Dr. Marion Schrumpf is a Group Leader in the Soil Biogeochemistry research group at the Max Planck Institute for Biogeochemistry, affiliated with the Department of Biogeochemical Processes. Her work focuses on soil carbon dynamics, mineral-organic matter interactions, and climate change impacts on soil systems. Research areas: Soil biogeochemistry, carbon cycling, mineral-soil interactions, nutrient stoichiometry, microbial ecology, and climate modeling. Email: mschrumpf@... Phone: +49 3641 57-6182 Office: B2.015 Her recent publications address themes like mineral control over soil carbon stabilization, drought effects on soil processes, microbial stoichiometric adaptation, and the Jena Soil Model's role in simulating carbon-nutrient interactions. She leads efforts to disentangle the complex relationships between land use, mineralogy, and soil organic matter turnover across diverse ecosystems.
Rainald Loehner is a Distinguished Professor of Fluid Dynamics at George Mason University's Center for Computational Fluid Dynamics. Since 2003, he has led the Center for Computational Fluid Dynamics at George Mason University. He is currently a Hans Fischer Senior Fellow at the Technical University of Munich's Institute for Advanced Study (TUM-IAS) for 2023, hosted by Professors Kai-Uwe Bletzinger and Roland Wüchner in the 'Adjoint-Based System Identification of Large-Scale Structures' Focus Group. Loehner received his Diplom Ingenieur (Maschinenbau) degree from the Technical University of Braunschweig, and his PhD and a DSc in civil engineering from the University College of Swansea, Wales. After teaching at Swansea for a year, he worked at the Naval Research Laboratory in Washington, DC, followed by a research professorship at George Washington University. He joined George Mason University as an associate professor and was promoted to full professor in 1995 and distinguished professor in 2004. With over 35 years of experience, Professor Loehner's research spans the complete pipeline of numerical solvers and simulation tools. His expertise includes pre-processing, grid generation, numerical methods, field solvers, parallel computing, adaptive mesh refinement, fluid-structure interaction, shape optimization, system identification, and computational crowd dynamics. His current work focuses on developing advanced field solvers for compressible and incompressible flows, acoustics, electromagnetic wave propagation, heat and mass transfer, structural mechanics, and fluid-structure interaction. Key application areas include blast mitigation, ship hydrodynamics, blood flow, contaminant transport, and pedestrian safety. Loehner's recent research output (2020-2024) shows a strong trend toward digital twin technology and adjoint-based methods for structural analysis and optimization. His publications focus on high-fidelity digital twins for detecting structural weaknesses, risk assessment in engineering systems, and optimization of sensor placement. His work bridges computational mechanics with machine learning approaches, particularly in system identification and inverse problems, demonstrating how computational methods can solve complex real-world engineering challenges. 2020: Ranked #15119 in the Stanford List of Most Influential Scientists of the World; #8 in Aerospace and Aeronautics 2010: Distinguished International Career Award, Argentine Association of Computational Mechanics 2008: Fellow, International Association for Computational Mechanics 2006: Associate Fellow, AIAA 2005: Honorary Professor, University of Wales Swansea 2005: Advisory Professor, Shanghai Jiao Tong University 2004: Distinguished Professor of Fluid Dynamics, George Mason University 1999: Computational Mechanics Achievements Award, Japan Society of Mechanical Engineering 1993: Doctor of Science in Civil Engineering, University College of Swansea 1979-1983: Studienstiftung des Deutschen Volkes (Top 1% of German Students) Professor Loehner has mentored numerous students through his work at George Mason University and has supervised research in computational fluid dynamics, structural mechanics, and related fields. His research has been supported by various grants from government agencies and industry partners, enabling the development of advanced simulation tools applied in aerodynamics, hydrodynamics, shock-structure interaction, and medical applications. His codes and methods have been widely adopted in industry and academia for applications ranging from aircraft and ship design to medical simulations and urban pathogen transmission modeling. Loehner leads the Center for Computational Fluid Dynamics at George Mason University, which focuses on developing cutting-edge computational methods for fluid dynamics and related multiphysics problems. The center works on strategic application areas including blast mitigation, ship hydrodynamics, blood flow simulation, and pedestrian movement modeling. As a TUM-IAS Fellow, he collaborates with the Chair of Computational Modeling and Simulation at TUM on adjoint-based system identification of large-scale structures, bringing together expertise in computational mechanics and digital twin technology to address complex engineering challenges.
