Find Academic Supervisors

Paolo GorgiView profile

Associate Professor

• Score-driven time series models
• Stochastic processes
• Forecasting economic variables
• +3 more

Dr. Paolo Gorgi is an Associate Professor at the Department of Econometrics and Data Science in the School of Business and Economics at Vrije Universiteit Amsterdam. He holds a PhD in Statistics and Econometrics from the Joint Degree Program of the University of Padova and Vrije Universiteit Amsterdam (2017). His research focuses on score-driven time series models, stochastic processes, forecasting economic variables, and statistical inference in non-linear dynamic models. He is also a Partner at ACMetric B.V. since 2021. His work contributes to UN Sustainable Development Goals related to economic growth and sustainable cities. Key research interests include developing novel methodologies for time series analysis, particularly in handling non-linear dynamics and high-dimensional data. He has authored over 36 publications, including influential works on score-driven models, copula-based count models, and robust statistical estimation techniques. Teaching responsibilities include courses on Data Science Methods and Financial Econometrics . His research network spans collaborations with institutions globally, focusing on econometric applications in finance, macroeconomics, and sports analytics. He has supervised two PhD theses and actively contributes to the academic community through editorial roles and conference participation.

Bin LiView profile

Researcher

• Machine Learning
• Biomedical Engineering
• Bioimage Informatics
• +5 more

Dr. Bin Li is a postdoctoral researcher in the Institute of Biomedical Engineering at the University of Oxford . His work bridges machine learning , bioimage informatics , and computational pathology , with a focus on advancing AI applications in healthcare. Education: PhD in Biomedical Engineering (2020) from the University of Wisconsin-Madison under Professor Kevin Eliceiri. Dr. Li's research centers on developing deep learning techniques for histopathology , emphasizing weakly supervised and semi-supervised learning to analyze unlabeled/coarsely-labelled data. He also explores multimodal learning for image-based drug screening, integrating data from microscopy, genomics, and proteomics. His publication history reveals expertise in stochastic PDEs , singular SPDEs , and nonlinear dynamics , indicating cross-disciplinary foundations in mathematics and physics. Dr. Li contributes to the Professor Jens Rittscher's group , focusing on innovative computational methods for biomedical image analysis.

Lili YuView profile

Lecturer

• Reading Comprehension
• Eye Movements
• Cross-Language Reading
• +5 more

Lili Yu is a Lecturer at the School of Psychological Sciences, Macquarie University, and a member of the Macquarie University Centre for Reading. Her research focuses on cognitive and perceptual processes underlying reading comprehension, employing eye-tracking methodologies to investigate how visual attention interacts with linguistic processing. She holds a Ph.D. in Psychology from Tianjin Normal University (2014). Her research interests include: Eye movement patterns as indicators of reading comprehension Cross-language differences in reading strategies Misinformation retention in digital environments Multimodal integration of text, speech, and visual information Yu has led or contributed to three major projects including the Macquarie University Centre for Reading (2020–2022) and the Centre for Elite Performance Expertise and Training (2019–2021). She serves on the editorial boards of Behavior Research Methods and Scientific Reports . Her recent work explores digital reading's cognitive impacts, Chinese reading mechanisms, and predictive eye movement models. Collaborative projects include developing child-friendly eye-tracking tools for literacy research and analyzing subtitle processing in multimedia contexts.

• Renewable Energy
• Sustainable Development
• Environmental Economics
• +4 more

Prof. Magdalena Ligus is a full Professor at the Department of Corporate Finance and Public Finance within Wrocław University of Economics. Her primary research focuses on sustainable energy development, renewable energy policy evaluation, and multi-criteria analysis of energy technologies. She has contributed significantly to developing methodologies for assessing energy sustainability indices and quantifying externalities in energy systems. Her work integrates environmental economics principles with financial analysis, particularly examining eco-efficiency investments and regulatory impacts on energy markets. Prof. Ligus has published extensively on topics like renewable energy technology rankings, cost-benefit analyses of low-emission systems, and hedonic valuation of environmental amenities. Recent studies include evaluation of EU energy policies and spatial analysis of urban environmental impacts on housing markets. Key research themes: Sustainable Energy Indices, Renewable Energy Financing, Multi-Criteria Decision Analysis Methodological expertise: Contingent Valuation, Fuzzy AHP-TOPSIS, Hedonic Pricing Models Policy focus: EU energy strategy implementation, Polish energy transition challenges Her interdisciplinary approach bridges financial, environmental, and technological dimensions of energy systems, with particular emphasis on policy instruments for achieving climate goals. Current research trends include assessing energy security valuation, spatial distribution of renewable energy potentials, and regulatory risk in dynamic energy markets.

