Find Academic Supervisors

Julie DethierView profile

Research Fellow

• Computational Neuroscience
• Neural Oscillations
• Brain-Machine Interfaces
• +2 more

Julie Dethier is a Research Fellow at the University of Liège, affiliated with the Faculty of Applied Sciences and Montefiore Institute. Her research bridges cellular neuroscience and network dynamics, with focus on pathological rhythms in Parkinson's disease and brain-machine interface development. She completed her Ph.D. in 2015 under Prof. Sepulchre's supervision. Her academic journey includes: Ph.D. in Systems and Modeling (2015), University of Liège with Princeton University research stay (2014-2015) Master of Science in Bioengineering (2011), Stanford University (Brains in Silicon lab) Master of Applied Sciences in Biomedical Engineering (2010, summa cum laude), University of Liège Bachelor of Applied Sciences (2008, summa cum laude), University of Liège Dr. Dethier investigates how cellular feedback mechanisms generate pathological beta oscillations in basal ganglia circuits, disrupting motor function in Parkinson's disease. Her computational approaches model the transition from unicellular rhythms to network-level oscillations, with implications for deep-brain stimulation therapies. She integrates electrophysiological data with dynamical systems theory to explain robustness and modulation in neural circuits. Her publication record demonstrates evolving expertise from brain-machine interface hardware (2011-2012) to fundamental neural mechanism studies (2013-2015). Key themes include spiking neural network decoders, cellular feedback loops, and pathological oscillation generation. Work spans computational modeling, neuromorphic engineering, and translational neuroscience with applications in neuroprosthetics. Major recognitions include: WBI excellence grant for Princeton research (2014) LEAR Foundation Fellowship for Cambridge research (2013) Audience Award at ULg thesis competition (2013) IEEE EMBS Best Poster Award (2011) Fulbright Honorary Fellowship and Rotary International Fellowship (2010) Funded by competitive F.R.S.-FNRS and international fellowships, her research involved cross-institutional collaboration with Princeton, Cambridge, and Stanford teams. While no formal advisees are listed, her publications reflect mentorship through co-supervised projects and conference presentations. Current work extends her doctoral thesis on multiscale neural dynamics. She maintains active ties with the Systems and Modeling Research Unit at Liège, Brains in Silicon lab at Stanford, and participates in Benelux neuroscience networks through the Montefiore Institute.

• Conceptual Modeling
• Business Process Management
• Digital Transformation
• +5 more

Yves Wautelet serves as an Associate Professor at the Faculty of Economics and Business at KU Leuven, where he conducts research in conceptual modeling, business process management, and digital transformation. His work addresses critical challenges at the intersection of information systems engineering and business strategy, with particular focus on sustainability-driven modeling approaches and IT governance frameworks. His primary research interests include: Conceptual modeling methodologies and frameworks Business process management and information systems design Digital transformation strategies and implementation IT governance and business-IT alignment Sustainability-driven modeling for circular economy Agile software development practices and methods Requirements engineering with user stories Wautelet's recent publication record demonstrates significant scholarly productivity with numerous 2024-2025 publications spanning conceptual modeling frameworks for sustainability (Circulise), tools for identifying ambiguity in user stories (AmbiTRUS), and approaches to align strategic and operational agility. His work bridges theoretical foundations with practical applications across diverse domains including healthcare, circular economy, software development, and organizational transformation. His research consistently applies model-driven approaches to solve complex real-world problems, often integrating sustainability considerations into information systems engineering. As a promotor and co-promotor, Wautelet currently supervises multiple doctoral research projects including: Automatic generation of conceptual models from textual descriptions (2024-2028) Sustainability-Driven Modeling Assistant for Twin Transition in Vietnam (2024-2028) Home Care Business Process Management using Distributed Ledger Technologies (2024-2028) Teaching Modeling Skills in BPMN formalism (2021-2025) His research is conducted through the Information Systems Engineering Research Group (LIRIS) at KU Leuven's Brussels campus, where he contributes to advancing model-driven approaches for addressing contemporary business and technological challenges.

