Find Academic Supervisors

• Sustainable urban transport
• Urban form
• Land use planning
• +7 more

Yngve Karl Frøyen is a Professor at the Department of Architecture and Planning within the Faculty of Architecture and Design at the Norwegian University of Science and Technology (NTNU). Since 2010, he has taught and coordinated spatial and transport planning in the master's program in physical planning, while also leading GIS and geodata activities across academic programs. His research focuses on sustainable urban transport , emphasizing walking, cycling, and public transit as tools to enhance urban systems. He investigates how urban form —including land use, density, and functional mix—affects travel behavior, with specific projects on retail location transport impacts, cycling infrastructure modeling, and park-and-ride solutions in urban peripheries. Key trends in his recent publications include urban ecology , smart city geospatial analysis , and pedestrian/cycling mobility . His work integrates GIS, accessibility metrics, and land use-transportation interdependencies, reflecting collaborations with institutions like SINTEF and Asplan Viak. Doctoral training in transport economics and impact analysis 9-year research at the Norwegian Institute of Urban and Regional Research (NIBR) Consulting and project management in transport modeling, electronic ticketing, and GIS applications Contributions to Norwegian transport policy frameworks

• Robotics
• Cognitive Systems
• Bio-inspired Robotics
• +4 more

Constantin Uhde is a PhD candidate at the Institute for Cognitive Systems (ICS) of the Technical University of Munich (TUM). His research focuses on integrating cognitive approaches with robotic planning to achieve robust, unsupervised task execution. He holds a Master's degree in Robotics, Cognition, and Intelligence from TUM and a Bachelor's in Mechatronics from Friedrich-Alexander University Erlangen. Research Interests include bio-inspired robotics, human-robot interaction, virtual reality applications in robotics, and path planning using multimodal sensor data. His work bridges theoretical cognitive science with practical robotic systems, emphasizing causal reasoning and transfer learning. Uhde teaches as a lecturer for the Advanced Seminar & Practical Projects in Cognitive Systems and has published in top-tier conferences such as IEEE CASE, IROS, and ICRA. His contributions range from visuomotor learning frameworks to benchmark datasets for symbolic grounding in robotics. He is part of the ICS lab team developing systems for humanoid robotics and neuroengineering applications, contributing to platforms like the Compact Omni-directional Mobile Platform and EEG Laboratory setups.

Jo BovyView profile

Professor

• Galactic Dynamics
• Dark Matter
• Stellar Astrophysics
• +3 more

Jo Bovy is a Professor and Canada Research Chair in Galactic Astrophysics at the University of Toronto's Department of Astronomy and Astrophysics. He specializes in galactic dynamics, dark matter, and the structural evolution of the Milky Way, leveraging large-scale surveys like Gaia and APOGEE. His research focuses on using kinematic and chemical data to trace galactic formation processes and dark matter distribution. Bovy is the lead developer of the galpy software library for galactic dynamics and co-authored a forthcoming textbook Dynamics and Astrophysics of Galaxies (Princeton UP, 2026). He has held leadership roles in the APOGEE survey and its successor APOGEE-2, advancing infrared spectroscopic studies of the Milky Way's bulge and disk. His accolades include the Sloan Fellowship (2016), Vera Rubin Prize (2019), and Steacie Prize (2024). Bovy advocates for open-source scientific software, with extensive contributions to projects like astroNN and pynbody. Education: Ph.D. 2011, New York University. Research emphasizes data-driven approaches, including machine learning for stellar age estimation and probabilistic density modeling. Active in international collaborations such as Euclid and SDSS-V. Currently exploring the implications of dark matter self-interactions on stellar streams and refining measurements of Galactic fundamental parameters through acceleration-based methods. Key contributions include modeling Galactic vertical motion dynamics, analyzing GD-1 stream disruptions via N-body simulations, and developing frameworks for chemodynamical tagging of dissolved star clusters. His work bridges theoretical modeling with observational data, fostering interdisciplinary advancements in astrophysical data analysis. Awards: Price Prize (2010) Rutherford Memorial Medal (2021) CAP Herzberg Medal (2025) Grants/Advising: Leads major survey initiatives and mentors researchers in computational astrophysics. Current projects include Euclid's Early Release Observations and Gaia Data Analysis.

