Find Academic Supervisors

• Cosmology
• Large Scale Structure of the Universe
• Cosmic Microwave Background
• +5 more

Fabien Lacasa is a cosmology researcher affiliated with the Université Libre de Bruxelles as a postdoctoral researcher funded by BELSPO (ESA, Euclid). He holds a dual role as Maître assistant at the University of Geneva and chercheur associé at the Institut d'Astrophysique Spatiale (Université Paris-Saclay). His career spans multiple institutions including ICTP-SAIFR, University of Padova, and involvement in major missions like Planck, Dark Energy Survey, and Euclid. Past Affiliations : PhD at Institut d'Astrophysique Spatiale (2010-2013), Postdoc at ICTP-SAIFR (2013-2016), University of Geneva (2016-2019, 2021-2022), CNES postdoc (2019-2020), INFN postdoc (2022-2023) His research focuses on non-linear effects in cosmic structure formation , analyzing Large Scale Structure (LSS), Cosmic Microwave Background (CMB), and their interplay. Key contributions include modeling super-sample covariance ( Lacasa & Grain 2018 ), bispectrum analysis for primordial non-Gaussianity, and developing methodologies for multi-probe cosmological constraints. He actively shares computational tools through GitHub repositories like IDL-fablib (CMB analysis routines) and PySSC (super-sample covariance implementation with comprehensive documentation). Data and analysis notebooks for his publications are openly available to ensure reproducibility.

Michael DrydenView profile

Assistant Professor

• Microfluidics
• Analytical Chemistry
• Neurobiology
• +3 more

Michael Dryden is an Assistant Professor at the University of Toronto (Downtown Toronto Campus). His research focuses on developing microfluidic systems for single-cell analysis, electrochemical sensing, and biomedical applications. Key areas include astrocyte responses to stroke, digital microfluidic devices for immunoassays, and integration of nanotechnology in analytical platforms. Research interests span Neurobiology, Analytical Chemistry, and Biomedical Engineering with a strong emphasis on lab-on-a-chip technologies. Notable contributions include open-source hardware for analytical instruments and novel methods for dopamine uptake measurements in neurons. His work bridges fundamental science and practical applications, addressing challenges in medical diagnostics and neuroscience. No scientific awards have been listed in available data.

Jamie SikoraView profile

Assistant Professor

• Quantum Computing
• Quantum Information
• Quantum Cryptography
• +3 more

Dr. Jamie Sikora is an Assistant Professor in the Department of Computer Science at Virginia Polytechnic Institute and State University (Virginia Tech), within the College of Engineering. His research focuses on quantum computing, quantum information, quantum cryptography, semidefinite programming, and convex optimization. He holds a Ph.D. in quantum computing from the University of Waterloo, Canada. His work addresses foundational and applied challenges in quantum information science, including cryptographic protocols, error mitigation, and optimization techniques. Recent research has explored quantum state exclusion, secure sampling, and device-independent protocols. His contributions span theoretical frameworks for quantum algorithms and cryptographic systems, with implications for post-quantum security and quantum communication. He has published extensively in top venues, including the Conference on the Theory of Quantum Computation and the Physical Review series. His articles often bridge quantum theory with practical cryptographic and computational applications, emphasizing rigor in protocol design and analysis.

Rosie TohidiView profile

Lecturer

• Environmental Chemistry
• Analytical Chemistry
• Environmental Toxicology
• +3 more

Rosie Tohidi is an Instructor of Chemistry at the Department of Chemistry, Virginia Tech, within the College of Science. Her research focuses on environmental chemistry, analytical methods, and pollution assessment. She has contributed to studies on pollutants like PAHs, triclosan, and heavy metals in environmental samples, emphasizing wastewater treatment processes and ecological impacts. Her work spans urban pollution, soil biology, and metabolic profiling in microbial systems. Her publications since 2004 reflect a strong emphasis on environmental contaminants, analytical techniques (e.g., GC/MS), and ecological health. Trends include investigation of triclosan fate in wastewater, heavy metal toxicity in aquatic ecosystems, and methodological advancements in trace metal analysis. No scientific awards or grants are explicitly mentioned in the provided text. She currently has no listed advisees or students, though her role as an instructor likely involves teaching and mentoring.

