Díaz (ongoing) Tomás Otero Casal (2024) Alberto Rodríguez Vázquez (2022) Olga Pérez Barral (2020) Víctor Sanmartín López (2019) Cristina Vidal Castiñeira (2016) Research Leadership: He leads the project "Submanifolds, curvature and geometric equations from the viewpoint of symmetry" (PID2022-138988NB-I00) and coordinates the "Symmetry and Shape" conference series. He collaborates with researchers internationally including Jürgen Berndt (King's College London) and Andreas Kollross (Universität Stuttgart).

Anurag PurwarView profile

Associate Professor

• Robotics Design
• Kinematic Analysis
• Machine Learning in Engineering
• +3 more

Dr. Anurag Purwar is an Associate Professor of Mechanical Engineering at Stony Brook University, directing the Computer-Aided Design and Innovation Lab and serving as PI for NSF I-Corps. He holds a Ph.D. from Stony Brook (2005) and a B.Tech. from IIT Kanpur (1995). His research merges rigid body kinematics with machine learning for mechanism and robot design, yielding 107+ peer-reviewed publications and patents licensed to industry. Key projects include the sit-to-stand walker assistive device (SAE Top 100 Award) and MotionGen software tools. Education: Ph.D., Stony Brook University (2005); B.Tech., IIT Kanpur (1995) Awards: A.T. Yang Award (2017), SAE Top 100 Award (2016), ASEE Distinguished Teaching Award (2021) Leadership: Program Chair (ASME 2014), Conference Co-Chair (IDETC 2016), NAI Senior Member Research focuses on machine learning-driven design of mechanisms, robotics, and assistive technologies. His labs develop algorithms for path synthesis, generative design, and kinematic analysis. He actively commercializes innovations through industry partnerships and has spun off startups like MotionGen.io.

Robert FischerView profile

Professor

• Precoding and Signal Shaping
• Equalization Algorithms
• OFDM Transmission Systems
• +7 more

Prof. Dr.-Ing. Robert Fischer has been a full professor for Communications and Signal Theory at the University of Ulm, Germany, since 2011. He specializes in fast digital transmission techniques, including single- and multicarrier modulation, with a focus on precoding and shaping methods for high-rate systems. Research Interests: His work spans Precoding and Signal Shaping , Equalization Algorithms , OFDM Transmission Systems , Low-Complexity Receivers , MIMO and Multiuser Communications , Ultra-Wideband , Information Theory , Channel Coding , Physical-Layer Security , and Compressed Sensing . Recent publications emphasize applications in THz communication, MIMO systems, and compressed sensing. Scientific Recognition: He has received multiple awards, including the Promotionspreis der Technischen Fakultät (1997) Literaturpreis der ITG (2000) Wolfgang-Finkelnburg-Habilitationspreis (2002) Philipp-Reis-Preis (2005) Christian Doppler Laboratory Industrial Award (2007) Best Paper Award at International OFDM Workshop (2012) Teaching: At Ulm University, he teaches Signals and Systems , Communications Engineering , and MIMO Systems . Previously, he taught courses like Kanalcodierung (Channel Coding) at University Erlangen (1998–2010) and short courses at ETH Zürich and TU Berlin.

David M.J. CalderbankView profile

Professor

• Differential Geometry
• Geometric Analysis
• Kähler Geometry
• +7 more

David M.J. Calderbank is a Professor in the Department of Mathematical Sciences at the University of Bath , England. He is actively engaged in research and teaching, offering advanced courses such as Projective Geometry, Differential and Geometric Analysis, and Group Theory. His research lies at the intersection of differential geometry, geometric analysis, and mathematical physics, with a particular focus on Kähler and Einstein metrics, integrable systems, and parabolic geometries. His work often explores the interplay between geometric structures and algebraic conditions such as stability. The recent publications highlight a sustained focus on extremal and Einstein metrics, c-projective and ambitoric geometry, and integrability in geometric contexts. His work frequently involves collaborations with prominent geometers such as Vestislav Apostolov, Paul Gauduchon, and Michael Singer. No scientific awards are mentioned in the provided materials. He advises no students listed in the provided texts. His research has been supported through standard academic channels, though specific grants are not detailed. He has collaborated extensively, notably with Tammo Diemer on conformal geometry and invariant operators. While no formal lab or research team is described, his collaborative publication record suggests an active research group or network in differential geometry at Bath.

• Algebraic Number Theory
• Automorphic Forms
• Galois Representations
• +15 more

Dan Fretwell is a Lecturer in Security and Protection Science within the School Of Mathematical Sciences at Lancaster University. His academic journey includes a PhD from the University of Sheffield (2015) under Prof. Neil Dummigan, a Heilbronn Research Fellowship at the University of Bristol (until 2022), and a Lecturer position at the University of South Wales (2022-2023). His research spans Algebraic Number Theory with extensive work on: Quadratic forms, lattices, and error correcting codes Modular forms, elliptic curves, and number fields Automorphic forms, Galois representations, and L-functions Interacting particle systems with applications in Statistical Mechanics Fretwell's work is significantly motivated by the Langlands program, focusing on computational evidence for conjectures and practical applications. His recent publications show a clear trajectory toward cybersecurity applications, particularly in cryptography and quantum computation. His 2025 publication on 2-superirreducible polynomials over finite fields demonstrates this applied direction. The publications collectively reveal expertise across pure number theory, computational mathematics, and increasingly relevant cryptographic applications. He teaches MATH320: Mathematical Cryptography and supervises PhD students in Algebraic Number Theory with emphasis on Modular Forms and Galois Representations. His professional activities include public engagement through the STEM Lecturer Series, "The Magic of Maths" public lecture, Pint of Science events, and school outreach programs at Winstanley College and Rochdale Sixth Form College.

• Computer Graphics
• Physics Based Animation
• Computer Vision
• +1 more

Knud Henriksen serves as a Part-time Lecturer at the Department of Computer Science (DIKU), University of Copenhagen, within the Image Analysis, Computational Modelling and Geometry research section. His academic profile integrates teaching and research in computer graphics, physics-based animation, and computer vision, contributing to DIKU's expertise in visual computing methodologies. His educational background comprises: Elektroingeniør (Electrical Engineering) Cand. Scient (Master of Science) Ph.D. Henriksen's research focuses on Computer Graphics, Physics-Based Animation, Computer Vision, and Mathematics, with current investigations into inverse kinematics using bone representations and quaternions. His work emphasizes improving computational efficiency and realism in character animation through mathematical modeling and geometric algorithms. Analysis of his 30 publications (2002-2008) reveals consistent innovation in animation algorithms, particularly in inverse kinematics, physics simulation, and spline-based modeling. These contributions bridge theoretical computer graphics with practical applications in gaming and virtual reality, demonstrating robust solutions for 3D interaction and character rigging. No scientific awards are documented in the available information. Henriksen has supervised graduate projects including a 2008 thesis on quaternion-based inverse kinematics. While specific grant details are absent, his research aligns with DIKU's interdisciplinary approach. He operates within the Image Analysis, Computational Modelling and Geometry section, which collaborates extensively with industry on visual computing challenges.