John PyeView profile

Associate Professor

• High-Temperature Solar Thermal Energy
• Concentrating Solar Power (CSP)
• Industrial Decarbonisation
• +4 more

Associate Professor John Pye leads research in high-temperature solar-thermal systems and industrial decarbonisation at the Australian National University's School of Engineering. He holds a BE/BSc (University of Melbourne) and a PhD (University of New South Wales) focused on solar thermal modelling. His work bridges engineering innovation and sustainability, with a focus on green steel production, CSP technologies, and hydrogen applications. As a Visiting Scholar at Sandia National Laboratories, he advanced solar thermal testing methodologies. Educations: Bachelor of Engineering (Mech.) and Bachelor of Science (University of Melbourne, 1997) PhD in System Modelling of Compact Linear Fresnel Reflectors (UNSW, 2008) His research interests include solar thermal energy systems, concentrated solar power (CSP), and hydrogen-based industrial processes. Notable contributions include system-level optimisation of CSP plants, techno-economic analysis of green steel production, and solar-thermal beneficiation of iron ore. His work often integrates AI for optimisation and free/open-source engineering software. Recent publications focus on solar thermal applications in steelmaking, particle-based CSP systems, and hydrogen plasma metallurgy. Projects include the Gen3 Liquids Pathway for CSP and solar-driven thermochemical processes. Collaborations span industry and academia, addressing decarbonisation challenges in steel production and energy storage. Supervises research in solar thermal engineering and low-carbon technologies, contributing to Australia's role in zero-emissions commodity production. Active in policy submissions related to green energy and manufacturing frameworks.

• Applied Mechanics
• Robotics
• Precision Agriculture
• +5 more

Andrea Botta serves as a Fixed-term Assistant Professor in the Department of Mechanical and Aerospace Engineering (DIMEAS) at the Polytechnic University of Turin. He is an invited member of both the College of Electrical and Energy Engineering and the College of Mechanical, Aerospace, and Automotive Engineering. His academic career spans teaching Mechanics of Automatic Machines across multiple degree programs including Mechanical Engineering and Energy Engineering since the 2020/21 academic year. Botta's research focuses on Applied Mechanics and Robotics, with particular expertise in articulated robots, mobile manipulators, precision agriculture systems, and rehabilitation robotics devices. His work bridges theoretical mechanics with practical applications in agricultural automation and assistive technologies, addressing challenges in mobility platforms, mechanism design, and human-robot interaction. His research directly contributes to multiple UN Sustainable Development Goals including Zero Hunger, Good Health, Clean Energy, and Climate Action. His publication record shows consistent output with significant contributions in 2023-2025, demonstrating expertise across both agricultural and medical robotics domains. Recent work reveals a strong trend toward practical implementations of robotic systems for greenhouse agriculture, rehabilitation assistance, and hospital service applications, with notable emphasis on control strategies, kinematic modeling, and user-centered design. Scientific Recognition: Best Paper Award of Jc-IFToMM International Symposium (2022) Botta actively supervises doctoral research, currently guiding Francesco Amodio in the 40th cycle of the Mechanical Engineering PhD program. He participates in competitive research projects including PAL-HAND (Pneumatic And Lightweight Handheld Device) and TWIN-IT-ROMANS (Twinning IZTECH in Robotics Manufacturing Systems), with funding from European Union initiatives including EIT and Horizon Europe Widening Participation programs. His work demonstrates strong interdisciplinary collaboration across mechanical engineering, control systems, and application-specific domains. As a member of the Automation and Robotics research group within DIMEAS, Botta contributes to developing innovative robotic solutions with practical implementations in precision agriculture through projects like AGRIMARO.Q and rehabilitation technology through wearable assistive devices like WELiBot.

