Find Academic Supervisors

• Urban Mobility
• Transportation Planning
• Climate Change Resilience
• +3 more

Mohammad Sharif is a Researcher at the Institute for Mobility and Urban Planning within the Department of Building Sciences at the University of Duisburg-Essen. His work integrates transportation engineering, climate science, and computational methods to address urban mobility challenges under climate change scenarios, with particular focus on infrastructure resilience and sustainable transport systems. His research spans urban mobility modeling, climate-resilient transport infrastructure, trajectory analytics, and AI-driven environmental prediction systems. Key interests include first/last-mile connectivity solutions, dust storm pathway forecasting, tropical cyclone trajectory prediction, and context-aware movement analysis. He develops hybrid machine learning frameworks that incorporate spatiotemporal data, geographic context, and fuzzy logic to solve complex transportation and environmental problems. Recent publications demonstrate a strong interdisciplinary trend, combining transportation engineering with atmospheric science and health informatics. His work frequently employs convolutional neural networks, ensemble learning, and context-aware systems to model phenomena ranging from urban road network resilience to asthma exposure risks. Collaborations with Ali Asghar Alesheikh and Dirk Wittowsky highlight his focus on practical climate adaptation tools. Dr. Sharif contributes to the "R2K-Klim+" project developing strategic decision support tools for climate change adaptation in the Rhine river basin. His office is located at Berliner Platz 6-8, Room WST-A.09.06 in Essen, with office hours by email arrangement.

Kashif MahmudView profile

Assistant Professor

• Remote Sensing
• Hydrogeology
• Terrestrial Carbon Cycle
• +12 more

Kashif Mahmud is an Assistant Professor at the Kimbell School of Geosciences, Midwestern State University, and an Adjunct Senior Lecturer at the School of Biological, Earth and Environmental Sciences, University of New South Wales. His research integrates remote sensing, hydrogeology, and carbon cycle dynamics, focusing on karst environments, groundwater recharge, and climate change impacts. Develops innovative methodologies using terrestrial LiDAR and drip loggers for subsurface hydrology studies Specializes in data assimilation for improving terrestrial biosphere model predictions Collaborates on international projects like the ARC-funded 'Caves and their stalagmites: linking climate to groundwater recharge' His lab engages in advanced geospatial projects, including the 'Texas as Art' initiative and NSF-funded GeoTech Center activities. Research areas span from cave hydrology to wildfire smoke impact analysis, with a strong emphasis on computational modeling and environmental sustainability. Recent publications highlight his expertise in: Stochastic modeling of karst aquifers with training image algorithms LiDAR-based biomass estimation for urban forests Climate change feedbacks in terrestrial carbon cycling Wildfire PM2.5 pollution dynamics using satellite data The lab's work has received recognition through student awards (AIPG Shoemaker Award, GSA Karst Division Grant) and collaborative grants like the $3,038,909 ARC project. He supervises graduate students in projects ranging from cave exploration with emerging technologies to spatiotemporal deforestation analysis, maintaining active fieldwork at sites like Natural Bridge Caverns, Texas.

• Digital Innovation Platforms
• Blockchain Technology
• Fintech
• +3 more

Ahmad Ghazawneh is a Senior Lecturer at the School of Information Technology , Halmstad University. His research explores the intersection of digital innovation platforms, blockchain technology, and fintech, emphasizing transformative impacts on financial systems and digital economies. Email: ahmad.ghazawneh@hh.se Research Focus: Dr. Ghazawneh investigates blockchain-based financial ecosystems, knowledge graph integration in healthcare, and platform dynamics across multiple domains including mobility systems and social media affordances. Scientific Trends: Recent publications demonstrate expertise in federated health data systems, token-based blockchain ecosystems, conversational AI for healthcare, and sustainable mobility platforms. His work bridges theoretical platform economics with practical implementations.

