Find Academic Supervisors

Sebastian DiehlView profile

Professor

• Aquatic Ecology
• Ecological Modeling
• Climate Change Impacts on Ecosystems
• +5 more

Sebastian Diehl is a Professor at Umeå University's Department of Ecology, Environment and Geoscience. His research focuses on mathematical modeling of aquatic ecosystem dynamics, with particular emphasis on consumer-resource interactions and climate change impacts on northern lake ecosystems. Current affiliations: Umeå University (Department of Ecology, Environment and Geoscience) Previous affiliations: Ludwig-Maximilians-Universität München (Professor of Aquatic Ecology) Academic background: Biology undergrad from University of Göttingen, PhD in Animal Ecology from Umeå University (1994) Research interests center around aquatic ecosystem dynamics in response to environmental change, including: Climate change effects on lake ecosystems (temperature and terrestrial nutrient inputs) Mathematical modeling of consumer-resource interactions Benthic-pelagic coupling in nutrient and energy flows Phytoplankton-zooplankton dynamics under environmental stressors Trophic interactions in stream and lake systems Stoichiometric constraints on ecosystem function His recent publications (2025-2020) demonstrate an integrated approach combining mathematical modeling with experimental validation through field studies and lab experiments, focusing particularly on: Climate-induced regime shifts in lake ecosystems Stoichiometric mismatch in warming systems Functional response modeling Vertical niche partitioning in plankton Resource acquisition trade-offs Browning impacts on primary producers Administrative roles include: Final examiner for PhD education Chair of Umeå Marine Science Centre advisory council Steering group member of Integrated Science Lab (IceLab)

David R. ReichmanView profile

Professor

• Disordered Materials
• Glass-Forming Systems
• Soft Materials
• +3 more

David R. Reichman is the Centennial Professor of Chemistry at Columbia University, affiliated with the Department of Chemistry within the School of Arts and Sciences. His research focuses on the chemistry, physics, and biology of disordered materials, including glass-forming systems, soft materials (gels, colloids, emulsions), and biological systems. Key themes include disorder, dynamical heterogeneity, and metastable configurations. His work spans computational methods such as Quantum Monte Carlo, time-dependent variational principles, and exciton theory. Notable contributions include studies on singlet fission mechanisms, halide perovskites, and optically pumped phonon dynamics in superconductors. Leads the Reichman Group, based at 520 Havemeyer Hall. Active in cross-disciplinary collaborations, as seen in publications across journals like Nature Communications and Physical Review B . Research emphasizes bridging microscopic quantum phenomena with macroscopic material behavior, particularly in energy-related materials and nanostructured systems.

Mickael MounaixView profile

Research Fellow

• Photonics
• Optical Engineering
• Biomedical Imaging
• +3 more

Dr Mickael Mounaix is a Research Fellow at the School of Electrical Engineering and Computer Science, University of Queensland. His research focuses on controlling the spatial and temporal properties of light through complex disordered materials (e.g., multimode fibers, biological tissues). He leads projects on optical time reversal, spatiotemporal beam shaping, and nonlinear light propagation. Key achievements include demonstrating time-reversed optical waves (Nature Communications, 2020) and controlling light delivery in multimode fibers (Nature Communications, 2019). His work has been featured in Phys.org and highlighted in international conferences like CLEO and ECOC. Education background: Ph.D. in Physics (university unspecified). Collaborations include Nokia Bell Labs, Crawford Hill Labs, and international institutions. His lab employs spatial light modulators and advanced software techniques for light manipulation. A fully funded Ph.D. project is currently available. Research interests span photonics applications in biomedical imaging and telecommunications, with a focus on overcoming scattering limitations in complex media. Recent innovations include programmable spatiotemporal exotic beams (2025) and high-dimensional light tomography (2023). His work bridges theoretical optics with experimental photonics, addressing challenges in light delivery and control. Media and outreach: UQ News press releases, YouTube abstracts, and pedagogical conference presentations (e.g., 75-minute CLEO 2020 talk). No explicit awards listed, but publications in top-tier journals highlight his contributions. Advising: No listed students yet. Grants: Not explicitly detailed in provided texts. Lab/teams: Focus on transmission matrix methods, spatiotemporal engineering, and optical time reversal systems. Ongoing projects include developing optical time reversers and analyzing multimode fiber characteristics without coherence (Referenceless 2023 work).