Yifan WangView profile

Research Fellow

• Gravitational Wave Astronomy
• General Relativity
• Data Analysis
• +3 more

Yifan Wang is a Postdoc/Research Fellow at the Department of Astrophysical and Cosmological Relativity , Max Planck Institute for Gravitational Physics (Albert Einstein Institute) in Potsdam, Germany. He obtained his B.S. (2015) from the University of Science and Technology of China and his Ph.D. (2019) from the Chinese University of Hong Kong. From 2019-2023, he worked at the Observational Relativity and Cosmology department in AEI Hannover. Research Focus : Data analysis of gravitational waves from compact binary coalescence, multi-messenger astronomy, testing general relativity, and black hole ringdown phenomena. Publications : His recent work (2025-2019) spans gravitational wave detection, compact binary systems (black holes/neutron stars), waveform modeling, multi-messenger correlations (gamma-ray bursts, FRBs), and tests of general relativity using open catalogs. Key subfields include eccentric binary black holes, quasi-normal modes, parity symmetry, and subsolar mass binaries. He collaborates with Alexander H. Nitz, Collin D. Capano, and others, contributing to LIGO/Virgo collaborations and catalogs like 4-OGC. Tools & Collaborations : Actively develops Python-based gravitational wave analysis tools (e.g., pycbc, pycbc-plugin-seobnr) and contributes to open-source projects. His GitHub activity reflects commits, pull requests, and code reviews in gravitational wave software repositories.

• Theoretical Physics
• Astrophysics
• General Relativity
• +6 more

Daniela Doneva, Ph.D., is a Lecturer at the Institute for Astronomy and Astrophysics (IAAT) , University of Tübingen. Her work spans theoretical and computational astrophysics, focusing on nonlinear gravitational phenomena in modified theories of gravity. Key affiliations: Institute for Astronomy and Astrophysics (IAAT), University of Tübingen Degree: Ph.D. in Physics Research interests include: Black Hole Scalarization : Spin-induced and curvature-induced scalarization mechanisms in black holes and neutron stars. Modified Gravity Theories : Einstein-Gauss-Bonnet, scalar-tensor theories, and teleparallel gravity extensions. Gravitational Wave Physics : Modeling waveforms, stability analysis, and LISA mission applications. Numerical Relativity : Simulations of compact object mergers and nonlinear evolutions. Her publications emphasize computational methods (e.g., neural network surrogates), stability analysis, and observational constraints from gravitational wave detectors like LISA. No scientific awards or student advisement details were found in the provided texts.

• Astrophysics
• Radio Astronomy
• Pulsar Studies
• +3 more

Dr. Ramesh Bhat is a Senior Research Fellow at Curtin University's School of Electrical Engineering, Computing and Mathematical Sciences (EECMS), affiliated with the Curtin Research Institute and Curtin Institute of Radio Astronomy (CIRA). His primary affiliation is with the Faculty of Science and Engineering. He is based at Curtin Perth Campus in Brodie Hall, Room 161. His research focuses on astrophysics and radio astronomy, particularly pulsar timing, gravitational wave detection using pulsar timing arrays, and the study of transient phenomena such as fast radio bursts (FRBs). He contributes to major projects like the High Time Resolution Universe (HTRU) survey, MeerTime, and the Murchison Widefield Array (MWA). Key research interests include pulsar population studies, interstellar medium interactions, signal processing for radio astronomy, and instrumentation development for next-generation telescopes like the Square Kilometre Array (SKA). His work spans theoretical models of pulsar emission mechanisms to observational studies of pulsar nulling, subpulse drifting, and gravitational wave backgrounds. Recent publications highlight advancements in pulsar survey techniques (e.g., GPU-accelerated analysis), discovery of new pulsars and FRBs, and constraints on cosmological models via pulsar timing arrays. His research often involves international collaborations, leveraging facilities like the Parkes radio telescope and the MWA. He actively contributes to radio interferometry, transient detection algorithms, and pulsar timing array data analysis. His work bridges observational astronomy with computational methods, aiming to advance understanding of compact objects and gravitational physics.