Isabel ValeraView profile

Professor

• Machine Learning
• Fairness in AI
• Causal Inference
• +7 more

Isabel Valera is a full Professor in the Department of Computer Science at Saarland University, Saarbrücken, Germany. She also holds an adjunct faculty position at the Max Planck Institute for Software Systems (MPI-SWS) and is a fellow of the European Laboratory for Learning and Intelligent Systems (ELLIS), contributing to the Robust Machine Learning Program and the Saarbrücken AI & Machine Learning (Sam) Unit. Research Interests: Her work lies at the intersection of machine learning, fairness, and causality. She focuses on developing methods for algorithmic recourse , fair decision-making , causal modeling , and robust learning . She is particularly interested in designing models that provide actionable explanations and ensure equitable outcomes in AI systems. Her research leverages probabilistic modeling, variational inference, and deep generative architectures. Publication Trends: Her recent publications (2021–2023) show a strong emphasis on algorithmic recourse , fairness under uncertainty , causal representation learning , and multimodal and graph-based generative models . She frequently publishes in top-tier venues such as NeurIPS, ICML, ICLR, AAAI, and FAccT, often in collaboration with leading researchers like Bernhard Schölkopf and Zoubin Ghahramani. Scientific Awards and Fellowships: Humboldt Post-Doctoral Fellowship Minerva Fast Track Fellowship (Max Planck Society) ELLIS Fellow Advising and Grants: She has mentored several early-career researchers who are now active contributors in machine learning, including Adrián Javaloy and Amir-Hossein Karimi. While specific grant details are not listed, her leadership roles and fellowships indicate sustained funding support from major research organizations. She has served as a co-editor for major conferences such as AISTATS and ECML PKDD, demonstrating her active role in the academic community. Labs and Research Groups: She leads or has led research groups at both Saarland University and the Max Planck Institutes (MPI for Intelligent Systems and MPI for Software Systems), focusing on foundational and applied aspects of machine learning with societal impact.

Tamara BlakeView profile

Research Fellow

• Respiratory Physiology
• Paediatrics
• Cystic Fibrosis
• +6 more

Dr Tamara Blake is a Research Fellow and Respiratory Scientist at the Child Health Research Centre , affiliated with the Faculty of Health, Medicine and Behavioural Sciences at The University of Queensland . With a PhD from Queensland University of Technology , her expertise lies in pediatric lung function assessment and respiratory disease mechanisms. Education: Doctor of Philosophy (Queensland University of Technology) Her research focuses on Cystic Fibrosis , Asthma , and Australian First Nations respiratory health , particularly validating diagnostic standards for spirometry and fractional exhaled nitric oxide. Recent studies explore environmental impacts on lung development, CF disease progression, and novel oscillometry techniques for preschoolers. Major grants include MBW Training and LCI Overread Services (2023–2026) and Running for Health (2023–2026). She supervises PhD projects on early CF disease detection, MRI lung structure analysis, air pollution impacts, and normative oscillometry data development. Key collaborations span Queensland Children's Hospital , CSIRO , and Barwon Infant Study Investigator Group . Her work emphasizes improving clinical outcome measures for vulnerable populations and advancing diagnostic tools for early respiratory disease intervention.

• Statistics
• Randomized Response Techniques
• Survey Sampling
• +5 more

Pier Francesco Perri is a Full Professor of Statistics (SSD STAT-01/A) at the Department of Economics, Statistics, and Finance 'Giovanni Anania' (DESF) of the University of Calabria (Unical). He has held academic positions since 2002 and coordinates institutional activities such as the National Plan for Scientific Degrees (L-41, Statistics) and editorial roles in journals like Metron and Model Assisted Statistics and Applications . His research focuses on survey methodology, sensitive data estimation, and statistical modeling. Education: Ph.D. in Methodological Statistics (University of Trento, 2002), Honors Degree in Statistical and Actuarial Sciences (University of Calabria, 1997) Perri’s research spans randomized response techniques for sensitive populations, copula modeling for financial data, and inequality index linearization. He explores indirect questioning methods to detect truthfulness and improve survey accuracy, particularly for stigmatized behaviors like abortion, migration, and non-heterosexual identities. His work integrates auxiliary information and complex sampling designs to enhance estimation efficiency. Recent publications emphasize innovations in sample survey traditions, including the 2025 editorial on methodological advancements and 2024 studies on adjusting self-protective behaviors in prevalence estimation. His 2023–2021 research includes logistic regression extensions for randomized response models, prevalence estimates for health behaviors, and crossed model applications for sensitive topics. Earlier work (2020–2000) covers item sum techniques, financial copula modeling, and environmental sensitivity analysis. He serves on editorial boards and institutional committees, including the Italian Statistical Society’s Council and the Ph.D. Teaching Board at Unical. The Laboratorio Statistico Informatico supports his research in statistical computing and survey design.