Hanqing JinView profile

Associate Professor

• Mathematical Finance
• Stochastic Analysis
• Portfolio Optimization
• +3 more

Dr. Hanqing Jin is an Associate Professor in the Mathematical Institute at the University of Oxford, specializing in Mathematical Finance and Applied Stochastic Analysis. His research focuses on investor decision-making under non-utility behavior, dynamic portfolio optimization, and stochastic control problems in financial markets. Prior to Oxford, he held an Assistant Professorship at the National University of Singapore. He has contributed to foundational work on mean-variance portfolio selection, behavioral finance, and the application of stochastic processes to financial modeling. His academic background includes extensive work on continuous-time portfolio optimization, risk management frameworks, and the intersection of behavioral economics with quantitative finance. Notable contributions include studies on optimal lockdown policies during pandemics, blockchain consensus algorithms analysis, and the development of novel biomarker detection techniques using Raman spectroscopy. Dr. Jin's research integrates advanced mathematical techniques with real-world financial challenges, bridging theoretical models with practical applications in areas such as robo-advising systems and cryptocurrency frameworks. His work on transaction cost analysis and dynamic mean-variance strategies has been widely cited in both academic and industry contexts.

Robert BoydView profile

Professor

• Nonlinear Optics
• Optical Physics
• Quantum Optics
• +3 more

Robert Boyd is a Professor of Optics and Physics at the University of Rochester and holds a Canada Excellence Research Chair at the University of Ottawa. He leads major research initiatives in nonlinear optics, quantum optics, and metamaterials. His work spans theoretical and applied optics, with focus on nonlinear optical interactions, epsilon-near-zero materials, and advanced imaging techniques. Education: BS in Physics from MIT (1977), PhD in Physics from UC Berkeley (1977), supervised by Charles Townes. He joined the University of Rochester faculty in 1977 and expanded his research to the University of Ottawa in 2010. His research group operates in both institutions, emphasizing interdisciplinary collaborations. Research interests include nonlinear optical properties of materials, quantum optics, nanophotonics, and metamaterials. His team explores applications like optical imaging, plasmonic devices, and high-efficiency nonlinear processes in novel materials. Awards include Fellowships from the Optical Society of America and American Physical Society. He authored seminal textbooks such as Nonlinear Optics (1992) and holds nine US patents. His group’s work has produced over 350 publications and trained 33 PhD students. Labs and teams: The Boyd Group operates at both universities, with teams focused on nonlinear optics, quantum photonics, and metamaterials. Active projects include epsilon-near-zero-based devices, high-harmonic generation, and turbulence-resilient optical communications.

Luca SchenatoView profile

Professor

• Control Systems
• Distributed Optimization
• Federated Learning
• +5 more

Luca Schenato is a Full Professor in the Department of Information Engineering at the University of Padova. His research focuses on distributed control systems, federated learning, multi-agent optimization, and wireless communication protocols. He has extensive experience in developing algorithms for cyber-physical systems, with applications in robotics, smart grids, and sensor networks. Education and Appointments section lists his academic journey but lacks explicit details. He has held positions related to control systems and information engineering throughout his career. Research interests include: Design of resilient wireless control systems Federated learning architectures for edge computing Distributed optimization under communication constraints Robotics and multi-agent coordination Smart energy management systems His recent publications (2021–2025) demonstrate a strong focus on: Over-the-air federated learning innovations High-speed wireless control systems (e.g., 1 kHz Wi-Fi control) Resilient distributed optimization algorithms Human-centric building automation He has contributed to numerous projects related to networked control systems and has organized conferences like ECC13. His work emphasizes bridging theoretical control principles with practical industrial applications.