Niels AageView profile

Associate Professor

• Topology Optimization
• Acoustics and Vibroacoustics
• Biomechanics
• +5 more

Niels Aage is an Associate Professor in the Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU). His research focuses on topology optimization, biomechanics, and multiphysics modeling, with applications in acoustic devices, biomedical implants, and microelectromechanical systems (MEMS). He holds roles such as Vice President of the International Society for Structural and Multidisciplinary Optimization (2023–2027). Education and Professional Background: Conducted a 5-month research visit at the University of Colorado, Boulder (USA) in 2010. Specializes in giga-scale numerical modeling, finite element methods, and topology optimization algorithms. Research Interests: Develops novel methods for topology optimization of fluidic, thermal, and acoustic systems. Explores applications in patient-specific spinal implants, metamaterials with vibroacoustic bandgaps, and nonlinear dynamic substructuring. His work integrates machine learning and reduced-order modeling for efficient simulation. Publications: Over 100 peer-reviewed articles, including recent contributions on connectivity promotion in topology optimization (2025), vibroacoustic metamaterial design (2025), and anatomically conforming spinal fusion cages (2024). Research emphasizes high-resolution modeling and bridging computational design with additive manufacturing. Scientific Awards: ISSMO Haftka Young Investigator Award (2021), Equinor Prize 2020, and Hyperion Innovation Excellence Award (2017). Recognized for contributions to structural optimization and computational mechanics. Advising and Grants: Supervises multiple PhD projects, including work on vibroacoustic shape optimization, quantum-opto-mechanical systems, and smart hearing aid modeling. Engages in collaborative projects funded by industry and academia. Labs/Teams: Collaborates with DTU’s Solid Mechanics group and industry partners on projects involving topology optimization, multiphysics simulation, and biomedical engineering. Active in international conferences and serves on editorial boards.

Stuart LittlefairView profile

Professor

• Astrophysics
• Interacting binary stars
• High time resolution astrophysics
• +5 more

Professor Stuart Littlefair is a Professor of Astrophysics at the University of Sheffield's School of Mathematical and Physical Sciences. His research focuses on Interacting binary stars , Brown dwarfs and low-mass stars , Star formation , and High time resolution astrophysics . He contributes to projects like the Gravitational-wave Optical Transient Observer (GOTO), which detects transient astrophysical events. His work bridges observational astronomy and theoretical modeling, emphasizing multi-messenger astronomy and gravitational wave source identification. Research interests include studying accretion processes in compact binaries, AGN variability, and transient phenomena like gamma-ray bursts. Recent publications highlight his involvement in analyzing high-cadence optical/X-ray data (e.g., NGC 4395 AGN variability studies) and discovering peculiar systems such as inflated brown dwarfs in eclipsing binaries. He collaborates internationally, serving on committees like the ESO Observing Programmes Committee and the LSST:UK Board. Teaching activities include PHY241 Observational Astronomy . Professional roles include leading the Astrophysics Research Cluster and contributing to departmental administration (e.g., Head of Second Year Astrophysics). His work supports the University of Sheffield's astronomy infrastructure, including the GOTO telescope array.

• Astrophysics
• Particle Physics
• Neutrino Astronomy
• +5 more

Irene Tamborra is a Professor at the Niels Bohr Institute (University of Copenhagen) and leads the Particle Astrophysics group . She holds the Mercator Fellow visiting professorship at the Max Planck Institutes for Physics and Astrophysics in Garching, Germany. Her research bridges astrophysics and particle physics, focusing on multi-messenger astronomy through neutrinos , gravitational waves , and photons . Current research themes include: Stellar explosions (supernovae, gamma-ray bursts) Neutrino flavor evolution in extreme environments Physics beyond the Standard Model using astrophysical probes Nucleosynthesis of heavy elements Recent work (2024-2025) explores neutrino production mechanisms in compact transients, fast flavor instabilities , and multi-messenger signatures of stellar collapses. She collaborates extensively with institutions in Germany, Spain, and the US. Scientific awards: MERAC Prize (European Astronomical Society) Duggal Award (IUPAP) ERC Consolidator Award She leads the Particle Astrophysics group at the Niels Bohr Institute and contributes to supernova neutrino theory , neutrino quantum kinetics , and cosmic accelerators analysis.