Max FalkenbergView profile

Research Fellow

• Computational Social Science
• Network Science
• Climate Communication
• +3 more

Max Falkenberg is a Research Fellow in the Department of Network and Data Science at Central European University (CEU), Vienna, Austria, and holds Visiting Fellow positions at the Institute for Sustainable Resources at University College London (UCL) and the Inverse Complexity Group at IT:U in Linz, Austria. He earned his PhD in Physics from Imperial College London (2022) and completed a postdoc in Mathematics at City, University of London (2024). His research applies network science and computational methods to study political polarization, climate communication, climate finance, and structural dynamics of social systems. Dr. Falkenberg’s work bridges computational social science with policy analysis. Notable contributions include datasets on Indian microblogging platform Koo, reports on climate tipping points for COP28, and analyses of fossil fuel finance in banking sectors. His findings have been featured in media outlets like The Guardian, Bloomberg, and BBC World Service. He has also advised policy forums such as the UK Parliament’s EFRA Select Committee and presented at institutions like the Bank of England and Spotify. Education: PhD Physics (Imperial College London), MSci Physics (Imperial College London) Key Projects: Climate finance modeling, Koo dataset analysis, COP28 climate policy report Media Contributions: Interviews with The Times, AFP Paris, and TVP World His policy-oriented research includes op-eds in The Banker (Financial Times) and collaborations with think-tanks. Falkenberg’s interdisciplinary approach integrates network science, statistical inference, and AI to address global challenges in sustainability and governance.

• Mathematical Biology
• Ecology
• Population Dynamics
• +7 more

Lia Hemerik is an Associate Professor in Mathematical and Statistical Methods at Wageningen University & Research. She holds dual master's degrees in Biology (1985) and Mathematics (1987) from Leiden University, followed by a PhD in 1991 on 'Studies on larval parasitoids of Drosophila: from individuals to populations.' Her research integrates mathematical modeling with ecological applications, focusing on survival analysis, population dynamics, and biological control. Key areas include food web stability, invasive species, sustainable agriculture, and conservation of endangered species. She has contributed to pioneering studies, such as investigating magnetic alignment in cattle and analyzing the impact of climate change on forest recovery. Her work also extends to educational outreach, including authoring a Dutch booklet on ecological tipping points and developing teaching materials for high school students on statistics and ecology. Hemerik actively engages in interdisciplinary projects, combining ecological modeling with policy-relevant questions like ecosystem service valuation and soil biodiversity assessment. Her academic roles include teaching advanced courses in mathematical methods, ecological modeling, and soil biology. She has advised numerous research projects and contributed to international collaborations on pest risk assessment and Arctic ecosystem resilience. Beyond academia, she advocates for environmental stewardship through initiatives like Homeward Bound and promotes public engagement in nature conservation.

Christine StauberView profile

Professor

• Environmental Health
• Water Sanitation
• Environmental Microbiology
• +3 more

Dr. Christine Stauber is a Professor and Associate Chair in the Department of Population Health Sciences at Georgia State University School of Public Health, where she also directs the Ph.D. program. She holds a Ph.D. in Environmental Science from UNC Chapel Hill and has over 20 years of experience in environmental health research. Her research examines environmental exposures in resource-limited settings, focusing on drinking water contamination impacts on child health and urban environmental hazards. International work includes a Fulbright award to Brazil where she leads study abroad programs. Current projects investigate extreme heat and radon exposure disparities in Atlanta using geospatial analysis. Research spans water quality interventions, diarrheal disease epidemiology, and urban health metrics. Recent articles demonstrate consistent focus on wastewater surveillance, environmental justice, and global water security. Publications show increasing emphasis on climate-related health impacts and diagnostic innovations. Awards: Fulbright Scholar Award to Brazil She teaches graduate courses in environmental health and global water issues, and leads field research programs in Brazil.