Yanghui KangView profile

Assistant Professor

• Remote Sensing of Terrestrial Ecosystems
• Agroecosystem Monitoring and Modeling
• Nature-Based Climate Solutions
• +4 more

Yanghui Kang is an Assistant Professor in the Department of Biological Systems Engineering at Virginia Tech. He holds a Ph.D. in Geography from the University of Wisconsin-Madison and has prior postdoctoral experience at UC Berkeley and USDA-ARS. His work integrates satellite remote sensing, machine learning, and process-based modeling to monitor terrestrial ecosystems and address climate mitigation through nature-based solutions. B.S. (2011): Geographic Information Science, Beijing Normal University M.S. (2013): Environment & Resources, University of Wisconsin-Madison M.S. (2018): Computer Sciences, University of Wisconsin-Madison Ph.D. (2020): Geography, University of Wisconsin-Madison Research focuses on remote sensing of vegetation dynamics , agroecosystem modeling , and nature-based climate solutions . He develops frameworks for quantifying carbon/water fluxes, leaf area index (LAI), and gross primary productivity (GPP) using satellite data. His work enables sustainable land/water management and climate policy support. Recent publications span multi-sensor LAI validation , CO2 fertilization impacts on GPP , and deep learning for ecosystem monitoring . Key projects include OpenET satellite evapotranspiration and CEDAR-GPP datasets , with funding from NASA and prior fellowships from SCINet and NASA Earth Science . Scientific Awards : NASA Early Career Investigator (2024), SCINet Fellowship (2020-2021), IOP Top Cited Paper (2020) He advises graduate students working on ecosystem-atmosphere fluxes , agricultural water use , and climate-adaptive remote sensing . The Kang Lab maintains open-source tools like the Landsat-LAI GitHub repository for global vegetation monitoring.

Olaf PoschView profile

Professor

• Macroeconomics
• Dynamic Stochastic General Equilibrium (DSGE) Models
• Asset Pricing
• +12 more

Olaf Posch is a Professor of Economics, specializing in Methods of Economics, at the Department of Economics within the Faculty of Economics and Social Sciences at the University of Hamburg. His research integrates macroeconomic theory, econometrics, and computational methods to analyze dynamic equilibrium models, asset pricing, and policy design. Research Interests: His primary research areas include Macroeconomics, Dynamic Stochastic General Equilibrium (DSGE) models, Asset Pricing, Monetary and Fiscal Policy, Econometrics, Structural Estimation, and Continuous-Time Modeling. He investigates the implications of uncertainty, rare disasters, heterogeneous agents, and public policy on macroeconomic dynamics and financial markets. Recent Research Trends: His recent publications demonstrate a consistent focus on advancing the estimation and solution methods of macroeconomic models. He explores the role of uncertainty (e.g., Peso problems, Poisson shocks), the impact of fiscal policy and debt maturity (e.g., FTPL), and the importance of risk in model approximations. His work often bridges theoretical innovation with empirical application, using mixed-frequency data and structural estimation techniques. Scientific Grants: DFG Project No. 268475812: 'Dynamic equilibrium models' – Developing a continuous-time New Keynesian model. DFG Project No. 446166239: 'Fiscal Sustainability'. DFG Project No. 510995673: 'Fiscal policy in models with heterogeneous agents'. Advising and Grants: While specific advisees are not listed, he frequently collaborates with co-authors on research projects and working papers, indicating an active role in mentoring junior researchers. He is the principal investigator on multiple DFG-funded projects, demonstrating significant grant acquisition and research leadership. Laboratories and Research Teams: He leads a research team at the University of Hamburg, including Corinna Kienle, Réka Rátfai, and Josie Oetjen, focused on dynamic equilibrium models and macroeconomic policy analysis.