Kerry TaylorView profile

Associate Professor

• Ontologies
• Semantic Web
• Linked Data
• +5 more

Kerry Taylor is an Associate Professor (Data Science) at the School of Computing, Australian National University (ANU). She holds visiting roles at the University of Surrey (UK) and University of Melbourne. Her career spans 20 years at CSIRO, UN big data projects with ABS, and interdisciplinary research in data management, IoT, and semantic technologies. She lectures in data mining and convenes ANU's postgraduate applied data analytics programs. Education includes a BSc (Hons 1) in Computer Science from UNSW (1983) and a PhD in Computer Science and Technology from ANU (1996). She co-chaired the W3C/OGC Spatial Data on the Web working group (2015-2017) and serves on editorial boards for Knowledge-Based Systems and International Journal of Distributed Sensor Networks . Research focuses on ontologies, semantic web, machine learning in IoT, and spatial data systems. Active projects include government information frameworks, distributed IoT facilities, and sensor data integration. Her work emphasizes interdisciplinary applications of logic-based and semantic approaches to data challenges.

Sharon C. GlotzerView profile

Professor

• Computational Assembly Science
• Materials Design
• Colloids
• +3 more

Sharon C. Glotzer is the Anthony C. Lembke Department Chair of Chemical Engineering and the John Werner Cahn Distinguished University Professor of Engineering at the University of Michigan. She holds dual professorships in Materials Science & Engineering and Macromolecular Science & Engineering, alongside Physics and Applied Physics. Her research focuses on computational assembly science, predictive materials design of colloids, and soft matter, leveraging entropy-driven self-assembly principles. Glotzer leads a large interdisciplinary group of ~30 researchers, producing over 300 peer-reviewed papers and contributing to federal agency roadmaps in materials research. Education: B.S. and Ph.D. in Physics from UCLA and Boston University. Leadership: Directed the NIST Center for Theoretical and Computational Materials Science (1993–2001). Her work introduced 'patchy particles' and the 'shape space diagram,' revolutionizing nanoparticle design and colloidal self-assembly. Notable contributions include entropy-mediated assembly, quasicrystal engineering, and computational tools like HOOMD-blue and freud. Awards include National Academy memberships, APS Fellowships, and the Aneesur Rahman Prize. Her lab integrates simulation, theory, and AI to design programmable materials, with applications in nanotechnology, photonics, and biomaterials.

• Applied Probability
• Polymer Physics
• Biophysical Systems
• +4 more

Juan Alvarez is a Teaching Assistant Professor at the Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign (UIUC), where he has held roles since 2013. He also served as a Visiting Lecturer at institutions like Zhejiang University and Ho Chi Minh City University of Technology. His academic journey includes postdoctoral fellowships at York University (Canada), University of Toronto, and University of Saskatchewan, alongside sessional lecturing roles in Canada. **Education**: Ph.D., M.S., and B.Sc. in Electrical Engineering from UIUC and ITESM-CCM, respectively. **Research Interests**: Focus on applied probability, polymer physics (e.g., self-avoiding walks, copolymer localization), biophysical systems, and engineering education. He explores student success strategies, metacognition, and pedagogical approaches to improve learning outcomes. **Recent Publications**: Over 15 articles in journals like Journal of Statistical Mechanics and conferences like ASEE, covering topics from polymer models to student learning profiles. Recent work emphasizes undergraduate education innovations. **Teaching**: Courses include ECE 210 (Analog Signal Processing), ECE 313 (Probability), and ECE 398MA (Modern Communications with Python).

• Numerical Analysis
• Computational Electromagnetism
• Finite Element Methods
• +3 more

Ana Maria Alonso Rodriguez is a Full Professor of Numerical Analysis at the Department of Mathematics, University of Trento. She holds a PhD in Applied Mathematics from Universidad Complutense de Madrid (1993) and has held academic positions across Italy and Spain since 1990. Her research focuses on numerical methods for partial differential equations, computational electromagnetism, finite element methods, and domain decomposition techniques. She has organized international workshops and minisymposia, including the 2022 Oberwolfach workshop on Hilbert Complexes and the 2018 ICOSAHOM conference session on high-order methods. Her work bridges numerical analysis, topology, and applied electromagnetism, with recent contributions to Whitney finite elements and discrete potential theory. Education: PhD in Applied Mathematics, Universidad Complutense de Madrid (1988-1993) Licenciatura en Ciencias Matematicas, same institution (1982-1987) Research emphasizes high-order discretizations for electromagnetic problems, leveraging finite element exterior calculus and graph-based decomposition techniques. Recent work (2024) advances tree-cotree methods for curl operator spectra and Whitney form interpolation. She actively collaborates with international institutions like the CI2MA in Chile and the Laboratoire J. A. Dieudonné in France. Teaching includes courses on numerical PDEs, finite elements, computational electromagnetism, and MATLAB-based numerical analysis at both undergraduate and PhD levels. She has supervised numerous courses in Italy and Spain since 2000, integrating practical software tools like FreeFem and MODULEF into instruction.