• Natural Language Processing
• Machine Learning
• Computational Linguistics
• +8 more

Marijn Schraagen is an Assistant Professor in Natural Language Processing at Utrecht University's Faculty of Science, specifically within the Information and Computing Sciences department. His academic work bridges computational linguistics with practical applications across multiple domains including healthcare, law, and cultural heritage. His research interests focus on the application of machine learning methods to large collections of text and speech data. Schraagen has developed expertise in Dutch language processing with specific applications in clinical settings, legal contexts, and historical language analysis. Notably, within the Goallab at the department of Social, Health and Organizational Psychology, he contributes to developing machine learning models for detecting and preventing low literacy among Dutch children. His publication record demonstrates consistent research activity from 2010 through 2025, with recent work showing particular strength in legal text analysis, clinical NLP applications, and historical language processing. His articles reveal a pattern of interdisciplinary collaboration, working with researchers from psychology, public health, law, and social sciences to address real-world problems through NLP solutions. Schraagen has received research funding from diverse sources including Anders AI Lab, NWO Ai-NEDXS, the National Police, and the Royal Library. His projects include developing AI tools for literacy detection, analyzing protest events in social media, and creating systems for processing historical Dutch texts. He teaches courses in computational thinking, knowledge-intensive process analysis, and methods in AI research, contributing to both the theoretical and practical education of students in the field of artificial intelligence and natural language processing.

• Aquaculture
• Mathematical Modeling
• Oceanography
• +2 more

Morten Omholt Alver is an Associate Professor at the Norwegian University of Science and Technology (NTNU), affiliated with the Department of Technical Cybernetics. His work primarily focuses on marine biocybernetics, integrating mathematical modeling, data assimilation, and oceanographic research to advance aquaculture and marine environmental monitoring. Deputy Head of Research at the Department of Technical Cybernetics Program advisor for the PhD program in Technical Cybernetics Research interests span aquaculture systems, oceanographic modeling, and adaptive robotic sampling. Recent work emphasizes digital twin technologies for aquaculture optimization and dissolved oxygen modeling in salmon farms. His methodological contributions include data assimilation techniques for skewed oceanic variables and multiscale simulations of aquaculture effluents. Publications highlight collaborations with interdisciplinary teams across Europe. Key projects involve precision fish farming frameworks, hyperspectral imaging, and environmental monitoring systems for marine industries. He also contributes to kelp cultivation automation and coastal ecosystem modeling.

Melissa HartView profile

Professor

• Urban Climatology
• Air Pollution
• Thermal Comfort
• +3 more

Professor Melissa Hart is a leading academic at the University of Tasmania serving as Associate Director- Training and Leadership . Her research focuses on the interplay between urban environments and climate systems , particularly urban heat islands, air pollution dynamics, and thermal comfort . Co-Chair, World Climate Research Programme Training Academy Past Chair, Australian Meteorological and Oceanographic Society Equity & Diversity Committee Participant, 2018 Homeward Bound Women in STEMM Initiative Her work leverages machine learning for urban temperature mapping and thermal comfort prediction , while also advancing large eddy simulation datasets for urban canopy layer turbulence. Notable scientific recognition includes the UNSW Vice-Chancellors Award for Higher Degree Research Leadership . She actively promotes gender equity in climate science through committee leadership and international initiatives.

Maninder Singh DhillonView profile

Researcher

• Agricultural remote sensing
• Crop yield modeling
• Land-use diversity
• +6 more

Dr. Maninder Singh Dhillon is a Postdoctoral Researcher at the Department of Remote Sensing, Institute of Geography and Geology, University of Wuerzburg (Germany). Since March 2024, he leads the 'Biodiversity' work package in the EO4CAM project, continuing his academic career at the same institution where he completed his PhD (2019-2023) with the thesis 'Potential of Remote Sensing in Modeling Long-Term Crop Yields'. His previous roles include scientific employee (2023-2024), PhD student (2019-2023), and research assistant (2018-2019) at the University of Wuerzburg's Remote Sensing Department. Education: M.Sc. in Earth Observation and Geoanalysis (EAGLE) from University of Wuerzburg (2016-2019), with thesis on crop growth models using synthetic remote sensing data Professional Experience: Internship at German Aerospace Center (DLR) in Neustrelitz (2018) and research assistant role at Punjab Remote Sensing Center (2015-2016) Dr. Dhillon's research focuses on agricultural remote sensing applications, particularly: Crop yield modeling through multi-sensor data fusion (MODIS, Landsat, Sentinel-2) Biodiversity analysis in agricultural ecosystems Land-use diversity impacts on crop biomass Climate variability and soil quality interactions Sustainable agriculture through precision farming technologies Carbon emissions assessment in groundwater irrigation systems His publication record (2018-present) shows expertise in: STARFM data fusion algorithms for NDVI time-series Machine learning integration with crop models Environmental monitoring of agroecosystems Water-energy-agriculture nexus analysis Phenological pattern detection in small-scale farming Multiscale biodiversity assessment frameworks