• Wireless Communications
• Signal Processing
• 6G Technology
• +4 more

Prof. Erik G. Larsson is a Professor and Head of the Division of Communication Systems at Linköping University's Department of Electrical Engineering (ISY). He joined LiU in 2007 after positions at KTH, University of Florida, and Ericsson Research. His research focuses on 6G wireless connectivity, distributed machine learning, and signal processing. He has authored over 200 journal papers and two textbooks, holds multiple patents, and serves on editorial boards for prestigious journals. Awards include IEEE Fellow, Royal Swedish Academy of Sciences membership, and the 2021 'golden carrot' teaching award. Education: Ph.D. from Uppsala University (2002). Visiting Fellow at Princeton University (2015). Research Interests: Wireless communications, network science, decentralized learning, and 6G technologies. Grants: Knut and Alice Wallenberg Foundation, SSF, ELLIIT, H2020 projects. Teaching: Courses include TSKS10 (Undergraduate), TSKS34 (Undergraduate), TSKS15 (Master), TSKS33 (Master). Students: Advised over 20 Ph.D. and Licentiate students, many now in academia and industry. Current advisees include Chung-Hsuan Hu and Ahmet Kaplan. Awards: Multiple IEEE prizes (e.g., Ellersick Prize, Fink Award) and recognition for leadership in signal processing and wireless research.

Ehsan MiandjiView profile

Assistant Professor

• Computer Graphics
• Computer Vision
• Machine Learning
• +4 more

Ehsan Miandji is an Assistant Professor and Docent at Linköping University's Department of Science and Technology (ITN), part of the Faculty of Science and Engineering. His research focuses on computer graphics, computer vision, and machine learning, with a particular emphasis on BRDF modeling, light field imaging, compressed sensing, and sparse representation techniques. He is affiliated with the Computer Graphics and Image Processing group and the Wallenberg Autonomous Systems Program (WASP). His work spans both theoretical advancements and applied methodologies in visual data processing. Recent research includes optimizing BRDF acquisition via FROST-BRDF, advancing multidimensional compressed sensing for spectral light fields, and developing sparse representation frameworks for bidirectional texture functions (BTF). Miandji collaborates with interdisciplinary teams within the Media and Information Technology (MIT) division, contributing to projects that bridge computational imaging, algorithm design, and real-world applications. His publications reflect a strong commitment to pushing boundaries in visual data compression, rendering efficiency, and perceptual quality assessment of material models.

• Gynecologic Cancer Research
• HPV Detection and Prevention
• Women's Health
• +3 more

Christer Borgfeldt is a Professor at Linköping University's Department of Biomedical and Clinical Sciences. His research focuses on gynecologic cancer, HPV detection, and healthcare quality improvement through data validation studies. He leads projects evaluating clinical registers and screening programs in Sweden and Ethiopia. Research interests include cervical cancer prevention, HPV epidemiology in low-screened populations, and improving diagnostic protocols for gynecological conditions. His work emphasizes clinical data integrity and global health equity.

• Algorithmic development
• Stochastic modelling
• Risk/reliability analysis
• +9 more

Dr. Tanmoy Chatterjee is a Lecturer in Resilient Design at the University of Surrey's School of Mechanical Engineering Sciences, affiliated with the Surrey Institute for People-Centred AI and the Institute for Sustainability. Previously, he was a postdoctoral researcher at Swansea University (2018–2022), funded by the EPSRC 'DigiTwin' grant. His research focuses on algorithmic development, stochastic modeling, and machine learning for structural systems, with applications in nonlinear dynamics, metamaterials, and energy harvesting. Education: PhD in Civil Engineering (2014–2018), Indian Institute of Technology Roorkee Masters in Structural Engineering (2011–2013) Key Research Areas: Resilient design of structures under uncertainty Data-driven discovery of nonlinear dynamics Metamaterials for wave propagation control Machine learning for uncertainty quantification Publications: Recent work includes stochastic model updating, Bayesian inference for aeroelastic systems, and PINN-based reliability analysis. His 2025 paper on nonlinear structural joints introduced a novel framework combining experimental data with deep learning. Awards: Recipient of CSIR and Ministry of Education scholarships for his master's and PhD. Supervision: Co-supervised PhD students James Smith (University of Surrey) and Pushpa Pandey (Swansea University). Open to exceptional candidates for funded PhD projects in AI-driven engineering and resilient design. Labs/Teams: Active in Surrey's Centre for Engineering Materials and collaborations with industry partners like Autodesk and UK Atomic Energy Authority.