Dr Dee Wu serves as a Senior Lecturer at the School of Civil and Environmental Engineering at the University of Technology Sydney (UTS), specializing in the integration of computational mechanics, machine learning, and engineering design. With a strong research profile focused on structural reliability and safety assessment, Dr Wu develops innovative frameworks that bridge theoretical mechanics with practical engineering applications, particularly in the realm of composite materials and uncertain structural behavior. Dr Wu's research interests center on computational stochastic and non-stochastic mechanics, with particular emphasis on machine-learning-aided engineering safety assessment, nondeterministic methods for isogeometric analysis with polymorphic uncertainties, and AI techniques for composite material design. Their work addresses critical challenges in structural engineering where uncertainty quantification becomes essential for safety evaluation. The research output reveals a clear trajectory toward developing virtual modeling techniques that significantly enhance computational efficiency while maintaining accuracy in structural analysis. Dr Wu's publications demonstrate expertise in phase-field methods, support vector regression variants (including Extended SVR, Capped SVR, and Twin SVR), and uncertainty quantification frameworks that handle both aleatoric and epistemic uncertainties. These techniques have been successfully applied to fracture mechanics, buckling analysis, vibration analysis, and impact assessment problems. Dr Wu actively pursues funded research in three main areas: Digital twin applications in Civil Engineering, Machine learning aided engineering analysis and design, and Safety assessment for Smart City initiatives. Currently, they are a key participant in the ARC Discovery Project 'Assessment of Dynamic Pile Driving Using Machine Learning' (DP230102781), running from June 2023 to May 2026, working alongside researchers Khabbaz M, Fatahi B, and Zhang X. In teaching, Dr Wu delivers courses including Introduction to Civil and Environmental Engineering (48310), Advanced Engineering Computing (48371), and Finite Element Analysis (49047), demonstrating commitment to both foundational and advanced engineering education. Their ORCID identifier is 0000-0002-7284-5024, and they maintain an active Google Scholar profile reflecting their substantial research contributions in computational structural engineering.
Damiano Piovesan is Associate Professor in Bioinformatics (SSD BIO/10) at the Department of Biomedical Sciences , University of Padua , Italy. Since March 2022 he has held this rank, having previously served as Assistant Professor (2022) and PostDoc researcher (2019) in the same department. Education 2013 – PhD in Biotechnology, Pharmacology and Toxicology, University of Bologna 2009 – MSc in Bioinformatics, University of Bologna 2007 – BSc in Biotechnology, University of Bologna Research Focus Piovesan’s research integrates machine-learning approaches with structural bioinformatics to advance understanding of intrinsically disordered proteins (IDPs) and protein function prediction . He develops widely used resources such as MobiDB for disorder annotation, DisProt for functional curation of disordered regions, and RING for residue interaction networks. Additional interests include tandem repeat proteins , cancer-related IDP targets , and community benchmarking initiatives (CAFA, CAID, CAGI). Publication Trends His 2024–2025 output is dominated by updates to flagship databases ( InterPro , DisProt , MobiDB ), next-generation disorder predictors leveraging deep learning ( PredIDR , MobiDB-lite 4.0 ), and large-scale genomics challenges ( CAGI6 ). Across the decade, recurring themes include methodological advances in disorder prediction, creation of interoperable bioinformatics platforms, and rigorous benchmarking to ensure community-wide reliability. Scientific Awards No specific awards are listed in the provided materials. Advising & Grants No individual students or grant details are explicitly supplied; however, his leadership in multi-institutional consortia (e.g., InterPro, DisProt, CAFA) implies substantial supervisory and funding coordination roles. Labs & Teams Piovesan is affiliated with the BioComputingUP Lab ( https://biocomputingup.it/ ) at the University of Padua, a hub for computational biology and bioinformatics tool development.
Jes Frellsen is an Associate Professor at the Department of Applied Mathematics and Computer Science (DTU) since 2016. Previously, he held academic positions at the IT University of Copenhagen (2016-2019), postdoctoral roles at University of Cambridge (2013-2016) and University of Copenhagen (2011-2013). Education: PhD in Bioinformatics (2011), University of Copenhagen MSc in Bioinformatics (2007), University of Copenhagen BSc in Mathematics and Computer Science (2005), University of Copenhagen EAP Exchange at University of California, Santa Cruz (2004-2005) Research Focus Jes Frellsen specializes in statistical machine learning , particularly generative AI and deep generative models with applications in bioinformatics . His work integrates Bayesian inference , directional statistics , and Markov chain Monte Carlo methods to address challenges in macromolecular structure prediction and missing data imputation . Recent efforts explore uncertainty quantification in image segmentation and generative modeling for materials science. Advising & Collaborations He actively supervises PhD students and postdoctoral researchers in projects spanning news recommendation systems , medical imaging , and 3D structure generation . Collaborations include work with Zoubin Ghahramani (Cambridge) and Thomas Hamelryck (Copenhagen), with contributions to protein structure prediction and statistical methods in structural bioinformatics .
