Find Academic Supervisors

• Horticulture
• Agricultural Sciences
• Greenhouse Cultivation
• +5 more

Monique Bijlaard is a Researcher at Wageningen University & Research specializing in sustainable greenhouse horticulture. Her work integrates engineering, data science, and crop physiology to develop energy-efficient cultivation systems, with active projects through 2026 focusing on resource optimization and technological innovation in agricultural production. Her research spans critical areas of modern horticulture: Greenhouse automation using sensor networks and AI-driven decision systems Energy reduction via low-e glass/screens and optimized lighting spectra Irrigation management and plant density optimization for diverse crops Computer vision applications for real-time crop monitoring Sustainable production of tomatoes, berries, courgettes, and ornamentals This multidisciplinary approach addresses climate challenges while maintaining productivity. Recent publications demonstrate leadership in autonomous greenhouse challenges and emission-free growing systems. Her work on dwarf tomato cultivation showcases multi-sensor feedback algorithms, while BEST-kas studies prove 20%+ energy savings in courgette/berry production. Spathiphyllum research reveals how light spectra manipulation enables carbon-neutral cultivation, establishing clear trends toward technology-driven resource efficiency across all crop systems. Monique leads two major LVVN-funded projects: 'Vergelijking low-ɛ glas en low-ɛ schermen' (2025-2026) quantifying energy savings from advanced glazing materials, and 'Zomerteelt in de WinterlichtKas' (2021-2022) developing CO 2 -limited summer cultivation protocols. These initiatives translate academic research into practical industry solutions for energy-intensive horticulture. She collaborates extensively with Fieldlab Vertical Farming partners including Delphy Improvement Centre, Logiqs, Vertify, and Philips Horticulture LED Solutions. Her work within Wageningen's Greenhouse Horticulture business unit ensures direct industry implementation through demonstration facilities and joint cultivation trials across the Netherlands.

Steef KoningsView profile

Researcher

• Health Economics
• Mental Health
• Schizophrenia
• +4 more

Steef Konings is a postdoctoral researcher at the University of Groningen , affiliated with the Faculty of Science and Engineering and the PharmacoTherapy, Epidemiology and Economics department. His research focuses on health economic modeling in mental healthcare and public health interventions. Research Interests include: Cost-effectiveness analysis in psychosis treatment Economic modeling of schizophrenia and mental disorders Vaccine safety and reactogenicity evaluations Public health policy through tax interventions Chronic disease management (diabetes) Population health metrics Contact : s.r.konings@umcg.nl

• Visual Learning Analytics
• Educational Technology
• Machine Learning
• +3 more

Zeynab Mohseni is a researcher at Linnaeus University , affiliated with the Department of Computer and Information Sciences. Her work focuses on Visual Learning Analytics (VLA) tools for teachers, enabling data-driven decision-making and improved student learning trajectories. She is a member of the EdTechLnu research group and the Computational Social Sciences team, contributing to educational technology innovation and digital transformation in K-12 and higher education.

• Internet of Things
• Open Source Software
• Program Comprehension
• +6 more

Simon Butler is a Senior Lecturer in the Department of Information Technology at the University of Skövde's School of Informatics. He is an active member of the Distributed Real-Time Systems research group and contributes significantly to undergraduate computer science education. His academic work bridges theoretical research with practical industry applications in software development. Butler's research interests center on the challenges software developers face in creating and maintaining software systems, with particular focus on program comprehension, software maintenance, and the socio-technical and educational aspects of software development in hybrid environments where open source and proprietary solutions coexist. His work addresses critical issues in Internet of Things (IoT) systems and the practical implementation of open source software solutions in industrial contexts. His publication record from 2018-2023 reveals a strong research trajectory focused on open source software adoption, interoperability challenges, and standardization processes. His work spans diverse venues including Software Quality Journal, Journal of Systems and Software, IEEE Transactions on Software Engineering, and OpenSym proceedings, demonstrating both academic rigor and practical relevance to industry challenges. Butler is actively involved in several significant research projects including SUDO (2020-2024) addressing lock-in effects in IT systems, OSSD (2021-2023) developing educational programs for sustainable digitalization, and LIM-IT (2016-2020) investigating interoperability and long-term maintenance challenges. His teaching portfolio includes core computer science subjects such as Operating Systems, Object Oriented Programming, Algorithms and Data Structures, and Distributed Systems. As a member of the Distributed Real-Time Systems research group, Butler collaborates with industry partners to address real-world challenges in software development practices, particularly focusing on how organizations can effectively integrate open source solutions while avoiding problematic lock-in effects that compromise long-term system sustainability.

