Find Academic Supervisors

• Composites
• Nano-composites
• Microscopy
• +5 more

Dr. David T. Fullwood is Professor of Mechanical Engineering at Brigham Young University (BYU), with a focus on composites/nano-composites, microscopy, and computational methods in materials science. He holds a PhD in Applied Mathematics (1991) and MS in Mechanical Engineering (2005) from BYU, alongside advanced degrees in Mathematics from the University of Utah (1989) and University of York (1987). His 25+ year career at BYU has produced 150+ peer-reviewed publications and patents, including a 2015 US patent for composite strain gauges and a 1994 flywheel patent. Education: 2005 MS (BYU), 1991 PhD (Applied Mathematics, London University) Employment: 2007–present (BYU Professor), 2006–07 (Drexel Research Assistant Professor) His research spans microstructure-sensitive design, twin transmission modeling in magnesium alloys, dislocation characterization via EBSD, and innovative sensor development using piezoresistive nanocomposites for biomechanical applications. He serves on technical committees for SAMPE and ICOTOM conferences, with 2016–2017 roles as General Chair. Recent work (2024–2025) explores strain gradient effects in aluminum alloys, viscoelastic modeling of nanocomposite sensors, and environmental factors influencing sensor drift. His 2025 publications include percolation theory for conductive composites and slip system identification in titanium alloys using coupled EBSD/HRDIC. Scientific Awards: SAMPE Best Paper (2011), CAMX Student Symposium 1st Place (2016), ICOTOM Keynote (2017) Dr. Fullwood teaches ME courses on composites, materials design, and computational methods while mentoring 13+ graduate students. His lab develops tools for EBSD-based dislocation analysis and contributes to the MagNET Research Network (2013) and multiscale mechanics studies in hexagonal metals.

Shakoor HajatView profile

Professor

• Climate Change
• Planetary Health
• Environmental Health
• +3 more

Professor Shakoor Hajat is a Professor of Global Environmental Health at the London School of Hygiene & Tropical Medicine , affiliated with the Department of Public Health, Environments and Society within the Faculty of Public Health and Policy. He serves as Director of the NIHR Health Protection Research Unit on Environmental Change and Health and contributes to the Centre on Climate Change and Planetary Health. Director, NIHR Health Protection Research Unit on Environmental Change and Health Committee Member, Centre on Climate Change and Planetary Health Editorial Board Member, International Journal of Environmental Research and Public Health Member, Global Climate-Homelessness Network Research Interests : Professor Hajat focuses on Climate Change , Planetary Health , and Environmental Health , particularly examining heat-related mortality, climate change impacts on vulnerable populations, and temperature-related health burdens. His recent work explores: Heat-related health risks for homeless populations Climate change effects on maternal and child health Neurological disease implications Temperature-mortality associations in Europe and Brazil Climate adaptation frameworks Teaching & Supervision : He directs the intensive MSc Public Health programme , organizes the Basic Statistics for PHP module , and lectures on Environmental Epidemiology. He has contributed to developing the new MSc Climate Change and Planetary Health programme and currently supervises three research degree students. Key Grants : NIHR Health Protection Research Unit on Climate Change and Health Security (2025-2030) HEARTH: National Hub on Net Zero Health and Extreme Heat (2025-2030) Developing solutions for temperature-related health impacts in the UK (2024-2028)

Jobst HeitzigView profile

Researcher

• Game Theory
• Complex Networks
• Climate Change Mitigation
• +5 more

Dr. Jobst Heitzig serves as Senior Scientist and Working Group Leader at the Potsdam Institute for Climate Impact Research (PIK) within the Department of Complexity Science, leading the Behavioural Game Theory and Interacting Agents (BeGa) group and developing the vodle group decision application. He holds a PhD in mathematics from Hannover University, with prior professional experience at the German National Statistical Office, German Development Bank KfW, and as a freelance statistical software trainer. His research integrates game theory, complex networks, and climate science to address democratic decision-making, climate coalition formation, and human-nature co-evolution. Key contributions include nondeterministic proportional consensus models for efficient democracy, bottom-up climate coalition frameworks, Moving Taylor Bayesian Regression (MoTaBaR) for data analysis, and power grid stability studies through the EIT Climate-KIC SWIPO project. His publication trends reveal interdisciplinary synthesis across mathematics, climate policy, and social choice, with influential work in PNAS and Social Choice and Welfare examining free-riding dynamics in climate agreements and consensus mechanisms. Dr. Heitzig co-leads the copan flagship project on coevolutionary pathways and directs the FutureLab on Game Theory & Networks of Interacting Agents, while previously managing the SWIPO power grid project. He actively organizes international workshops including the SC4AI series on Social Choice for AI Ethics (2023–2025) and delivers lectures on fair voting systems and human-empowerment-based AI.