Gilbert YeView profile

Assistant Professor

• Human-Robot Interaction
• Automation in Engineering
• AI in Construction
• +3 more

Yang (Gilbert) Ye is an Assistant Professor in the Department of Civil and Environmental Engineering at Northeastern University, joining in January 2025. His research focuses on human-AI/robot teaming, automation in engineering, and assistive technologies, with a particular emphasis on human-centric robotics and sensorimotor processes. He holds a PhD in Civil Engineering from the University of Florida (2024), advised by Dr. Eric Jing Du. **Affiliations**: Member of ASCE, IEEE, and HFES. His work integrates VR/AR, robotics (e.g., drones, exoskeletons), and AI to enhance civil engineering workflows and workforce training. He leads the Ye Lab, actively recruiting PhD students and postdocs with coding experience (Python/C++/C#) and backgrounds in engineering or computer science. **Key Research Themes**: Human-robot interaction, construction automation, exoskeleton training, and delayed feedback mitigation in teleoperation. Over 20 peer-reviewed publications in journals like ASCE JoCEN, IEEE Access, and Advanced Engineering Informatics. **Lab Opportunities**: PhD/postdoc applicants require strong academic records (GPA ≥3.5) and coding skills. Undergrad/master students can apply for thesis/research roles. Funding covers tuition, insurance, and stipends.

David BurtonView profile

Senior Lecturer

• Aerodynamics
• Fluid Mechanics
• Wind Engineering
• +11 more

David Burton is a Senior Lecturer in the Department of Mechanical & Aerospace Engineering at Monash University, Faculty of Engineering. He leads the Monash Wind Tunnel Research Platform (MWTRP), a major research facility supporting experimental and applied aerodynamics research across multiple industries. Research Interests: His expertise lies in experimental fluid dynamics, with a focus on wind engineering, industrial aerodynamics, and aero-acoustics. Key areas include building, vehicle, and sports aerodynamics, flow control, and the impact of wind storms and cyclones. He integrates experimental testing with numerical simulation, particularly in complex bluff body flows and sustainable engineering design. The recent publication trends reflect a strong emphasis on postcritical flow over rough and multiple cylinders, aerodynamic modeling in sports (especially cycling), and real-world applications such as freight train aerodynamics and cyclone resilience. His work combines rigorous experimentation with practical engineering solutions. Scientific Awards: No specific awards mentioned in the provided text. Advising and Grants: David Burton is accepting PhD students and actively supervises research projects. He has served as Primary Chief Investigator on significant research grants, including 'Wind and Water Loading of Flags in Cyclones' (2021–2022) and 'Wind Comfort Simulation and New Engineering Design Process' (2022–2023), demonstrating sustained external funding and project leadership. Labs and Teams: He manages the Monash Wind Tunnel Research Platform (MWTRP), an ISO9001-accredited facility featuring the largest wind tunnel of its type in the Southern Hemisphere. The platform includes CNC machining, rapid prototyping, and a multidisciplinary team of postgraduate students, designers, technical officers, and postdoctoral researchers, supporting collaborations across automotive, defense, construction, UAVs, wind energy, and sports sectors.

• Brain-Computer Interfaces
• Machine Learning
• Neural Signal Processing
• +5 more