Thomas BifanoView profile

Professor

• Photonics
• MEMS (Microelectromechanical Systems)
• Adaptive Optics
• +4 more

Dr. Thomas Bifano is a Professor of Mechanical Engineering and Director of the Boston University Photonics Center. He holds affiliations with the Biomedical Engineering, Materials Science & Engineering, and Electrical & Computer Engineering departments. His research focuses on MEMS technologies, adaptive optics, and biomedical imaging applications. Dr. Bifano leads interdisciplinary initiatives in photonics, including commercialization of deformable mirrors via Boston Micromachines Corporation. He directs the Neurophotonics Research Training Grant and participates in the NSF Engineering Research Center on Cellular Metamaterials (CELL MET). His lab develops optical instruments for microscopy and telescope instrumentation, emphasizing light control through deformable mirrors. Recent work includes engineered heart tissue studies and high-throughput cardiac tissue screening. Education: PhD from North Carolina State University. Key Roles: Former Chair of the Manufacturing Engineering Department (1999-2006). Affiliations: Photonics & Optical Systems, Neuroscience & Neuroengineering. Grants & Collaborations: NSF CELL MET, BU Photonics Center innovation programs. Facilities: Manages state-of-the-art shared labs and a business innovation center at the Photonics Center.

Didong LiView profile

Assistant Professor

• Biostatistics
• Machine Learning
• Geometric Data Analysis
• +7 more

Dr. Didong Li is an Assistant Professor in the Department of Biostatistics at the Gillings School of Global Public Health , University of North Carolina at Chapel Hill. His research focuses on statistical methods for complex data, including manifold learning, nonparametric Bayesian inference, and spatial statistics, with applications in healthcare, genomics, and environmental health. He holds a PhD in Mathematics from Duke University (2020), and degrees from Beijing Institute of Technology (BS 2012, MS 2015). His research interests include dimension reduction, Gaussian processes, geometric data analysis, and network analysis. He has developed novel methods for analyzing electronic health records, single-cell RNA sequencing data, and spatial omics datasets. Notable contributions include the spherelet manifold approximation framework and the STimage-1K4M dataset. Dr. Li has received the Inaugural IMS Lawrence D. Brown PhD Student Award (2019) . He serves on the editorial board of the Journal of Machine Learning Research and organized sessions at JSM 2021-2022 on geometric Bayesian methods. His lab supports interdisciplinary collaborations, with ongoing projects in spatial transcriptomics, healthcare access analysis, and AI-driven medical informatics. Advising highlights include guiding students through successful PhD defenses (e.g., Dr. Sam Hawke, Dr. Jiawen Chen) and postdoctoral placements. His team secured a NVIDIA Academic Grant (2024) for multi-modal AI in spatial transcriptomics. The Li Lab maintains active partnerships with institutions worldwide, advancing both statistical theory and real-world applications.

Josh ReissView profile

Professor

• Audio Engineering
• Signal Processing
• Music Production
• +4 more

Josh Reiss is a Professor of Audio Engineering at Queen Mary University of London (QMUL), part of the School of Electronic Engineering and Computer Science . He holds additional roles including President-Elect and Fellow of the Audio Engineering Society (AES), and Visiting Professor at Birmingham City University. His research focuses on audio signal processing, procedural audio, and intelligent music production. He earned degrees including BSc in Physics, BSc in Mathematics, and a PhD. Research & Awards : Reiss has published over 200 papers, authored books like Intelligent Music Production , and received awards such as the AES Board of Governors Award (2009, 2010) and Best JAES Paper 2016. His work spans sound synthesis, dynamic range compression, and live audio systems. Teaching & Industry : Teaches modules like Artificial Intelligence and Sound Design. Co-founded startups LandR (AI mixing), Tonz, and Nemisindo. Leads the Centre for Digital Music at QMUL, advancing research in audio technology. Labs & Teams : Active in the Centre for Digital Music, collaborating on projects like the Open Multitrack Testbed and semantic audio evaluation tools.

Jeffrey F. RhoadsView profile

Professor

• Mechanical Engineering
• Energetic Materials
• Additive Manufacturing
• +5 more

Jeffrey F. Rhoads is the John and Catherine Martin Family Vice President for Research at the University of Notre Dame and holds the rank of Professor of Aerospace and Mechanical Engineering . He previously served as Executive Director of the Purdue Institute for National Security and held leadership roles in Purdue’s School of Mechanical Engineering, including director of the Ray W. Herrick Laboratories and the Purdue Energetics Research Center. His research focuses on energetic materials , additive manufacturing , sensors , and engineering education innovation . Rhoads is a Fellow of the American Society of Mechanical Engineers and has contributed to over 100 peer-reviewed articles across these domains. Education : BS, MS, and PhD in Mechanical Engineering from Michigan State University. Key Research Themes : Development of novel sensors for CO₂, hydrogen, and other gases using nanotechnology and polymer composites. Advances in 3D printing of energetic materials (e.g., propellants, explosives) with applications in defense and aerospace. Investigations into coupled oscillator systems and nonlinear dynamics. Pedagogical studies on blended learning, student resource usage patterns, and faculty development for instructional innovation. Recent Article Trends (2022–2025) : Over 30% of his recent publications address additive manufacturing of energetic materials , with others focusing on engineering education research and sensor technology . His work bridges fundamental engineering science with practical applications in national security and environmental monitoring. Awards : Fellow, American Society of Mechanical Engineers (ASME) Labs and Teams : Leads Notre Dame’s research infrastructure strategy and previously directed Purdue’s Herrick Laboratories and Energetics Research Center. His work integrates interdisciplinary teams from mechanical engineering, materials science, and education research.