Johanna IhalainenView profile

Senior Lecturer

• Sports Physiology
• Female Athlete Health
• Hormonal Contraception in Sports
• +3 more

Johanna Ihalainen is a Senior Lecturer at the Faculty of Sport and Health Sciences , University of Jyväskylä. Her work focuses on the intersection of sports physiology and female athlete health, with particular emphasis on hormonal influences on performance and recovery. Co-leader of the FemInnovation research group Collaborator in interdisciplinary projects like MENSA and i3-INSHAPE Key contributor to understanding hormonal contraceptive effects on athletic adaptation Research interests center on female physiology , endurance training , environmental adaptations , and technology-driven sports innovations . Current projects examine hormonal impacts on cortico-reticular motor function and sedentary lifestyle interventions via digital tools. Her publications span topics including mental health interventions , infrared sauna recovery , menstrual cycle effects , and exercise-induced inflammation in female athletes. She employs rigorous methodologies like randomized controlled trials and longitudinal analyses. Research group affiliations include: Sound Science Lab (music-brain interactions) WellbeingDataLab (synthetic exercise data) BRAIN-BALANCE (aging and balance training)

Ihor SmalView profile

Assistant Professor

• Image Analysis
• Smart Microscopy
• Artificial Intelligence
• +7 more

Ihor Smal is an Assistant Professor at the Department of Biology, Faculty of Science, Utrecht University. He has held previous positions at Erasmus MC (2009-2018) and TU Delft (2019-2020). His research bridges statistical image processing, smart microscopy, and explainable AI for biological motion analysis, with applications in automated real-time imaging systems. Education: M.Sc. in Physics and Electrical Engineering, Ivan Franko National University of Lviv (1999, cum laude) Professional Doctorate in Engineering (PDEng), Eindhoven University of Technology (2005) PhD in Biomedical Imaging, Erasmus University/MC (2009) His work focuses on developing AI-driven solutions for motion registration, particle tracking, and image understanding in biological systems. He leads the NWO IMAGINE! program's Tech Work Package 2, aiming to automate imaging experiments using explainable AI. The 15 most recent publications highlight his contributions to deep learning for CT segmentation, particle tracking, diffusive state modeling, and real-time imaging optimization. Key subfields include neural networks, biomedical signal processing, and automated microscopy. Scientific Awards: VENI grant Erasmus MC Fellowship NWO BBoL grant Students: Vincent Hellebrekers Daan te Rietmole His lab at Utrecht University, accessible via www.smal.ws, collaborates with institutions like Erasmus MC and TU Delft, leveraging facilities such as the Utrecht Biology Imaging Center.

Johan RochelView profile

Researcher

• Law and Ethics of Digital Technologies
• International and European Law
• Migration Law
• +3 more

Dr Johan Rochel is a legal scholar and ethicist based at the University of Zurich , jointly affiliated with the Faculty of Law and the Center for Ethics . He is an active member of the university-wide Digital Society Initiative (DSI) , where he contributes to the DSI Community on AI & Law among others. Trained in law, political philosophy and ethics , his academic work interrogates questions of justice in international and European law, and probes the ethical and legal challenges posed by emerging digital technologies. Research Interests Rochel’s research agenda is interdisciplinary, spanning: Ethics and governance of AI and robotics – algorithmic accountability, transparency, and rights-based oversight. Digital rights and digital integrity – conceptualising new human rights for the digital age. Innovation ethics and responsible innovation – integrating ethical foresight into technology design and policy. Migration law and theory – republican non-domination, fairness in immigration policy, and normative foundations of border regimes. International intellectual property law – legitimacy, development, and access to knowledge. Across these themes he combines doctrinal legal analysis with normative political philosophy to craft actionable policy blueprints. Publication Trends Between 2020 and 2025 Rochel has produced an intensive stream of peer-reviewed articles that converge on two broad trajectories: first, embedding ethical reasoning into hard and soft law instruments governing digital technologies, and second, re-imagining migration governance through republican lenses. His work increasingly links abstract theory with concrete regulatory proposals, reflecting a commitment to applied legal theory. Scientific Awards & Distinctions No specific awards are listed in the provided material. Advising & Grant Activity No named students or detailed grant information are provided in the text. Laboratory / Research Teams Rochel is associated with the Digital Society Initiative (DSI) at UZH, a cross-faculty network fostering interdisciplinary research on digital transformation. Within DSI he contributes to the AI & Law community, collaborating with scholars from law, computer science, political science and philosophy.