Professor Guan Cuntai serves as Deputy Dean of the College of Computing & Data Science and holds the President's Chair in Computer Science and Engineering at Nanyang Technological University (NTU), Singapore. He also maintains a courtesy appointment as Professor at the Lee Kong Chian School of Medicine. His leadership extends to multiple research institutes including serving as Director of the Artificial Intelligence Research Institute (AI.R) and Co-Director of both S-Lab for Advanced Intelligence (2020-2025) and the Rehabilitation Research Institute of Singapore (2015-2018 & 2024-2025). Professor Guan's research focuses on Brain-Computer Interfaces (BCI), Machine Learning, Neural Signal & Image Processing, and Artificial Intelligence. His work at the Centre for Brain-Computing Research (CBCR) investigates deep learning algorithms for motor activity decoding, cognitive mechanism understanding, and explainable AI for brain decoding modeling. His research spans applications in motor decoding, attention and emotion detection, silent speech decoding, and olfactory response analysis from brain signals. His significant contributions to the field have been recognized through numerous awards: Annual BCI Research Award (First Prize) King Salman Award for Disability Research Nanyang Research Award IES Prestigious Engineering Achievement Award Achiever of the Year (Research) Award Finalist of the President Technology Award Professor Guan has delivered over 100 keynote speeches and invited talks globally, including at the opening ceremony of the 7th International BCI Meeting and IEEE International Conference on Rehabilitation Robotics. His extensive publication record includes 420 refereed journal and conference papers, and he has secured significant research funding resulting in 26 granted patents and patent applications, with 17 technologies licensed to six companies across Singapore and USA. He leads the Centre for Brain-Computing Research (CBCR) which focuses on fundamental and applied BCI research, and previously established the Brain-Computer Interface research program and founded the Department of Neural & Biomedical Technology at the Institute for Infocomm Research, A*STAR before joining NTU in 2016.

• Computational Fluid Dynamics
• Internal Combustion Engines
• Cavitation
• +13 more

Professor Manolis Gavaises is a leading academic in the field of mechanical engineering and computational fluid dynamics at City St George's, University of London, where he holds the position of Professor in the School of Engineering and Mathematical Sciences. He earned his PhD from Imperial College London and has been a faculty member since 2001, progressing to full Professor in 2009. His research is centered on advanced modeling of multi-phase flows, cavitation, and fuel injection systems, with extensive collaborations across Europe and industry partners such as Delphi, Caterpillar, and BP. Education: DIC, Mechanical Engineering, Computational Fluid Dynamics, Imperial College London, 1997 PhD, Mechanical Engineering, Computational Fluid Dynamics, Imperial College London, 1997 Diploma (5 years), Mechanical Engineering, National Technical University of Athens, 1992 His research interests span computational fluid dynamics, cavitation, fuel injection, atomization, high-pressure and supercritical flows, and alternative fuels . He has developed advanced numerical models and experimental techniques, including X-ray phase contrast imaging and high-pressure test rigs. His work integrates fundamental DNS and LES simulations with industrial applications in automotive, marine, aerospace, and medical devices such as heart valves. The recent publications reflect a strong trend toward real-fluid thermodynamic modeling (e.g., PC-SAFT), multi-component fuel behavior, cavitation erosion, and advanced diagnostics . His research increasingly incorporates machine learning and high-fidelity imaging to understand complex flow phenomena across energy, transportation, and biomedical domains. Scientific Awards and Recognitions: Richard Way Prize (1998) Arch T. Collwell Merit Award (1998) Best Oral Paper, SAE World Congress (2006) PE Publication Award, IMechE (2007) Best Presentation Award, Engine Combustion Processes (2009) Fellow, IMechE (2013) Fellow, IMA (2015) As a dedicated mentor, Professor Gavaises has supervised 13 PhDs to completion and currently guides 23 doctoral students. He has secured over €16 million in EU and UK funding, including multiple Horizon 2020 Marie Skłodowska-Curie ITN projects (CAFÉ, HAOS, IPPAD), which support 46 early-career researchers globally. He has created academic opportunities for post-docs and junior faculty, significantly advancing the research profile of his institution. He leads the International Institute of Cavitation Research (IICR), co-founded in 2011 with partners from Loughborough University, TU Delft, and Imperial College, supported by The Lloyd’s Register Foundation. His lab maintains strong experimental capabilities, including a 2000bar pressure flow rig with micro-transparent nozzles and collaborations with Argonne National Laboratory for X-ray imaging.