Iro ArmeniView profile

Assistant Professor

• Computer Vision
• 3D Scene Understanding
• Built Environment
• +5 more

Iro Armeni is an Assistant Professor in the Civil and Environmental Engineering Department at Stanford University's School of Engineering. She leads the Gradient Spaces research group, focusing on the intersection of civil engineering, architecture, and machine perception to design and construct data-driven environments across physical and digital space. Her educational background is highly interdisciplinary: PhD in Civil and Environmental Engineering with Minor in Computer Science from Stanford University (2020), Postdoctoral Researcher at ETH Zurich (2023), MSc in Computer Science from Ionian University (2013), MEng in Architectural Engineering from University of Tokyo (2011), and Diploma in Architectural Engineering from National Technical University of Athens (2009). Before academia, she worked as an architect and consultant for both private and public sectors. Dr. Armeni's research focuses on developing quantitative and data-driven methods that learn from real-world visual data to generate, predict, and simulate new or renewed built environments with humans at the center. She is particularly interested in creating gradient spaces that blend 100% physical (real reality) to 100% digital (virtual reality) using Mixed Reality. Her work spans computer vision, 3D scene understanding, semantic mapping, and their applications in the built environment. Her recent publications demonstrate significant contributions across multiple venues including CVPR, ECCV, SIGGRAPH, and ISPRS Journal, with research themes centered around 3D scene understanding, appearance transfer, scene synthesis, SLAM in dynamic environments, and semantic mapping. Her work shows a consistent trajectory toward creating sustainable, inclusive, and adaptive built environments that support current and future physical and digital needs. She has received prestigious awards including the ETH Zurich Postdoctoral Fellowship, Google PhD Fellowship, and MEXT Scholarship. Her teaching includes graduate courses such as Designing for Gradient Spaces (CEE342), Computer Vision for the Built Environment (CEE247C), and AI Applications in AEC (CEE329), reflecting her interdisciplinary approach to integrating machine perception with civil engineering applications.

Lee McIlreavyView profile

Lecturer

• Visual Perception
• Ophthalmology
• Optometry
• +3 more

Dr. Lee McIlreavy is a Lecturer at Cardiff University's School of Optometry and Vision Sciences , conducting fundamental research on visual function and motion perception linked to eye movements, particularly in neuro-ophthalmic conditions like infantile nystagmus. Their work investigates how pathological eye oscillations affect environmental perception and explores cortical organization through eye tracking and computer-based tasks. Research interests span Visual perception under normal and abnormal ocular development Objective eye tracking applications in clinical settings Quantitative analysis of smooth pursuit and saccadic eye movements Current projects include collaborations with Katherine Ward on nystagmus diagnostics and cortical organization studies. Recent publications focus on Standardizing eye tracking research methodologies (2024) Visual function assessment in infantile nystagmus (2024) Quantitative deficits in smooth pursuit accuracy (2022) Off-axis performance of eye tracking devices (2020) Key grants include funding from Fight for Sight/Nystagmus Network (2024, 2013) Cardiff University research programs (2016, 2015) IN-vision UK (2019) Contact: McIlreavyL@cardiff.ac.uk | +44 29208 70134