• Behavioural Economics
• Experimental Economics

Florian Zimmermann is a Professor and Distinguished CESifo Affiliate affiliated with the Institute on Behavior and Inequality (briq) in Bonn, Germany. As a CESifo Research Network Fellow, he contributes to the Behavioral Economics research area led by Ernst Fehr and Klaus M. Schmidt, focusing on how cognitive biases and social factors influence economic decisions. His research centers on Behavioural and Experimental Economics, examining mental models in financial markets, belief formation mechanisms, and the interplay between social environments and self-assessment. Key investigations include moral universalism, trust determinants, climate risk perception, and job search behavior, often revealing how associative memory and motivated cognition drive economic choices. Analysis of his 15 most recent publications shows a consistent trajectory exploring cognitive limitations in decision-making, with increasing emphasis on real-world applications like climate finance and labor markets. His work bridges theoretical models of uncertainty with empirical evidence from field and lab experiments, highlighting systematic deviations from rational choice assumptions. Zimmermann operates within the Institute on Behavior and Inequality (briq), an independent Bonn-based research institute specializing in behavioral approaches to economic inequality. briq's collaborative environment enables interdisciplinary studies on how psychological factors perpetuate or mitigate inequality through mechanisms like discriminatory beliefs and social comparison.

• Latent Variable Models
• Dynamic Latent Variable Models
• Latent Class Methods
• +8 more

Augustin Kelava is a Professor at the Department of Quantitative Methods, Eberhard Karls University of Tübingen. He has held this position since 2018 and leads the Methods Center as Managing Director. Previously, he was Professor at the Hector Institute for Empirical Educational Research (2013-2018) and Junior Professor at Technical University of Darmstadt (2011-2013). PhD in Psychology (Goethe University Frankfurt, 2009) Diploma in Psychology (Goethe University Frankfurt, 2004) Kelava specializes in latent variable modeling, machine learning in social sciences, and educational research. His work spans dynamic latent class models, Bayesian regularization techniques, and prediction of human behavior using intensive longitudinal data. He contributes to psychometric theory (e.g., item response theory extensions) and applies these methods to diverse fields including sports science and emotion regulation. Editor of "Testtheorie und Fragebogenkonstruktion" (3rd ed., Springer, 2020) Key researcher in the Cluster of Excellence "Machine Learning in Science" Active in methodological conferences (FGME 2017, SEM 2019) Review activities for 20+ journals and foundations including Psychometrika, DFG, and SNSF His recent publications focus on integrating machine learning with psychometrics, addressing identifiability in complex models, and evaluating personality assessment validity for large language models. He collaborates with researchers across psychology, education, and computational fields.

Hakan DemirelView profile

Associate Professor

• Marine Engineering
• Risk Assessment
• Fuzzy Logic
• +7 more

Hakan Demirel is an Associate Professor in the Department of Marine Engineering at Istanbul Technical University, College of Engineering. His research integrates advanced computational methods with marine systems engineering to improve safety, performance, and environmental compliance in maritime operations. Research Interests: Dr. Demirel specializes in risk assessment, fuzzy logic applications, decision-making models (such as BWM, MARCOS, ELECTRE, DEMATEL), and reliability analysis in marine and offshore systems. His work addresses critical challenges in ship engine performance, emission control, ballast water treatment, mooring operations, and hybrid energy systems. Publication Trends: His recent publications (2020–2025) demonstrate a consistent focus on applying fuzzy set theories and Bayesian networks to maritime safety and environmental engineering. These works often involve multi-criteria decision-making frameworks and are published in journals related to marine science, engineering, and environmental risk assessment. Scientific Awards: No awards are mentioned in the provided text. Advising and Grants: Dr. Demirel has served as Principal Investigator (PI) on multiple research projects funded by BAP (Scientific Research Projects Unit at ITU), including projects on exhaust emission analysis and risk assessment of hydrocarbon ship berthing operations. While no formal students are listed, his collaborative publication pattern suggests active mentorship and team-based research. Labs and Research Teams: Although specific lab names are not mentioned, his research activities suggest involvement in a marine systems and safety research group at Istanbul Technical University, focusing on computational modeling for maritime engineering challenges.