Ondřej PejchaView profile

Associate Professor

• Astrophysics
• Binary Stars
• Common Envelope Evolution
• +7 more

Assoc. Prof. Ondřej Pejcha is an active researcher at the Institute of Theoretical Physics, Faculty of Mathematics and Physics, Charles University in Prague. His work focuses on connecting theoretical modeling, observational astronomy, and data science to understand time-domain phenomena in stellar systems, particularly binary stars and their evolution. Dr. Pejcha's research spans computational astrophysics, with emphasis on (radiation)(magneto)hydrodynamics simulations of binary star systems, common envelope evolution, and stellar mergers. His group develops advanced numerical methods to study transients such as stellar mergers and core-collapse supernovae, persistent variable sources including eclipsing binaries and pulsating stars, and stellar dynamics. They combine supercomputer simulations with semi-analytic models and machine learning techniques applied to astronomical data from surveys like ASAS-SN. The analysis of Dr. Pejcha's recent publications reveals a strong focus on computational approaches to binary star evolution, with increasing integration of machine learning methods in the latest works. His research addresses fundamental questions about common envelope evolution, mass transfer processes, and the connection between theoretical models and observational signatures in time-domain astronomy. ERC Consolidator grant for ROGALLO project (developing new simulation methods for binary stars) ERC Starting grant for Cat-In-hAT project (computational methods for binary star mergers) Czech Science Foundation grant for studying mass transfer in binaries Czech-American collaboration grant for ASAS-SN survey participation Primus award PRIMUS/SCI/17 from Charles University Dr. Pejcha actively mentors PhD students and postdocs, with recent advisees including Jakub Cehula and Milan Pešta. His group has secured substantial funding that supports internationally competitive salaries, dedicated computing resources including a specialized cluster with upcoming GPU enhancements, and travel funds. Alumni from his group have successfully obtained competitive postdoctoral positions and national/international fellowships. The group maintains strong international connections, regularly collaborating with institutions including Princeton University, Brown University, MPA Garching, and Warsaw University Observatory.

• Electronics
• Analog Design
• Circuits and Systems Theory
• +4 more

Professor İsmail Serdar Özoğuz is a distinguished academic at Istanbul Technical University , affiliated with the Department of Electronics and Communication Engineering . Holding the title of Professor since 2009, he has contributed extensively to analog circuit design, neural network applications, and wireless communication systems. Ph.D. in Electronics and Communications Engineering (1995) Department Head (2020-present) Vice Dean (2017-2020) Research Interests: His work spans Electronics , Analog Design , Circuits and Systems Theory , with recent focus on: Neural network-based filter optimization Memristor emulator circuits Spintronic devices for wireless and memory applications Intelligent optimization in RF designs Article Trends: Recent publications highlight AI integration in engineering challenges, power efficiency in wireless systems, and hardware-software co-optimization . His work bridges theoretical models (e.g., fractional-order neural networks) with practical implementations (e.g., GaN amplifiers). Scientific Awards: GEBIP Award (TUBA), 2002 Mustafa Parlar Foundation Research Incentive, 2003 TUBITAK Incentive Award, 2004 Grants & Projects: As Principal Investigator, he has led initiatives on: Spintronic devices for wireless/memory/analog uses Passive combiners in HF transmitters High-power GaN amplifier development Fractional-order neural network models

Jari VepsäläinenView profile

Assistant Professor

• Mechatronics Design
• Energy Efficient Systems
• Generative Design
• +7 more

Jari Vepsäläinen is an Assistant Professor at Aalto University's Department of Energy and Mechanical Engineering under the College of Engineering. He serves as Director of the Fluid Power group and specializes in mechatronics design, energy efficiency, and generative design methodologies. Research focuses on physics-based modeling for energy recovery AI/ML applications in electromechanical system design Applications in robotics, heavy machinery, and sustainable transportation His recent publications demonstrate expertise in hybrid systems, fluid power optimization, and AI-driven engineering, with a strong emphasis on electrification and efficiency across automotive, maritime, and industrial domains. Key areas: Mechatronics, Energy Systems, Generative Design Technologies: Digital Twins, IoT, Machine Learning Current projects involve thermal energy systems, electric motor optimization, and advanced control algorithms for mobile machinery.

• Materials Science
• Mechanical Engineering
• Manufacturing Engineering
• +5 more

Rohollah Ghasemi is a Senior Lecturer in Mechanical Engineering at the School of Engineering Science , University of Skövde. His research focuses on materials science , manufacturing processes , and tribology , with particular emphasis on compacted/graphite iron microstructure analysis and laser welding optimization . His recent publications (2022–2025) explore advanced manufacturing techniques, including deep learning applications for welding quality prediction and multi-physics simulations for recoil force validation. Earlier works (2014–2019) investigate abrasion resistance , scratch mechanisms , and austempering variables in cast iron systems. Key Research Trends : Process-induced stress modeling, laser welding of dissimilar materials, microstructural engineering of CGI, tribological behavior under load, meta-model optimization Collaborations : Kent Salomonsson, Tobias J. Andersson, Anders E.W. Jarfors, Attila Dioszegi