Joan CordinerView profile

Professor

• Process Engineering
• Process Safety
• Hydrogen Safety
• +7 more

Professor Joan Cordiner serves as Head of the School of Chemical, Materials and Biological Engineering at the University of Sheffield, a position she assumed in 2021 after joining the department as Professor of Process Engineering and External Engagement in 2020. With a distinguished career at Syngenta spanning global and senior management roles, she brings extensive expertise in leadership, process design, complex modeling, and industry-academia collaboration to her academic leadership. Her research focuses on revolutionizing process efficiency and safety through cutting-edge modeling technologies. The Cordiner Group develops innovative mechanistic and data-driven models to address critical challenges in predictive maintenance, mRNA vaccine production, decarbonization strategies, hydrogen safety, and process resilience. Their work bridges academia and industry, exemplified by the spin-out company Kausalyze which transforms research into practical predictive maintenance solutions for manufacturers. Professor Cordiner's publications reveal a strategic research evolution toward integrating artificial intelligence with chemical engineering fundamentals to solve emerging industrial challenges. Recent work demonstrates increasing focus on hydrogen safety infrastructure, mRNA production technologies, and resilience assessment methodologies - all critical areas for the global transition to net-zero industrial processes. Her exceptional contributions have earned recognition through prestigious fellowships: Fellow of the Royal Academy of Engineering (FREng) Fellow of the Royal Society of Edinburgh (FRSE) Fellow of the Institute of Chemical Engineers (FIChemE) Fellow of the American Institute of Chemical Engineers (FAIChE) Chartered Engineer (CEng) Professor Cordiner has secured substantial research funding including current grants from Wellcome Leap for RNA production technology and EPSRC for sustainable microwave manufacturing. She actively serves on influential committees including the Royal Academy Policy committee and National Engineering Policy Centre, where she shapes national engineering policy. Her group maintains strategic partnerships with the UK HyRES Hub for Hydrogen research, the Vax Hub for vaccine development, and critical materials initiatives supporting net-zero technologies. The Cordiner Group operates at the vital intersection of academia and industry, with their 'Breaking down barriers' initiative featured in Nature highlighting their commitment to strengthening collaborative research models. Their work directly addresses industrial challenges while advancing fundamental engineering knowledge, creating a powerful feedback loop between theoretical innovation and practical application.

Jon ViventiView profile

Associate Professor

• Biomedical Engineering
• Neuroscience
• Flexible Electronics
• +3 more

Jon Viventi is the Hawkins Family Associate Professor of Biomedical Engineering at Duke University. He holds secondary appointments as Assistant Professor in Neurosurgery and Assistant Professor of Neurobiology , and is a Faculty Network Member of the Duke Institute for Brain Sciences . His research focuses on developing flexible electronics for high-resolution neural interfaces, with applications in diagnosing/treating epilepsy and advancing brain-machine interfaces . Research Interests Dr. Viventi's work combines flexible electronics and high-density neural recording to address clinical challenges. His innovations include µECoG arrays for cortical mapping, low-power neural interfaces , and bioresorbable devices . Collaborations span neurology, neurosurgery, and materials science , with industrial partnerships yielding five patents. Scientific Recognition MIT Technology Review Innovators Under 35 (2014) Popular Science Brilliant 10 (2014) Publications Recent work includes high-density µECoG arrays for stroke monitoring (2024), artifact-free neural interfaces (2019), and foundational flexible electronics for neurophysiological mapping (2011). Articles appear in Nature Neuroscience , Science Translational Medicine , and Nature Materials .

• Maritime Traffic Analysis
• Data-Driven Modeling
• Geospatial Data Processing
• +3 more

Búgvi Benjamin Magnussen is a PhD Fellow at the Department of People and Technology , Roskilde University, Denmark. His research focuses on data-driven modeling and analysis of maritime traffic systems, leveraging Automatic Identification System (AIS) data for network construction and route generation. Email: magnussen@ruc.dk Phone: +45 4674 3080 Research Trends : His recent work explores maritime traffic network modeling, trajectory interpolation techniques, and environment-adaptive algorithms for realistic route generation. Key themes include spatiotemporal data analysis and applications of machine learning to maritime domains. Notable publications include contributions to Transportation Research Part C: Emerging Technologies (2024) and the ACM International Conference Proceeding Series (2023).