Daniela de Angeli DutraView profile

Lecturer

• Disease Ecology
• Macroecology
• Parasitology
• +12 more

Daniela de Angeli Dutra is a Lecturer in Zoology at the School of Environmental and Natural Sciences, Bangor University. Her research sits at the intersection of disease ecology and macroecology, focusing on understanding the patterns and mechanisms of parasite spread, particularly malaria and malaria-like haemosporidian parasites in birds. She employs advanced modeling techniques such as network analysis and hierarchical Bayesian models, along with remote sensing and causal inference, to study the impacts of global change on disease transmission in wildlife and humans. Her research interests span a broad range of topics including avian parasitology, host-parasite dynamics, evolutionary ecology, and the conservation implications of disease. She investigates how factors like host migration, phylogeny, land use change, and climate affect parasite diversity and transmission. Her work contributes to improving conservation programs and human health policies by providing a deeper understanding of disease ecology. Dr. de Angeli Dutra's recent publications reveal a strong focus on the macroecology of avian haemosporidians, exploring drivers of parasite diversity, the role of migration in disease spread, host-parasite network structures, and the impacts of environmental gradients. She also contributes to critical discussions on equity in ecological research and research ethics in academia. Education: PhD, University of Otago (2020–2023) MSc, Universidade Federal de Minas Gerais (2017–2019) BSc, Universidade Federal de Minas Gerais (2013–2017) She is actively involved in the scientific community, publishing in high-impact journals such as Trends in Ecology and Evolution , Ecology Letters , Parasitology , and Science . While her primary focus is on research and teaching, she is open to supervising PhD and Master's students on projects related to parasite and disease ecology. Her work aligns with global sustainable development goals, particularly in the area of education and academic advancement.

Paloma Marí-BeffaView profile

Senior Lecturer

• Cognitive Neuropsychology
• Executive Functions
• Attentional Networks
• +3 more

Dr. Paloma Marí-Beffa is a Senior Lecturer at the School of Psychology and Sports Science , Bangor University. Her research focuses on Cognitive and Applied Neuropsychology , particularly Executive Functions , with applications to populations ranging from Schizophrenia to Martial Artists . She employs methods like ERP , Transcranial Magnetic Stimulation , and 3D virtual environments , exploring how verbal instructions , curiosity , and Martial Arts can enhance cognitive control. Education: PGCert in Teaching in Higher Education (Bangor University, 2001–2003) PhD in Experimental Psychology and Psychobiology (University of Almería, 1995–1997) MSc in Experimental Psychology and Behavioral Neurophysiology (University of Granada, 1992–1995) BSc in Psychology (University of Granada, 1987–1992) Research Trends: Her 15 most recent articles (2018–2025) span topics like ERP analyses , Stroop paradigms , Differential Outcomes Effect , and Martial Arts interventions . Keywords include Cognitive Neuroscience , Executive Functions , Task Switching , and Neurocognitive Aging . Activities: 2023: Bangor University Community Day stall 2022: Wales Martial Arts Practitioner-Researcher Network talk 2021: Workshop at University of Almería 2018: Public lecture on Martial Arts and brain function