Dr. Lucie Lu is a Senior Lecturer in the Department of Finance at the University of Melbourne, affiliated with the Faculty of Business and Economics. She joined the institution in 2023 and specializes in asset pricing, credit risk, international finance, and sustainable finance. Her research examines investor behavior in global markets, risk transmission mechanisms, and sustainable investment strategies. Dr. Lu holds a Ph.D. in Finance from McGill University, an MSc in Finance and Economics from the London School of Economics and Political Science, and a BA in Economics from Fudan University. Her work investigates topics such as heterogeneous investors' roles in risk-sharing, default risk propagation in credit markets, and institutional investors' preferences for sustainable investments. Her recent publications explore cross-market risk transmission, institutional investment dynamics, and structural credit modeling. While no specific awards are listed, her contributions to finance theory and empirical analysis are evident in her scholarly output. Dr. Lu does not currently list advisees or grants in the provided information. Her research extends to interdisciplinary areas, combining quantitative finance with global economic trends, reflecting her expertise in both theoretical and applied financial frameworks.
Thomas S. Gruca serves as the George Daly Professor in Marketing and Director of the Iowa Electronic Markets at the University of Iowa's Tippie College of Business. His interdisciplinary work bridges marketing, finance, and healthcare through innovative prediction market applications. Education PhD in Decision and Information Sciences, University of Illinois Urbana-Champaign MBA in Management Information Systems, University of Illinois Urbana-Champaign BS in Mathematics and Computer Science, University of Illinois-Chicago His research centers on prediction markets for political and healthcare forecasting, with recent work analyzing geopolitical biases , anti-incumbency effects , and rural healthcare access disparities . This intersects with his expertise in marketing/finance interface phenomena like brand equity measurement and consumer behavior modeling in casino gaming. Analysis of his 15 most recent publications reveals three dominant research streams: (1) Election forecasting through Iowa Electronic Markets (35% of output), (2) Rural healthcare access modeling (27%), and (3) Marketing analytics including brand equity and consumer behavior (38%). His work consistently appears in top journals like Journal of Marketing , International Journal of Forecasting , and PS: Political Science & Politics . Scientific Awards 9-time recipient of MBA Marketing Professor of the Year (2006-2019) President & Provost Award for Teaching Excellence (2018) Iowa MBA Instructor of the Year - Core (2014) Gruca has secured significant external funding including an NSF grant ($300,000) for Active Learning in Undergraduate Education Using Iowa Electronic Markets (2000-2003) and a US Department of Education grant for Enhancing Economic Literacy (1997-2000). His leadership roles include Faculty Director of the MBA Marketing Career Academy (2008-2019) and PhD Program Director for Marketing (2008-2014). He directs the Iowa Electronic Markets (IEM), a real-money prediction market used globally for election and economic forecasting research, which serves as both a research platform and teaching tool for over 10,000 students annually.
Professor Jae Kyung Woo is a distinguished academic in the School of Risk and Actuarial Studies at the UNSW Business School, University of New South Wales. She holds multiple prestigious professional designations including Fellow of the Institute of Actuaries of Australia (FIAA), Fellow of the Society of Actuaries (FSA), and Chartered Enterprise Risk Analyst (CERA). Her educational background includes MMath and Ph.D. degrees from the Department of Statistics and Actuarial Science at the University of Waterloo. She has held academic positions at Columbia University as Assistant Professor in the Department of Statistics (2011-2012), and at the University of Hong Kong as Assistant Professor in the Department of Statistics and Actuarial Science (2012-2017) before joining UNSW in July 2017. Research interests focus on risk theory, reliability theory, aggregate claim analysis, queueing theory, and dependence modelling Editorial Board member for ASTIN Bulletin (2021-present), European Actuarial Journal (2025-present), Probability in the Engineering and Information Sciences (2018-present), and Risks (2020-present) Principal investigator for ARC Discovery Projects (2020-2023) and Casualty Actuarial Society grants (2018-2020) Her research output includes 35 journal articles, 1 book, 1 thesis/dissertation, and 1 other publication, with recent work emphasizing shock models for correlated large losses, credibility theory under dependency structures, and advanced dependence modeling techniques in insurance contexts. Her work bridges theoretical stochastic analysis with practical applications in insurance and risk management. Fellow of the Institute of Actuaries of Australia (FIAA), since May 2018 Fellow of the Society of Actuaries (FSA), since Oct 2013 Chartered Enterprise Risk Analyst (CERA), since Jan 2012 Fellow Member of Actuarial Society of Hong Kong (ASHK), since Dec 2018 Professor Woo has secured significant research funding including an ARC Discovery Project grant of AUD 334,000 (2020-2023) for developing shock model-based frameworks for correlated large losses, and a Casualty Actuarial Society grant of USD 20,000 (2018-2020) for credibility theory research under general dependency structures. She served as Nominated Accreditation Actuary at UNSW until 2024.