Ionel HaiduView profile

Professor

• Hydrology
• Climatology
• Time Series Analysis
• +4 more

Ionel Haidu is a University Professor of Geography at the University of Lorraine since 2011, affiliated with the LOTERR-EA7304 Laboratory. His research focuses on hydro-climatic systems with international collaborations across France, Romania, Morocco, and the European Commission. Academic Background: Doctorate in Geography (1991, Alexandru Ioan Cuza University Iaşi) Master of Sciences in Hydrology (1992, Vrije Universiteit Brussels) Postgraduate Diploma in Water Resources Engineering (1994, Technical University of Bucharest) GIS Certification (1995, Clark University & Hungarian College) Haidu's research integrates hydrology , climatology , and remote sensing to address climate change impacts, particularly in Mediterranean and Eastern European regions. His work emphasizes probabilistic risk assessment, time-series analysis of hydro-climatic data, and technical geography applications for environmental management. Recent projects analyze drought trends in Morocco, lake dynamics using satellite imagery, and air pollution variations during/post-pandemic. His publication trends reveal three dominant themes: (1) Climate change adaptation in water resources (40% of recent work), (2) Remote sensing applications for environmental monitoring (35%), and (3) Spatial analysis of hydro-climatic risks (25%). Key methodologies include Kalman filters, LSTM networks, and principal component analysis applied to satellite data. Scientific Recognition: Annual Prize of the Romanian Academy for Geography (1995) Haidu supervises four doctoral students researching Moroccan water resources, European air pollution, Romanian geotourism, and Eastern European climate risks. His grant portfolio includes EU-funded projects like FOREST@RISK (JRC) on forest climate risks, REGE regional environmental network, and RECRET historical hydrological reconstruction. Previous grants covered Romanian mountain settlements (2006-2010) and France-Romania-Madagascar climate impact studies (2008-2010). As core faculty in LOTERR Laboratory, he contributes to three thematic axes: Water/Environments, Landscape Transitions, and Territorial Planning. His technical platform utilizes hydrometry, drone imaging, and online databases like the 30,000-image LOTERR aerial archive and IKARE karst mapping system.

Louis LongchampsView profile

Assistant Professor

• Precision Agriculture
• Farm Data Management
• On-Farm Experimentation
• +5 more

Louis Longchamps is an Assistant Professor in the School of Integrative Plant Science (Soil and Crop Sciences Section) at Cornell University. He specializes in digital agronomy, precision agriculture, and farmer-centric on-farm experimentation. His work focuses on integrating farm data management systems with environmental sustainability goals. Education: PhD in Agronomy from Laval University (thesis on weed population spatial structure and site-specific weed management). Postdoctoral research at Colorado State University’s Department of Soil and Crop Sciences. Research Interests: Precision nitrogen management using remote sensing, reduction of nitrous oxide emissions via variable rate fertilization, co-creation of solutions with farmers for environmental stewardship, and leveraging AI/digital tools for farm decision-making. Recent projects include assessing on-farm experimentation practices in NY State and developing frameworks for pooling farm data across multiple sites. Outreach: Leads an integrated research-extension program focused on co-creating digital agriculture solutions with farmers. Engages in expanding on-farm experimentation through data contextualization and artificial intelligence applications. Labs/Teams: Associated with the Farmers DataLab initiative. Previously co-led a Living Laboratory project on the St. Lawrence River ecosystems.

Federico MariniView profile

Professor

• Chemometrics
• Analytical Chemistry
• Food Chemistry
• +3 more

Federico Marini is a Full Professor at the Department of Chemistry, University of Rome La Sapienza. He holds editorial roles including Editor-in-Chief of *Chemometrics and Intelligent Laboratory Systems* and membership in multiple journal boards. His research focuses on chemometrics, particularly method development and application in food chemistry, metabolomics, and multi-block data analysis. He has authored over 300 publications and edited books like *Chemometrics in Food Chemistry* (Elsevier 2013). Education: PhD in Analytical Chemistry (University of Rome La Sapienza, 2004) with Marie Curie Fellowship (2000–2004). Postdoctoral roles included visiting positions at universities in Copenhagen, Stellenbosch, and Lille. Research interests span advanced chemometric methods for food authentication, omics data processing, and non-linear modeling. Notable contributions include SO-PLS(-LDA) algorithms and multi-block fusion strategies. He coordinates the Chemometrics Task Group of DAC-EuCheMS and serves as Vice President of the Italian Society of NIR Spectroscopy. Awards include the 2006 Young Researcher Award (Italian Chemical Society) and 2012 Chemometrics Award. His work bridges analytical chemistry with data science, addressing real-world problems in agriculture, food safety, and biomedicine through innovative spectroscopic and statistical techniques.