Arun ChandrasekharView profile

Professor

• Economics
• Social Networks
• Economic Development
• +6 more

Arun Chandrasekhar is a Professor of Economics at Stanford University and Senior Fellow at the Stanford Institute for Economic Policy Research (SIEPR). His research focuses on the intersection of economics and network science, particularly in social and economic networks, economic development, and public health economics. Ph.D. in Economics from Massachusetts Institute of Technology (2012) B.A. in Mathematics from Columbia University (2007) Research Interests: Chandrasekhar investigates how social networks influence economic behavior, including information diffusion, reputation systems, and informal institutions. His work employs machine learning and network analysis to study microfinance, public health messaging, and economic development. Article Trends: His recent publications examine network effects in public health campaigns, measurement error in diffusion models, and network formation theory. Key themes include network analysis, social learning, and statistical methodology in economic contexts. Scientific Awards: 2024 Infosys Prize in Economics, Phi Beta Kappa (2006), NSF Graduate Research Fellowship (2007-2011), and Duke University's Empirical Microeconomists' Jamboree (2014) Advising and Grants: Chandrasekhar actively advises doctoral students in economics and serves as a faculty sponsor for postdoctoral research. He has received grants from the National Science Foundation and served as a referee for numerous top journals in economics and related fields.

• Biostatistics
• Pregnancy Complications
• Mathematical Modelling
• +7 more

Dr Shalem Leemaqz is an Adjunct Researcher in the College of Medicine and Public Health at Flinders University, where he contributes to the Pregnancy Health and Beyond (PHaB) Lab. He is also a Statistician at the South Australian Health and Medical Research Institute (SAHMRI), holding a PhD from the University of Adelaide and advanced degrees in statistics and engineering. PhD, Predicting Risk for Pregnancy Complications, University of Adelaide (2010–2015) Master of Applied Statistics, Macquarie University (2009) Bachelor of Science, Mathematics/Statistics & Electronic Systems Engineering, University of South Australia (2006–2008) His research focuses on biostatistics and mathematical modelling of complex health data, particularly in pregnancy complications and maternal-fetal health. He applies advanced statistical and machine learning techniques to high-dimensional datasets, integrating clinical and genomic information. His work spans predictive modelling for preeclampsia, preterm birth, gestational diabetes, and fetal growth restriction. More recently, his research extends into transgender health and cancer epidemiology, particularly Indigenous health disparities. His recent publications (2023–2025) reflect a strong trend in applying rigorous statistical and machine learning methods to clinical problems, especially in endocrinology and obstetrics. Key themes include risk prediction models, hormone therapy safety, cancer survival analysis, and data integration from omics and electronic health records. His work often involves secondary analyses of randomized trials and large cohort studies. Dr Leemaqz is committed to advancing statistical rigour in medical research and collaborates widely with clinicians and bioinformaticians. His contributions support multiple UN Sustainable Development Goals, particularly those related to good health and well-being. He has not received any specific scientific awards mentioned in the provided text. Dr Leemaqz advises no known students but actively contributes to research teams and collaborative projects. He does not hold any named grants in the information provided but is involved in externally funded research through SAHMRI and Flinders University. His technical expertise includes R programming, machine learning, and high-dimensional data analysis. He is a member of the PHaB Lab at Flinders University and contributes to research teams at SAHMRI, focusing on biostatistical support for large-scale health studies.

Pengcheng LiuView profile

Senior Lecturer

• Robotics
• Bio-inspired Robotics
• Soft Robotics
• +14 more

Pengcheng Liu is an Associate Professor (Senior Lecturer) in Robotics and Applied Control at the Department of Computer Science, University of York, UK. He has previously held academic positions at Cardiff Metropolitan University, University of Lincoln, Bournemouth University, and visiting roles in China. He is a member of IEEE and IFAC, and serves on several IEEE Technical Committees related to robotics and automation. PhD in Robotics and Control MSc in Control Theory and Control Engineering BEng in Measurement Control and Instrumentation His research focuses on the convergence of robotics and biology, particularly in bio-inspired design, soft robotics, human-robot collaboration, rehabilitation, and embodied AI. He explores how biological systems can inform adaptive, resilient, and energy-efficient robotic systems. His work spans modeling animal/human motion, sensory-motor learning, morphological design, and control optimization. The 15 most recent publications reflect a strong interdisciplinary trend combining robotics, control theory, machine learning, and biomedical applications. Key themes include soft robotics, bio-inspired actuators, motion planning, rehabilitation systems, and wireless communication for robotic systems. The research integrates simulation, hardware prototyping, and intelligent control, often using ROS and Gazebo. Global Peer Review Awards — Top 1% in Cross-Field (2019) Global Peer Review Awards — Top 1% in Engineering (2019) Outstanding Associate Editor of 2020, IEEE Access Outstanding Contribution Awards, Elsevier (2017) Dr Liu has extensive experience in securing and managing research grants from EPSRC, Innovate UK, Horizon 2020, Erasmus Mundus, FP7-PEOPLE, HEIF, NHS I4I, and NSFC. He serves as a regular reviewer for around 30 journals and 8 flagship conferences in robotics, AI, and control. He is an Associate Editor for IEEE Access and Academic Editor for PeerJ Computer Science, and has contributed to special issues on computational learning for robotics. He leads research in bio-inspired robotics and advises PhD students in areas such as lifelong learning machine intelligence, soft robotics, motion planning, and cyber-physical systems. He is actively recruiting motivated PhD candidates with backgrounds in engineering, computer science, or applied mathematics.