Bassam Bamieh is a Professor of Mechanical Engineering at the University of California, Santa Barbara (UCSB), with affiliate roles in Electrical and Computer Engineering and the Center for Control, Dynamical Systems and Computation (CCDC). His research focuses on control systems, dynamical systems, and their applications in fluid mechanics, quantum control, and network science. He holds fellowships from IEEE and IFAC and has received accolades such as the NSF Early Career Award and IEEE Distinguished Lecturer designation. Education: B.Sc. in Electrical Engineering and Physics from Valparaiso University (1983), M.Sc. and Ph.D. in Electrical and Computer Engineering from Rice University (1986, 1992). Formerly an Assistant Professor at the University of Illinois at Urbana-Champaign (1991–98). Research interests span robust and optimal control, distributed systems, shear flow turbulence, and thermoacoustic energy conversion. He has authored over 200 publications and pioneered work in spatially invariant systems and network controllability. His teaching includes courses on linear systems, vibrations, and control systems design. Awards include the IEEE Axelby Award (twice), Hugo Schuck Best Paper Award, and recognition for student research mentorship (e.g., Outstanding Student Paper Awards at CDC and IFAC NecSys22). His group collaborates across disciplines, integrating mathematical analysis with engineering applications.
Kwaku Ohene-Asare is a Lecturer in Business Analytics at De Montfort University, UK, within the School of Leadership, Management and Marketing. He holds a PhD in Operational Research and Management Science from the University of Warwick, an MSc in Economics and Finance (with distinction) from Loughborough University, and a BSc in Economics (first-class honors) from the University of Ghana-Legon. He also completed a certificate in Decision Science and Machine Learning at MIT, USA. He has held visiting professorships at Warwick University and Stellenbosch University and plays a senior lecturer role at the University of Ghana. His educational background includes: PhD in Operational Research and Management Science, University of Warwick, UK (2012) MA in Decision Science and Machine Learning, MIT, USA MSc in Economics and Finance, Loughborough University, UK (Distinction) BSc in Economics, University of Ghana-Legon (First Class) PGCAP (Part 1), University of Warwick, UK (2009) Certificate in Nonparametric & Bootstrap Methods, Sapienza University of Rome, Italy (2012) Kwaku's research interests span business analytics, management science, artificial intelligence, data science, machine learning, economic efficiency, productivity analysis, data envelopment analysis (DEA), stochastic frontier econometrics, and their applications in energy, finance, insurance, and credit unions. He has developed a research-based DEA course at the University of Ghana and pioneered the advanced quantitative research methods course for PhD students since 2015. His work integrates cutting-edge computational techniques and econometric modeling to address real-world economic and business challenges. The recent trend in his publications shows a strong focus on efficiency and productivity analysis across sectors—particularly in energy, banking, and insurance—using advanced non-parametric and parametric methods. He frequently applies DEA, Malmquist indices, and stochastic frontier models to assess performance in African and ECOWAS economies, with a growing emphasis on sustainability, undesirable outputs, and dynamic efficiency. His work bridges theoretical rigor with practical policy implications. His scientific awards include: Global Leadership Award (2021) DFID Shared Scholarship Scheme Award (2004) Doctoral Research Scholarship, Warwick Business School (2007) He has received multiple research grants, primarily from the University of Ghana Business School (UGBS), as Principal Investigator, including projects on data science and machine learning, energy productivity, banking efficiency, and multinational operations. He has supervised PhD students through course development and research mentorship. His consultancy work includes efficiency analysis for the National Petroleum Authority, Ghana, and market entry feasibility studies for international firms. He is affiliated with the Centre for Enterprise and Innovation (CEI), the Institute for Sustainable Economics, and the Institute of Energy and Sustainable Development (IESD) at DMU, where he contributes to interdisciplinary research on sustainable economic development. He is an active member of professional societies including the Operational Research Society (UK), INFORMS, Association of European Operational Research Societies, British Academy of Management, Productivity Analysis Research Network (USA), and the Economic Society of Ghana.