Aaron RothView profile

Professor

• Algorithms
• Machine Learning
• Differential Privacy
• +10 more

Aaron Roth is the Henry Salvatori Professor of Computer and Cognitive Science at the University of Pennsylvania, affiliated with the Department of Computer and Information Science in the School of Engineering and Applied Science. He holds a secondary appointment in the Department of Statistics and Data Science at the Wharton School and is associated with several research centers including PRiML, the Warren Center for Network and Data Sciences, and the AMCS program. He received his PhD from Carnegie Mellon University under Avrim Blum and was a postdoc at Microsoft Research New England. His research focuses on algorithms and machine learning, particularly in private data analysis, fairness in machine learning, game theory, mechanism design, and learning theory. His work bridges theoretical computer science with societal concerns, advocating for ethically aware algorithm design. He co-authored the book The Ethical Algorithm with Michael Kearns, which explores how to embed social values like privacy and fairness into algorithmic systems. His recent publications show a strong trend toward uncertainty quantification, multicalibration, conformal prediction, and fairness in reinforcement learning and high-dimensional settings. He frequently publishes in top-tier venues such as STOC, FOCS, ICML, NeurIPS, and COLT, often with a focus on rigorous theoretical foundations with practical implications. Hans Sigrist Prize Presidential Early Career Award for Scientists and Engineers (PECASE) Alfred P. Sloan Research Fellowship NSF CAREER award Google Faculty Research Award Amazon Research Award Yahoo Academic Career Enhancement award Roth has advised numerous PhD students and postdocs, many of whom now hold academic or industry research positions. He is also an Amazon Scholar at AWS and has served in advisory roles for companies like Apple, Facebook, Leapyear, and Spectrum Labs. He has been active in organizing workshops and tutorials on differential privacy, fairness, and adaptive data analysis, and has given keynotes at major conferences and institutions worldwide. He leads research groups and collaborates widely across Penn, focusing on responsible AI, privacy, and algorithmic fairness. His lab produces foundational work on calibration, unlearning, privacy-preserving learning, and equitable decision-making systems.

Kyle McCallView profile

Assistant Professor

• Materials Science and Engineering
• Inorganic Chemistry
• Physics
• +13 more

Kyle McCall is an Assistant Professor in the Department of Materials Science and Engineering at the University of Texas at Dallas, within the Erik Jonsson School of Engineering and Computer Science. He holds a PhD in Applied Physics from Northwestern University (2019) and a B.S. in Physics and Mathematics from the University of Notre Dame (2014). He served as a Postdoctoral Research Fellow at ETH Zurich, Switzerland, from 2019 to 2021. Research Interests: Dr. McCall's research lies at the intersection of materials science, chemistry, and physics, focusing on the synthesis and characterization of complex semiconductors for energy and radiation detection applications. His group employs a materials-by-design approach to develop novel functional optoelectronic materials, particularly halide perovskites and related compounds. Key areas include crystal growth (via Bridgman method), X-ray crystallography, and the development of materials for solar cells, light-emitting devices, X-ray photodetectors, and neutron/gamma-ray scintillators. Publication Trends: His recent publications (all from 2021) highlight a strong focus on halide perovskite materials for radiation detection and optoelectronics. Themes include room-temperature gamma-ray detection, neutron imaging using luminescent materials, structural instabilities in perovskites, and optical behavior tuning via cation engineering. The work combines fundamental structure-property studies with device-relevant performance metrics. Scientific Awards and Memberships: Member, American Chemical Society (ACS) Member, Materials Research Society (MRS) Advising and Grants: As a tenure-track faculty member, Dr. McCall leads the McCall Research Group at UT Dallas, mentoring students in interdisciplinary materials research. He was part of the 2021 cohort of new tenured/tenure-track faculty at UT Dallas. While specific grants are not listed, his research program is clearly supported by institutional funding and infrastructure, including crystal growth and characterization facilities. Laboratories and Teams: He founded the crystal growth component of the ETH+ SynMatLab facility during his postdoc at ETH Zurich. At UT Dallas, he leads his own research group focused on materials chemistry and functional device integration, continuing his work on single crystal growth and optoelectronic characterization.

• Environmental and Power Reactor Health Physics
• Radiation Detection
• Nuclear Security
• +1 more