Lindsey Van YperView profile

Senior Lecturer

• Auditory Neuroscience
• Cochlear Implants
• Binaural Hearing
• +5 more

Lindsey Van Yper serves as a Senior Lecturer at Macquarie University within the Department of Linguistics Hearing Research Centre. With an ORCID identifier (0000-0002-6062-0928) and active research profile, she maintains a significant presence in auditory neuroscience research with an h-index of 7 based on Scopus citations. Dr. Van Yper completed her PhD at Ghent University (Belgium) in 2016, with research funded by the Institute for Neuroscience conducted in collaboration with Radboud University Medical Centre in Nijmegen, Netherlands. Her doctoral work focused on central auditory processing in cochlear implant users who wear hearing aids in their non-implanted ear. Her research interests center on understanding brain mechanisms of binaural hearing in both normal hearing listeners and bilateral cochlear implant users. She employs electrophysiological techniques and functional near-infrared spectroscopy to investigate auditory processing, with particular emphasis on speech perception, cochlear prostheses, and neural responses to auditory stimuli. Her work bridges clinical audiology with fundamental neuroscience, examining how the brain processes complex auditory scenes and emotional vocal cues. Analysis of her recent publications reveals consistent focus on neural correlates of auditory processing, with growing emphasis on cortical hemodynamic responses and the relationship between neural activity and perceptual outcomes in hearing-impaired populations. Her research increasingly incorporates advanced neuroimaging techniques to examine individual differences in auditory processing capabilities. Dr. Van Yper actively supervises PhD candidates in auditory neuroscience, guiding research that utilizes neurophysiological measures to understand the human auditory system in both normal and impaired hearing conditions. Her grant portfolio includes significant projects such as 'On the relation between speech understanding and neural processing' (2021-2026), 'How does the human brain separate foreground and background in complex auditory scenes?' (2020), 'MQRIS Small: Audiological equipment to unlock hearing research' (2020), and the 'Faculty Equipment Grant Scheme 2017'. She maintains laboratory facilities within the Hearing Research Centre, with recent dataset publications indicating active primate auditory research. Her work shows increasing media attention, with one dataset 'picked up by 17 news outlets' and widely shared on academic platforms.

Özlem TÜRKER BAYRAKView profile

Associate Professor

• Statistics
• Time Series Analysis
• Quality Control
• +5 more

Dr. Özlem TÜRKER BAYRAK is an Associate Professor at Çankaya Üniversitesi, primarily affiliated with the Department of Statistics under the Inter-Curricular Courses unit. She has held academic roles since 1996, including Assistant Professor at the Faculty of Engineering and Visiting Position at University of Waterloo. Her research focuses on statistical methodologies, time series analysis, quality control, environmental acoustics, and energy economics. She has advised 11 graduate students and contributed to projects like the Turkish soundscape evaluation and robust estimation techniques. She teaches courses such as Engineering Statistics and Systems Analysis. Key research areas include non-normal distribution modeling, soundscape perception, and energy market dynamics. Recent work includes studies on urban nightlife impacts and adaptive statistical inference. She has over 40 publications in journals like Applied Acoustics and Quality and Reliability Engineering International.

Enrique Orduña-MaleaView profile

Assistant Professor

• Library and Documentation Science
• Webometrics
• Cybermetrics
• +9 more

Enrique Orduña-Malea is an Assistant Professor in the Department of Communication, Audiovisual Media, Documentation and Art History at the Universitat Politècnica de València (UPV). His work is centered in Library and Information Science, with a strong emphasis on webometrics, cybermetrics, and digital scholarly communication. He contributes to key initiatives such as the EXIT directory, DocuMenea, and the ThinkEPI think tank, promoting innovation in information science through collaborative and web-based platforms. Research Interests: His research spans webometrics , information retrieval , author name disambiguation , academic search engines (especially Google Scholar), and the use of social media (e.g., Twitter) as alternative indicators of academic impact. He investigates the web presence and visibility of universities, digital repositories, and industry-academia linkages. Publication Trends: His most recent work (2013–2015) focuses on methodological advances in measuring academic web impact, including estimating Google Scholar's index size, analyzing Twitter as a source of external links, and mapping the web network structures of private companies and university-industry interactions. These studies reflect a strong methodological orientation using data from Topsy, Majestic, and Open Site Explorer. Scientific Awards: None mentioned in the provided texts. Advising and Grants: There is no information available on student supervision, grant funding, or formal advising roles in the provided materials. Labs and Teams: He is actively involved in collaborative research groups, notably Grupo ThinkEPI , a think tank focused on innovation in information and documentation, and contributes to the EXIT directory, a web 2.0 platform for experts in information management. He also co-founded DocuMenea , a social news site for documentation professionals.