Jackie BaekView profile

Assistant Professor

• Machine Learning
• Algorithmic Fairness
• Data-Driven Operations
• +7 more

Jackie Baek is an Assistant Professor in the Department of Technology, Operations, and Statistics at the Leonard N. Stern School of Business, New York University, where she joined in January 2023. Her research bridges machine learning, operations research, and societal impact, focusing on algorithmic fairness, decision-making systems, and data-driven applications in healthcare and online platforms. Ph.D., Operations Research, Massachusetts Institute of Technology (2022) Bachelor, Mathematics, University of Waterloo Her research interests span Machine Learning, Algorithmic Fairness, Data-Driven Operations, Healthcare Analytics, Revenue Management, and Transportation Systems . She develops algorithms that improve decision-making while examining the societal consequences of algorithmic systems, particularly in hiring and health interventions. Her work combines theoretical rigor with practical applications, often involving collaborations with institutions like the Simons Institute at UC Berkeley. The recent publications reflect a strong trend in fairness-aware machine learning, bandit algorithms, and behavioral health interventions . Her work on TS-UCB improves Thompson sampling efficiency, while papers on statistical discrimination and algorithmic monoculture highlight ethical concerns in hiring algorithms. Other works apply machine learning to global health, such as COVID-19 forecasting and personalized behavioral interventions. These contributions appear in top-tier journals and conferences including Management Science , Operations Research , PNAS , and ACM FAccT . Her scientific awards include: Winner, Pierskalla Best Paper Award (2024) Second place, MSOM Student Paper Competition (2022) Finalist, George Nicholson Student Paper Competition (2021) Finalist, RMP Jeff McGill Student Paper Award (2021) Honorable Mention, MIT ORC Best Student Paper Award (2021) Oral presentation at EAAMO (2021) Jackie Baek has advised or collaborated on research with students and scholars such as Hamsa Bastani, Shihan Chen, and Vivek Farias. She has contributed to forecasting efforts through the COVID-19 Forecast Hub and presented her work at venues like BIRS. While no specific grants are mentioned, her publications suggest support from institutions like MIT, Simons Institute, and NYU Stern. She is actively involved in research groups focusing on dynamic allocation and matching, as evidenced by her BIRS talk in 2025. She maintains an active research presence with code available on GitHub and participates in interdisciplinary collaborations across computer science, operations, and social impact. Her lab or research team appears to focus on algorithmic fairness and decision systems, likely involving graduate students and postdocs in ongoing projects related to fairness, learning, and operations.

• Hematology
• Bone Marrow Failure Syndromes
• Aplastic Anaemia
• +6 more

Lucy Fox is a Research Fellow in Acute & Critical Care at Monash University, actively contributing to clinical and genomic research in hematological disorders. She is involved in multiple national research projects focusing on bone marrow failure syndromes, aplastic anaemia, and transfusion medicine. Her research interests lie at the intersection of hematology, genomics, and clinical outcomes, particularly in inherited bone marrow failure and related disorders. She investigates novel phenotypes, diagnostic genomics, and management strategies for rare hematopoietic conditions. Her work supports advancements in precision medicine and patient-centered care in critical hematology. The recent publications highlight a strong trend in clinical genomics, therapeutic trials in aplastic anaemia, and ethical considerations in blood donation for individuals with hereditary cancer predispositions. Her research spans editorial insights, clinical protocols, and original genomic discoveries, reflecting a multidisciplinary approach to improving patient outcomes. Lucy Fox has contributed to significant collaborative projects funded by the Department of Health and Aged Care, Australia, including the DIAAMOND study and national transfusion data initiatives. She has also engaged in external HDR supervision, mentoring a Doctor of Medical Science student on bone marrow failure outcomes. She has been involved in key research networks and collaborations across Australia, working with leading hematologists and researchers. Her laboratory and team affiliations are embedded within large multicenter research consortia focused on hematological diseases and data-driven clinical solutions.