• Nonlinear Partial Differential Equations
• Calculus of Variations
• Materials Science
• +5 more

Robert V. Kohn is the Silver Professor of Mathematics at New York University, affiliated with the Courant Institute of Mathematical Sciences (CIMS). He holds academic positions within the Department of Mathematics at the College of Arts & Science and the Graduate School of Arts & Science. His research focuses on nonlinear partial differential equations (PDEs), calculus of variations, and their applications to materials science, thin elastic sheets, and machine learning. Education: Ph.D. in Mathematics from Princeton University (1979), M.Sc. from the University of Warwick (1975), and A.B. from Harvard University (1974). Research interests span elastic energy-driven pattern formation (e.g., wrinkling, folding), PDEs in machine learning (e.g., prediction with expert advice), and continuum mechanics. Recent work includes variational analysis of thin film mechanics and PDE-based approaches for binary sequence prediction. His articles explore topics ranging from metamaterials to stochastic growth models. Notable themes in his publications include energy minimization in materials, optimal control analogies in learning algorithms, and mathematical modeling of physical phenomena. While no formal awards are listed, his contributions to PDE theory and applied mathematics are widely recognized. Advising and grants details are not explicitly documented here.

Marc SchmidtView profile

Professor

• Neurobiology
• Animal Behavior
• Physiology
• +3 more

Marc Schmidt is a Professor of Biology at the University of Pennsylvania's School of Arts & Sciences, co-directing the Biological Basis of Behavior Program. He holds a B.A. in Biology from Swarthmore College (1986) and a Ph.D. in Neuroscience from Colorado State University (1993), followed by postdoctoral work at the California Institute of Technology in Neuroethology (1993–1999). His research focuses on neural mechanisms underlying courtship behaviors in songbirds, particularly the brown-headed cowbird, integrating neurobiology, computational methods, and engineering to study vocal and social displays. Key projects include analyzing neural circuits for vocal production, respiratory control, and female mate choice using a 'smart aviary' equipped with computer vision and wireless neural recording systems. Collaborations span engineering, physics, and other disciplines to track social behavior dynamics and neural activity in naturalistic settings. Research highlights include unraveling the role of the 'song system' in coordinating non-vocal courtship behaviors and linking brain activity to social context. Schmidt's work bridges neural circuitry with behavioral outcomes, emphasizing interdisciplinary approaches to understand complex social interactions. His lab employs advanced tracking systems and computational models to quantify group behavior across breeding seasons, aiming to predict and explain social network dynamics. He teaches courses in cellular/molecular neurobiology and animal behavior, contributing to both undergraduate and graduate education. Publications span vocal motor control, norepinephrine modulation, and social network analysis. His NSF-funded 'smart aviary' project exemplifies translational research, merging engineering and biology to study avian social behavior. Schmidt's contributions advance our understanding of neural mechanisms behind social communication and the evolution of courtship displays in vertebrates.

Ulrich ParlitzView profile

Adjunct Professor

• Nonlinear Dynamics
• Chaos Theory
• Biomedical Physics
• +7 more

Ulrich Parlitz is an Adjunct Professor of Physics at Georg-August-University Göttingen and a Scientist leading the Biomedical Physics Group at the Max Planck Institute for Dynamics and Self-Organization. His research focuses on nonlinear dynamics, chaos theory, and biomedical applications, particularly in cardiac dynamics and excitable media. He has held visiting positions at institutions like UC San Diego and the Santa Fe Institute. Education: 1987 PhD in Physics, Georg-August-University Göttingen 1984 Diploma in Physics, Georg-August-University Göttingen Research Interests: Analysis of nonlinear systems (neurons, lasers, oscillators) Bifurcation and chaos phenomena Data-based modeling and synchronization control Wave dynamics in excitable media (e.g., cardiac arrhythmias) Fractal dimension estimation and reservoir computing Labs/Teams: Leads the Biomedical Physics Group at MPI-DS and contributes to the IMPRS Program in Physics of Biological and Complex Systems.