GÜÇLÜ ŞEKERCİOĞLU is an Associate Professor at Akdeniz University, Faculty of Education, Department of Educational Sciences. Currently serving as Director of the Center for Measurement, Evaluation, Certification Research and Application and Director of the Institute of Educational Sciences since 2022, they also hold the position of Vice Dean of the Faculty of Education (2022-2025). Their academic career spans over 15 years at Akdeniz University, progressing from Research Assistant (2010-2011) to Assistant Professor (2011-2019) and currently Associate Professor (2019-present). Academic background includes: Doctorate (2003-2009): Ankara University, Institute of Educational Sciences, Measurement and Evaluation Postgraduate (1998-2001): Ankara University, Institute of Educational Sciences, Measurement and Evaluation Undergraduate (1993-1997): Ankara University, Faculty of Educational Sciences, Psychological Services in Education Dr. Şekercioğlu's research focuses on the intersection of psychometrics, educational measurement, and statistical analysis in educational contexts. Their work demonstrates deep expertise in measurement invariance, differential item functioning, scale development and validation, and advanced statistical methods in education. They have developed specialized knowledge in analyzing international assessments like PISA and TIMSS, with particular attention to cross-cultural measurement equivalence. Their research methodology combines rigorous quantitative approaches with practical applications in educational settings, contributing significantly to the understanding of how psychological constructs can be reliably measured across diverse populations. Analysis of their publication record reveals a strong emphasis on measurement theory and its practical applications in educational contexts. Their work consistently addresses critical issues in cross-cultural assessment, scale adaptation, and the psychometric properties of educational instruments. A notable trend is the application of advanced statistical techniques to solve practical measurement problems in education, particularly focusing on how tests function across different language groups and cultural contexts. They have made significant contributions to understanding measurement invariance in international assessments like PISA, with implications for fair and valid cross-national comparisons. Dr. Şekercioğlu has supervised 8 theses at various levels and serves on numerous doctoral and master's thesis committees. Their research is supported by multiple grants, including several TÜBİTAK projects addressing critical educational issues such as child sexual abuse prevention, nursing education assessment, and language acquisition among immigrant children. They actively contribute to the academic community through peer review activities for journals like Educational Sciences: Theory & Practice and Hacettepe Education Faculty Journal.
Robert J. Trapp serves as Director of the School of Earth, Society, and Environment and Head of Climate, Meteorology and Atmospheric Sciences at the University of Illinois, while also holding a Professorship at the National Center for Supercomputing Applications (NCSA). His leadership spans both academic and research domains within atmospheric sciences. Trapp's research focuses on severe convective storms, tornado dynamics, and radar meteorology with significant contributions to understanding bow echoes, tornadic vortex signatures, and the impacts of climate change on severe weather. His work integrates advanced numerical modeling with observational data from field campaigns like BAMEX and VORTEX, utilizing Doppler radar systems including WSR-88D and Doppler On Wheels (DOW). His publication record demonstrates consistent research output from 1995-2007, with recent work emphasizing telescoping model approaches for evaluating severe convective storms under future climate scenarios. Key methodological contributions include objective analysis techniques for weather radar data and multi-platform observational strategies for severe thunderstorms. Trapp maintains active research collaboration through the National Center for Supercomputing Applications, leveraging computational resources for atmospheric modeling. His work bridges fundamental atmospheric dynamics with practical severe weather forecasting applications. Professional service includes leadership roles as Director and Department Head, indicating significant administrative responsibilities alongside research activities. His scholarly contributions appear primarily in conference proceedings and peer-reviewed journals focused on meteorology and atmospheric science.