• Environmental Science
• Marine Science
• Biogeochemistry
• +5 more

Dr. Neven Cukrov is an Associate Professor and Scientific Advisor at the Ruđer Bošković Institute in Zagreb, Croatia, where he works in the Division for Marine and Environmental Research within the Laboratory for physical chemistry of traces. His research focuses on environmental and marine sciences with particular emphasis on biogeochemistry of metals in water systems, anchialine ecosystems, and anthropogenic influences on sedimentation processes. Dr. Cukrov earned his PhD in geosciences with a focus on geology from the Krka River Estuary research, completed his M.Sc. in Brazil at the Universidade de Brasília, and holds a B.Sc. in Cretaceous Carbonate Lithofacies and Tectonics from the Faculty of Natural Science in Zagreb. His educational background includes specialized courses in GIS (ArcView, ArcInfo) and remote sensing (ENVI). His research interests span environmental science, marine science, biogeochemistry of metals in water systems, anchialine ecosystems, anthropogenic influences on sedimentation and tufa precipitation, underwater sampling development, and natural and anthropogenic radionuclides in recent sediments. Dr. Cukrov's work bridges geology, hydrology, and environmental chemistry with a strong focus on Croatian karst systems, particularly the Krka River estuary. Analysis of Dr. Cukrov's recent publications (2023-2025) reveals a strong focus on environmental monitoring of coastal and karst systems, with particular attention to metal contamination, microbial communities in anchialine caves, atmospheric deposition of radionuclides, and advanced techniques for marine monitoring including sonar and ROV technologies. His research demonstrates interdisciplinary approaches combining geochemistry, microbiology, and advanced monitoring techniques to address environmental challenges in the Adriatic region. Dr. Cukrov actively collaborates with researchers across multiple institutions and countries, contributing to numerous international projects focused on environmental monitoring, marine pollution, and karst hydrology. His work has significant implications for environmental protection and sustainable management of coastal resources in the Adriatic region. His laboratory work focuses on physical chemistry of trace elements in marine and freshwater systems, with particular expertise in the unique anchialine cave ecosystems found along the Croatian coast. Dr. Cukrov's research group employs both traditional sampling methods and cutting-edge technologies for environmental monitoring in these complex hydrological systems.

• Topological Photonics
• Photonic Crystals
• Semiconductor Lasers
• +5 more

Dr. Sang Soon Oh is a Lecturer at the School of Physics and Astronomy, Cardiff University, and a Sêr Cymru II Rising Star Fellow (2017-2023) funded by the Welsh government. His research spans theoretical and experimental aspects of topological photonics , photonic crystals , semiconductor lasers , and chiral metamaterials , with a focus on graphene-based systems and quantum emitters . Education: PhD in Physics from KAIST (2007), with a research visit at the University of St Andrews (2004-2005). Postdoctoral: ETRI (2007-2010), University of Surrey (2010), Imperial College London (2010-2017). His research interests center on: Topological protection mechanisms in photonic systems Non-Hermitian and non-linear photonic dynamics Quantum dot and nanowire laser integration Chiral and plasmonic light-matter interactions Selected publication trends reveal: Advances in nonlinear topological photonics (2025) Non-Abelian nodal line physics in photonic and mechanical systems (2024-2022) Graphene plasmonics and 2D material applications (2024) Machine learning for topological phase diagram analysis (2023) Scientific recognition: Sêr Cymru II Rising Star Fellowship (£983K) Outstanding reviewer for Light: Science & Applications (2022, 2023) Supervision includes: Current PhD students: Ghada Alharbi (optical bistability), Kyle Netherwood (quantum filtering), Ion Wood-Thanan (aperiodic materials) Former PhD students: Stephan Wong (topological lasing), Zeeshan Ahmad (graphene plasmonics), Joe Mahoney (quantum dot modulators), Shaikhah Almousa (resonator theory) Collaborative supervision of Jan Olthaus (Münster University) and 3 external PhD examining roles

• Human Developmental Biology
• Genomics
• Single-cell RNA Sequencing
• +6 more

Dr. Steven Lisgo is a developmental biologist and genomics researcher affiliated with Newcastle University . His research focuses on human embryonic and fetal development, with a strong emphasis on using single-cell RNA sequencing and spatial transcriptomics to map cellular and molecular processes across organs such as the brain, heart, skin, liver, and immune system. Research Interests: Human developmental biology and embryogenesis Single-cell genomics and transcriptomics Neurodevelopment and cerebellar morphogenesis Immune system ontogeny and organogenesis Congenital malformations and genetic disorders Comparative developmental genomics across mammalian species His recent publications (2020–2025) reflect a consistent trend toward creating comprehensive cell atlases of developing human organs, integrating multi-omics approaches to understand gene expression, cellular identity, and developmental trajectories. These studies often involve large-scale collaborations and utilize resources like the Human Developmental Biology Resource (HDBR) . Scientific Contributions & Collaborations: Dr. Lisgo has co-authored numerous high-impact studies with collaborators such as Susan Lindsay , Rachel Botting , and Emily Stephenson , indicating his role in both research leadership and data generation. His work has contributed to understanding developmental disorders like holoprosencephaly, Down syndrome, and congenital heart defects. Labs & Resources: He is closely associated with the Human Developmental Biology Resource (HDBR) , a UK-based initiative that provides human embryonic and fetal tissues for research, and is likely involved in managing or utilizing this resource for his studies.