Christian TetzlaffView profile

Professor

• Computational Neuroscience
• Synaptic Physiology
• Neuromorphic Engineering
• +4 more

Prof. Christian Tetzlaff holds a W2 Professorship at the Department for Neuro- and Sensory Physiology, University Medical Center Göttingen. He leads the Computational Synaptic Physiology group, focusing on integrating computational methods to understand neural systems' principles and translating these into technologies like robotics and neuromorphic engineering. His work spans scales from synaptic protein interactions to large neural networks, leveraging disciplines such as nonlinear dynamics and machine learning. Educational Background: 2009: Diploma in Physics, Georg-August University Göttingen 2013: PhD in Physics (Dr.rer.nat.), Georg-August University Göttingen Research Leadership & Grants: Principal Investigator in EU Horizon 2020 Projects (Plan4Act, ADOPD, Human Brain Project's FIPPA) Lead in DFG-funded SFB 1286 (Quantitative Synaptology) INRC member (Intel Neuromorphic Research Community) BMBF-funded KISSKI project (2022–present) Research Interests: His lab explores synaptic mechanisms underlying learning, memory consolidation via synaptic tagging-and-capture, and neuromorphic hardware implementations. Recent work emphasizes calcium signaling in synapses, memristive devices for synaptic working memory, and robust trajectory generation using neuromorphic chips like Loihi. Affiliations: Co-coordinator of Plan4Act (2017–2021) and active in the Göttingen Graduate Center for Neurosciences (GGNB). Collaborates globally with institutions like the Weizmann Institute and Columbia University. Laboratory: Visit tetzlab.com for lab activities and open-source tools like Plastic Arbor .

Zoltán HarmanView profile

Researcher

• Quantum Electrodynamics
• Atomic Physics
• Highly Charged Ions
• +12 more

Zoltán Harman is a Leading Scientist at the Max Planck Institute for Nuclear Physics (MPIK) in Heidelberg, Germany, and is affiliated with Heidelberg University. He conducts cutting-edge research in atomic physics, quantum electrodynamics, and precision measurements, particularly using highly charged ions and Penning trap techniques. He holds a habilitation in physics from Heidelberg University and regularly lectures there on advanced topics such as quantum electrodynamics and theoretical physics. Research Interests: Quantum Electrodynamics (QED) in strong fields Precision spectroscopy of highly charged ions g-factor measurements and tests of fundamental physics Development of atomic clocks using highly charged ions Determination of fundamental constants (e.g., electron mass, fine-structure constant) Searches for new physics beyond the Standard Model, including fifth forces Neutrino mass determination via Penning trap measurements His recent publications (2024–2025) focus on high-precision g-factor measurements in ions like tin and beryllium, two-loop QED calculations, King plot analyses for new boson searches, and neutrino mass studies. These works appear in top journals such as Nature , Physical Review Letters , and Science , reflecting his leadership in precision atomic physics. Scientific Awards and Grants: Postdoctoral scholarship from the Max Planck Society (2005–2007) EMMI Visiting Professor Scholarship (2012, 2013) Erasmus student scholarship (1999–2000) Primary investigator of the ISOQUANT Collaborative Research Centre (SFB1225) Teaching and Advising: Harman has been a regular lecturer at Heidelberg University since 2008, teaching courses in quantum electrodynamics, theoretical physics, and experimental physics. He co-organizes advanced lecture series and supervises student research projects, including poster sessions and talks. He is also a lecturer in the International Max Planck Research School on Quantum Dynamics. Research Group and Collaborations: Harman is a key member of the quantum dynamics group at MPIK, led by Prof. Christoph H. Keitel. His work involves close collaboration with experimental teams at MPIK, GSI, and Heidelberg University, combining theoretical and experimental efforts in precision physics. He is actively involved in major projects such as PENTATRAP and ALPHATRAP, which aim to push the limits of atomic and nuclear measurements.