Ioannis Tzimas is a Professor at the Department of Electrical and Computer Engineering of the University of Peloponnese. He is a highly active researcher with numerous publications in areas of Service-Oriented Architectures, Web Engineering, Big Data, and Artificial Intelligence applications. University: University of Peloponnese Department: Department of Electrical and Computer Engineering Academic Rank: Professor Email: tzimas@uop.gr Ioannis Tzimas received his education from the Department of Computer Engineering and Informatics of the University of Patras, where he also completed his PhD in Web Engineering. His research spans multiple interdisciplinary domains at the intersection of computer science and practical applications. Service-Oriented Architectures and Information Systems Web Data Engineering and Web Modeling Big Data Management and Data Science Machine Learning and Artificial Intelligence Applications Digital Ecosystems and Digital Transformation for the Public Sector Bioinformatics Professor Tzimas' recent research output demonstrates a strategic focus on applying advanced computational techniques to address contemporary challenges. His work shows particular expertise in labor market analysis using large language models, electricity demand forecasting in Greece, and social protection systems. His publications reveal a pattern of bridging theoretical computer science with practical, real-world applications across multiple sectors. Since 2018, he has served as an international consultant to the World Bank in the field of information systems and digital transformation, working on projects across Europe, Africa, the Caribbean, the Pacific Islands, and China. His earlier career included significant technical leadership roles at the University of Patras and other Greek institutions. Technical Manager of the Graphics, Multimedia and Geographic Systems Laboratory (1996-2018) Technical Coordinator of the Internet and Multimedia Technologies Research Unit (1997-2011) Scientific Manager of the Network Management Center of the TEI of Messolonghi (2009-mid 2013)
Haoyu Wang is a Researcher in the Computer and Information Science department at the University of Pennsylvania . He previously held research positions at Shanghai Jiao Tong University and interned at Google DeepMind , Amazon AWS , ByteDance , AI2 , Tencent AI Lab , and Goldman Sachs . Education : PhD in Computer and Information Science (2021–Present), MS in Computer and Information Science (2019–2021), BS in Computer Science (2015–2019). His research focuses on Event-Centric NLP/NLU , LLM Reasoning and Planning , Knowledge Graph , and Pose Estimation in Computer Vision . His work includes event causality identification, semantic classification in context, and synthetic control for temporal reasoning. He has contributed to multimodal hallucination analysis and safety in reasoning models through projects like RESIN-11 and Devil's Advocate . His publications span venues like EMNLP , EACL , and ACL . His recent articles analyze LLM limitations in NP-hard problems , clinical trial prediction , event causality , and hallucination in vision-language models . He has served as PC Member for conferences including ACL , NAACL , NeurIPS , and EMNLP since 2019.
Djamel Rezgui is an Associate Professor in Aerospace Engineering at the School of Civil, Aerospace and Design Engineering, University of Bristol, specializing in nonlinear dynamics, aeroacoustics, and flight control of advanced aircraft systems. His research bridges theoretical modeling with experimental validation for next-generation aviation technologies. Education: MEng (Institution unspecified) PhD, University of Bristol (2009) - Thesis: Investigation into Rotor Blade Stability in Autorotation Using Bifurcation and Continuation Methods Research Focus: Dr. Rezgui pioneers experimental control-based continuation techniques for analyzing nonlinear dynamics in rotating-stationary structures and flexible wings. His work on distributed electric propulsion (DEP) systems addresses aeroacoustic challenges in multi-rotor UAVs and eVTOL vehicles, while bio-inspired rotor designs draw from natural samara seed aerodynamics. Key methodologies include bifurcation analysis, whirl flutter stability assessment, and real-time hybrid testing for periodic oscillations. Publication Trends: Recent outputs (2023-2025) reveal concentrated efforts in propeller-wing interaction noise, folding wingtip aeroelasticity, and DEP optimization. Over 40% of his 119 publications tackle aeroacoustic prediction through multi-fidelity solvers, with growing emphasis on turbulent flow effects and phase-synchronized noise reduction for urban air mobility platforms. Research Leadership: Principal Investigator for three major projects: EPSRC MENtOR (EP/S010378/1, £1.2M, 2018-2022), VLN Methods and Experiments for Novel Rotorcraft (£850k, 2018-2021), and VLN MENtOR Bristol (£400k, 2018-2022). Supervised 6 research students with datasets spanning real-time hybrid testing and propeller-wing aeroacoustics. Collaborative Infrastructure: Core member of Bristol's Dynamics and Control group, utilizing wind tunnel facilities for experimental bifurcation analysis of flared folding wingtips and tilting rotors. Active contributor to Vertical Lift Network initiatives and AIAA conferences, with peer-review duties for The Aeronautical Journal .