Suzanne AckerleyView profile

Research Fellow

• Stroke Rehabilitation
• Telerehabilitation
• Neurorehabilitation
• +3 more

Dr. Suzanne Ackerley serves as a Research Fellow at Lancaster Medical School, Lancaster University, specializing in stroke rehabilitation and telerehabilitation innovation. Her work focuses on developing and implementing evidence-based rehabilitation protocols through the NeuroRehabilitation OnLine (NROL) platform. Her research interests center on stroke rehabilitation optimization , with particular emphasis on telerehabilitation implementation, biomarker validation for recovery prediction, and increasing rehabilitation intensity through innovative service models. A key focus is the development and regional implementation of the NROL system for multidisciplinary group-based neurorehabilitation. Dr. Ackerley's recent publications (2023-2025) demonstrate consistent focus on stroke rehabilitation service delivery, with major themes including: implementation of group-based telerehabilitation during and post-pandemic, validation of the PREP2 algorithm for predicting upper limb recovery, and national surveys examining variations in stroke care pathways. Her work bridges clinical practice with implementation science. Scientific recognition includes: NHS England Chief Allied Health Professions Officer Awards, Digital Practice Award (Short-listed) Dr. Ackerley holds an active NIHR Senior Clinical and Practitioner Research Award (SCPRA) project titled 'R2_S Ackerley' running from May 2025 to April 2027. She participates in the 'Interdisciplinary network in culture, health, ethics and society' research group and has delivered invited talks on NROL implementation for the NHS England Chief Allied Health Professions Officer. Her work operates at the intersection of clinical neuroscience, rehabilitation engineering, and healthcare service delivery, with strong emphasis on translating research into practical clinical applications through robust implementation frameworks.

• Time Series Analysis
• Deep Learning
• Data-Intensive Systems
• +6 more

Tomasz Wiktorski is a Professor at the Faculty of Science and Technology , University of Stavanger , where he serves as Study Program Manager for MSc and PhD programs in Computer Science and Data Science. His research integrates conventional time series analysis with deep learning for applications in biomedical data (e.g., wearable devices), oil and gas drilling automation, energy systems prediction, and cloud infrastructure optimization. Education : Not explicitly detailed in the text. Research interests span data-intensive system modeling, focusing on: Biomedical time series analysis (wearables, ECG signal correction) Drilling process optimization via transfer learning and temporal models Energy systems prediction using machine learning Cloud infrastructure monitoring Curriculum development in data science education Scientific trends reveal expertise in recurrent neural networks, support vector machines, and hybrid data modeling for sensor networks across domains like health, petroleum, and cloud computing. Leadership includes designing data science programs and contributing to the EDISON Data Science Framework for global standards.

• Critical Care Medicine
• Cardiac Anesthesiology
• Perioperative Echocardiography
• +3 more

Caroline M. Ruminski, MD is a Clinical Assistant Professor in the Department of Anesthesiology specializing in perioperative transesophageal echocardiography and critical care medicine. Her clinical expertise bridges cardiac anesthesia and intensive care unit management. Her educational background includes: B.S. in Biology: Physiology & Neurobiology from the University of Maryland M.D. from the University of Virginia School of Medicine Internship, Residency (serving as Chief Resident), and Fellowship in Anesthesia Critical Care Medicine at Vanderbilt University Medical Center Dr. Ruminski's research integrates clinical anesthesiology with data science, focusing on cardiac complications in critically ill patients, post-traumatic pain management, and predictive analytics for cardiorespiratory monitoring. Her work addresses critical gaps in ICU outcomes through innovative applications of continuous monitoring systems and longitudinal outcome analysis. Her 2017-2019 publications reveal consistent investigation into critical care complications, demonstrating expertise in atrial fibrillation management, trauma-related opioid prescribing patterns, and machine learning applications for ICU monitoring. These studies collectively emphasize improving patient safety through evidence-based interventions in high-acuity surgical and trauma settings.

• Databases
• Information Systems
• Data Management
• +3 more

Dr. Mahdi Esmailoghli serves as a Researcher at the Institute of Computer Science within Humboldt University of Berlin's Faculty of Mathematics and Natural Sciences. His academic appointment focuses on advancing research in database technologies and information systems, contributing to both theoretical frameworks and practical implementations in data-intensive domains. His research spans Databases, Information Systems, Data Management, Database Systems, Information Retrieval, and broader Computer Science disciplines. Dr. Esmailoghli addresses critical challenges in data storage optimization, query processing efficiency, and scalable system architecture design, with particular emphasis on modern information management solutions. His work integrates theoretical rigor with real-world applications to enhance data accessibility and system performance.