Jason Harris is a Professor in Health Sciences Education at Purdue University with a courtesy appointment in the College of Engineering, Department of Nuclear Engineering. He serves as a key researcher at the Center for Radiological and Nuclear Security (CRANS) and maintains active leadership roles in major nuclear professional organizations. His academic credentials include: Ph.D. in Health Physics from Purdue University (2007) M.S. in Nuclear Engineering from the University of Illinois at Urbana-Champaign (2002) B.S. in Biology and Chemistry from the University of Tampa (1995) Dr. Harris's research centers on Environmental and Power Reactor Health Physics , Radiation Detection , Nuclear Security , and Nuclear Science Education and Training . His work pioneers methodologies for integrating nuclear safety and security frameworks, developing quantitative risk assessment tools that address terrorism scenarios while maintaining operational safety standards in nuclear facilities. Analysis of his 2020-2024 publications reveals a dominant focus on nuclear security risk quantification, with 80% of works developing facility risk indices and safety-security integration tools. His research consistently applies advanced computational methods including Monte Carlo simulations, game theory, and analytical hierarchy processes to model adversarial behavior and optimize defense strategies against radiological threats. Professional leadership includes: ABET Program Evaluator for Health Physics Chair of Health Physics Program Directors Organization (HPPDO) Chair of Academic Education Committee (Health Physics Society) Member-at-Large, Executive Committee (Institute of Nuclear Materials Management) Former Chair, International Nuclear Security Education Network (IAEA) At CRANS, Dr. Harris directs research on practical security assessment tools, including graphical user interface implementations for risk index calculation and terrorism scenario modeling. His work bridges theoretical security frameworks with operational implementation in nuclear facilities worldwide.

Vadim BackmanView profile

Professor

• Physical Genomics
• Chromatin Engineering
• Nanotechnology
• +5 more

Dr. Vadim Backman is the Sachs Family Professor of Biomedical Engineering and Medicine at Northwestern University's McCormick School of Engineering and Applied Sciences and Feinberg School of Medicine. He holds additional roles as Professor of Medicine (Hematology/Oncology) and Biochemistry and Molecular Genetics, Associate Director of Research Technology and Infrastructure at the Robert H. Lurie Comprehensive Cancer Center, and Director of the Center for Physical Genomics and Engineering. He earned his Ph.D. in Medical Engineering from Harvard-MIT and M.S./B.S. in Physics from St. Petersburg Polytechnic Institute. His research focuses on physical and biological science intersections, developing nanoscale imaging and computational technologies to study chromatin dynamics and their role in disease. Key areas include cancer diagnostics/therapeutics, chromatin engineering, and genome nanoimaging. Dr. Backman has published over 230 papers, holds 20+ patents, and leads large-scale projects like NCI Bioengineering Research Partnerships. Education: Ph.D. (Harvard-MIT), M.S. (MIT), M.S./B.S. (St. Petersburg Polytechnic Institute) Affiliations: PhD Programs in Applied Physics and Interdisciplinary Biological Sciences Research emphasizes chromatin's role in disease, with clinical translation for diagnostics and therapy. His lab develops technologies like nano-CHIA and ChromSTEM, advancing understanding of genomic organization and epigenetic regulation. Awards include the Cozzarelli Prize and MIT Technology Review's Top 100 Innovators. Awards: Cozzarelli Prize (2017), AIMBE Fellowship (2009), NSF CAREER Award (2003) Grants and collaborations include managing multi-investigator projects and co-founding biotech companies. Courses taught: BME 302 (Quantitative Systems Physiology), BME 429 (Advanced Physical and Applied Optics).

Lindsay TurnbullView profile

Professor

• Plant Ecology
• Biodiversity
• Ecology
• +3 more

Professor Lindsay Turnbull is a Professor of Plant Ecology at the University of Oxford's Department of Biology. Her research focuses on understanding the evolutionary and ecological basis of plant trait diversity and its consequences for ecosystems. Key interests include seed size variation, plant-soil interactions, and the impact of organic farming on biodiversity. She leads a research group exploring topics such as mutualism stability, species coexistence, and island conservation genetics. Turnbull's work integrates experimental, observational, and computational approaches to address fundamental questions in ecology. Her lab, based at the Department of Biology (Mansfield Road and South Parks Road campuses), has contributed to global understanding of biodiversity-ecosystem functioning relationships and plant-microbe symbioses. Notable projects include studies on Aldabra giant tortoises and coral reef connectivity in the Seychelles, highlighting her commitment to applied conservation science. Her research spans multiple scales—from molecular interactions in legume-rhizobia systems to large-scale biodiversity patterns in grasslands and tropical ecosystems. Recent work emphasizes the role of trait-based approaches in predicting ecological responses to environmental changes such as eutrophication and climate variability. Her publications frequently bridge theoretical and applied ecology, offering insights into both natural and human-managed ecosystems.