Atif MansoorView profile

Lecturer

• Computer Vision
• Machine Learning
• IoT and Sensor Networks
• +4 more

Atif Mansoor is a Lecturer in Computer Science and Software Engineering at the University of Western Australia, affiliated with the School of Physics, Maths and Computing. He is also part of the Planning and Transport Research Centre within the School of Social Sciences. His research spans interdisciplinary areas including computer vision, machine learning, IoT systems, and probabilistic graphical models. Mansoor has supervised numerous graduate students, contributing to advancements in automated inference, infrastructure monitoring, and image quality assessment. Recent research focuses on parallel Bayesian network inference, IoT-based structural health monitoring, and remote sensing applications for agriculture. His work integrates machine learning with domain-specific challenges in healthcare, urban planning, and environmental science. Mansoor has collaborated on projects funded by initiatives like the iMove CRC, emphasizing practical solutions for infrastructure and transportation systems. His academic contributions include over 50 peer-reviewed publications and active participation in international conferences. Mansoor’s teaching and research reflect a commitment to innovation in computational methods and their societal applications.

Gavin GarnerView profile

Associate Professor

• Human Machine Interface
• Mechatronics
• Advanced Manufacturing
• +3 more

Gavin Garner is an Associate Professor at the University of Virginia's School of Engineering and Applied Science, Department of Mechanical & Aerospace Engineering. He joined the faculty in 2009 after completing his Ph.D. at UVA and working as a mechanical engineer at AMF Bowling Worldwide. His research focuses on mechatronics, human-machine interfaces, and biomedical engineering applications such as automated tissue fabrication. He advises UVA's ASME and Pi Tau Sigma student chapters. Education: Bachelor's in Physics from Colby College M.S. and Ph.D. in Mechanical & Aerospace Engineering from University of Virginia Research Highlights: Developed FEBE bioreactor systems for tissue engineering Advances in 3D-printed diagnostic devices and microfluidics Interdisciplinary education projects like guitar-building for mechatronics Recent work includes automated biofabrication systems for muscle repair and low-cost diagnostic tools. His 2018 Jefferson Scholars Foundation award supported innovative engineering research. Teaching emphasizes hands-on projects like mechatronics labs, autonomous quadcopters, and bio-manufacturing systems. Key Contributions: Over 15 patents and peer-reviewed publications Student projects include UVA's award-winning ASME competition teams Collaborations with medical researchers for tissue-engineered therapies

Annika BetkenView profile

Assistant Professor

• Long Range Mathematics
• Stochastic Volatility
• Simulation Study
• +3 more

Annika Betken is an Assistant Professor in Mathematics of Operations Research. Her research focuses on advanced statistical methodologies including long-range dependence analysis, stochastic volatility modeling, and machine learning applications. Notable contributions include work on two-sample tests using Wilcoxon rank sums and label shift adaptation in neural networks. She actively engages in academic discourse through conference presentations and publications. Her recent research explores classification scenarios using kernel logistic regression and depth pattern analysis in time series. Betken has delivered invited talks on topics like class probability matching and change-point detection in time series analysis. Her work has been featured in peer-reviewed conferences and journals, contributing to 65 citations and an h-index of 5 as of 2025. Betken has collaborated internationally and contributed to the NAW article in February 2022. Her research spans theoretical advancements in statistical testing and practical implementations in adaptive machine learning systems.

• Payment Systems
• Economic Analysis
• Financial Innovation
• +3 more

Angelika Welte is an Adjunct Professor in the Department of Mathematics and Statistics at the University of Ottawa's Faculty of Science. Her research focuses on payment systems, economic analysis, and financial innovation, with particular attention to consumer behavior and market dynamics in the context of digital and traditional payment methods. She has conducted extensive studies on merchant acceptance of cash, the impact of payment card pricing, and the adoption of financial technologies like mobile payments. Her work often leverages high-frequency transaction data and survey methodologies to analyze spending patterns during economic disruptions such as the COVID-19 pandemic. Key research themes include the regressive effects of payment card pricing on merchants, the untapped potential of mobile payments in Canada, and the dynamics of ATM card adoption in Italy. Dr. Welte has contributed to policy-relevant analyses through reports like the Bank of Canada's retailer surveys and the 2023 Merchant Acceptance Survey. Her interdisciplinary approach bridges economics, data science, and behavioral analysis to address questions of market efficiency and consumer welfare. Notable collaborations include studies on discounting strategies for payment steering and the cost structures of point-of-sale systems in Canada. Her work frequently appears in peer-reviewed journals and policy reports, emphasizing both quantitative rigor and real-world applicability. While no specific awards or grants are listed, her extensive publication record reflects sustained academic engagement with payment systems and economic behavior.