Ian FosterView profile

Professor

• Distributed Computing
• Parallel Computing
• Data-Intensive Computing
• +7 more

Dr. Ian Foster serves as Senior Scientist and Distinguished Fellow at Argonne National Laboratory, directing the Data Science and Learning Division, while holding the Arthur Holly Compton Distinguished Service Professorship in Computer Science at the University of Chicago. His career bridges foundational computing research with transformative scientific applications. Education: BSc in Computer Science, University of Canterbury, New Zealand PhD in Computer Science, Imperial College, United Kingdom Foster pioneers distributed and data-intensive computing systems that enable breakthroughs in materials science, climate modeling, and biomedicine. His research develops tools for high-performance networking integration, parallel algorithms, and scalable data management, exemplified by the Globus platform which has processed over one exabyte of research data. Current initiatives include AI-driven scientific discovery frameworks like the NSF-funded $3.5M AI Model Gardens project. His exceptional contributions are recognized through: 2023 IEEE Internet Award for global impact on networked systems 2022 ACM/IEEE Ken Kennedy Award for parallel computing leadership 2019 IEEE-CS Charles Babbage Award for distributed systems innovation Fellowships in AAAS, ACM, BCS, and IEEE 30+ major awards spanning four decades Foster leads Globus Labs and the University's Systems Group, mentoring next-generation researchers through Argonne collaborations. His work continues to shape national research infrastructure with active NSF and DOE funding supporting next-generation data ecosystems.

Fruzsina AgocsView profile

Assistant Professor

• Scientific Computing
• Numerical Analysis
• Computational Physics
• +4 more

Fruzsina Agocs is an Assistant Professor in Computer Science at the University of Colorado, Boulder. Her research focuses on scientific computing, numerical analysis, and computational physics, particularly developing high-order numerical methods for ODEs/PDEs and early-universe physics. Previously, she was a research fellow at the Flatiron Institute's Center for Computational Mathematics and earned her PhD in cosmology from the University of Cambridge under advisors Anthony Lasenby, Mike Hobson, and Will Handley. She holds an MSci + BA in Physics. Research Highlights: Developed adaptive spectral solvers for oscillatory ODEs (e.g., riccati and oscode libraries). Advanced methods for scattering from periodic boundaries using integral equations. Investigated quantum initial conditions in curved spacetimes for inflationary cosmology. Explored computationally intensive models of closed universes and kinetic dominance in cosmology. Education: PhD in Cosmology, University of Cambridge (2021). MSci + BA in Physics, University of Cambridge. Software Contributions: Lead developer of riccati (adaptive oscillatory ODE solver). Core contributor to GAMBIT , a particle physics/cosmology collaboration tool. Outreach: Volunteer with NYC Audubon's Project Safe Flight to reduce bird-window collisions. Public science talks and articles on topics like meteor showers (in Hungarian).

Per Steinar HalvorsenView profile

Professor

• Cardiovascular Engineering
• Medical Device Development
• Critical Care Medicine
• +3 more

Per Steinar Halvorsen is a Professor at the University of Oslo, affiliated with the Division of Technology and Innovation and Oslo University Hospital (Rikshospitalet). His primary focus is on cardiovascular engineering and medical technology innovation, with an emphasis on developing advanced monitoring systems for critical care and cardiac applications. His work integrates biomedical engineering principles with clinical practice to address challenges in ECMO, left ventricular assist devices (LVADs), and real-time cardiac monitoring. Research Interests: Halvorsen’s research spans accelerometer-based cardiovascular monitoring, thrombosis detection in extracorporeal systems, and the application of machine learning in medical diagnostics. His studies often utilize porcine models to validate novel sensor technologies and device functionalities. He has contributed to advancements in non-invasive waveform analysis for emergency triage and therapeutic hypothermia protocols. Key Research Trends: His articles emphasize innovations in medical device design, particularly accelerometers for continuous cardiac monitoring. Recent work includes deep learning applications for valve event detection and vibration analysis for LVAD thrombosis. Collaborations with engineering teams (e.g., MEMS sensor development) highlight his interdisciplinary approach. Labs/Teams: He is part of the Clinical and Experimental Cardiovascular Monitoring research group, focusing on translational research between engineering and clinical cardiology.

Keith VanderlindeView profile

Associate Professor

• Cosmology
• Radio Astronomy
• Instrumentation Development
• +3 more

Keith Vanderlinde is an Associate Professor at the David A. Dunlap Department of Astronomy & Astrophysics and the Dunlap Institute at the University of Toronto. His research focuses on cosmology and long-wavelength instrumentation, particularly large-scale structure studies and the expansion history of the universe. He leads projects like CHIME/FRB, CHORD, and HIRAX, developing radio telescopes to detect fast radio bursts (FRBs) and map cosmic evolution. Education: PhD in Physics (University of Chicago, 2008); BS in Physics with EE (MIT, 2002). Awards include CIfAR Junior Fellow (2011-2012) and McGill Trottier Fellow (2009-2011). Research interests span cosmological instrumentation, dark energy probes, and transient astronomy. Key projects include the CHIME radio telescope (studying 21cm emission and FRBs), the CHORD observatory, and international collaborations like HIRAX in South Africa. His work emphasizes instrument design, data analysis pipelines like kotekan, and multi-messenger astronomy. Lab involvement includes the Algonquin Radio Observatory and contributions to SPT-3G. Active in graduate/undergraduate training, mentoring students in cosmology and radio instrumentation.