• Bayesian Statistics
• Hierarchical Modeling
• Demographic Statistics
• +4 more

Hannah Comiskey is a Research Fellow in the Department of Econometrics and Business Statistics at Monash University, within the Faculty of Business and Economics. Her research focuses on advanced statistical methods applied to global health and demographic data, particularly in reproductive health contexts. Her primary research interests lie in Bayesian hierarchical modeling, statistical demography, and public health analytics. She develops and applies sophisticated statistical models to estimate health indicators, especially related to contraceptive use and healthcare system contributions across countries. The recent publication in the Journal of the Royal Statistical Society Series A demonstrates a strong trend in using flexible Bayesian non-parametric models for health estimation, particularly in low-data settings. Her work integrates survey data from multiple sources to disentangle public and private sector roles in modern contraceptive supply. Hannah has actively contributed to academic discourse through presentations, including at the Annual Meeting of the Population Association of America (2022). While no formal advising or grant information is available, her collaborations with researchers like Leontine Alkema and Niamh Cahill suggest involvement in large-scale demographic estimation projects. She is part of an international research network focused on population health statistics, with external collaborations across multiple countries. Her work contributes to evidence-based policy in reproductive health through rigorous statistical inference.

• Infectious Diseases
• Tuberculosis
• HIV/TB Co-infection
• +9 more

Derek Sloan is a Reader and Consultant in Infectious Diseases at the School of Medicine, University of St Andrews, within the Infection and Global Health Division. He also holds an honorary position as Senior Lecturer at the Liverpool School of Tropical Medicine and Institute of Global Health, University of Liverpool. Education: PhD in Infection and Global Health, University of Liverpool (2013) Doctor of Medicine, University of Liverpool Master in Science, University of Chester Diploma in Tropical Medicine and Hygiene, University of Liverpool MRCP (UK), Royal College of Physicians, Glasgow Bachelor of Medicine and Bachelor of Science (Immunology), University of Glasgow Derek's research focuses on clinical therapeutics in global health, with emphasis on tuberculosis, HIV co-infection, antimicrobial resistance, and pharmacokinetic/pharmacodynamic (PK-PD) modeling. His work spans both high- and low-income countries, particularly Malawi and Uganda, addressing critical public health challenges through innovative diagnostics and treatment strategies. He has contributed to outbreak responses, including the UK’s Ebola response in West Africa in 2015. His recent publications reflect a strong trend in developing AI-driven diagnostic tools for TB, modeling antimicrobial resistance in East Africa, evaluating novel TB drugs like BTZ-043 and bedaquiline, and assessing the impact of dolutegravir in HIV treatment. His research integrates clinical data, microbiology, and computational modeling to improve patient outcomes. Scientific Awards: Conference on Retroviruses & Opportunistic Infections Young Investigator Award (2014) Conference on Retroviruses & Opportunistic Infections Young Investigator Award (2013) European Society for Clinical Microbiology and Infectious Diseases Travel Grant (2013) BIS/MSD Travel Bursary (2006) University of Cape Town Scholarship (2011) Derek Sloan has supervised several graduate students, including Rotimi Owolabi and Dr. Andrew McCallum, and has led or co-led major funded projects from the Wellcome Trust, Medical Research Council, European Commission, and EDCTP. His team collaborates extensively across the UK, Malawi, Uganda, and Tanzania, focusing on improving diagnostics, treatment safety, and antibiotic stewardship. He has been Principal Investigator on grants related to TB in the context of COVID-19 and antimicrobial resistance, and continues to lead cutting-edge research in infectious disease therapeutics and global health innovation.