Marika Edoff is a Professor in Solid State Electronics specializing in solar cells at Uppsala University. She leads the Thin Film Solar Cell group at the Ångström Solar Center and has held a 50% pro-dean appointment (2014-2018). Her research focuses on Cu(In,Ga)Se2 (CIGS)-based thin film solar cells, including physical deposition methods, alkali-metal doping, and nanostructured passivation strategies. Education : PhD in Solid State Electronics (KTH 1997), Master in Electrical Engineering (KTH 1990) Professional Experience : Full Professor (2012-), Senior Lecturer (2006-2012), Spin-off company founder (Solibro AB) Recent publications highlight her work on rear contact passivation , light management architectures , and wide-gap CIGS solar cells with efficiency breakthroughs (23.6%). Collaborations span institutions in Belgium, Portugal, France, and Slovenia. Scientific Awards : Member, Swedish Research Council Board (2019-2024) Project Leader, EU Horizon Projects (ARCIGS-M, SITA) Coordinator, Ångström Thin Film Solar Center She supervises PhD students including Dorothea Ledinek and Olivier Donzel-Gargand , and has contributed to thermally integrated PV-water splitting and industrial-scale CIGS module development .
Carlos Salomon Gallo is a Professor and NHMRC Investigator Fellow (EL2) at The University of Queensland's Centre for Clinical Research, affiliated with the School of Biomedical Sciences. He directs the Centre for Extracellular Vesicle Nanomedicine and leads the Exosome Biology Laboratory. A globally recognized key opinion leader in extracellular vesicles (ranked 3rd worldwide by Expertscape), his research focuses on EV biology for diagnostic and therapeutic applications in ovarian cancer, gestational diabetes, preeclampsia, and other obstetrical syndromes. His research integrates proteomics (SWATH-MS), miRNA analysis, and advanced isolation techniques to develop liquid biopsies. Core interests include: EV biomarker discovery and validation for early disease detection. Mechanisms of EV-mediated signaling in metabolic and oncological pathologies. Engineering EVs for targeted drug delivery and CRISPR-Cas therapeutics. Clinical translation of EV-based diagnostics (IVDs) and therapeutics. Analysis of his recent articles reveals a dominant focus on EV profiling in pregnancy complications (gestational diabetes, preeclampsia) and oncology (ovarian cancer), utilizing multi-omics approaches. Key trends include developing high-sensitivity EV biosensors, understanding hypoxia-induced EV signaling, and exploring 3D models for EV research. He has received significant recognition, including: NHMRC Emerging Leadership Fellow NHMRC Investigator Fellow (EL2) He leads the Exosome Biology Laboratory and the UQ Centre for Extracellular Vesicle Nanomedicine, fostering cross-disciplinary collaboration. His work involves extensive national and international partnerships, evidenced by leadership roles in the Centre for Clinical Diagnostics and over 20 invited international talks in 5 years. He actively mentors HDR students and contributes to global EV research standards (MISEV2023).
Olga G. Troyanskaya is a Professor of Computer Science and the Lewis-Sigler Institute for Integrative Genomics at Princeton University. She serves as Deputy Director for Genomics at the Simons Center for Data Analysis, Simons Foundation, NYC. Her research focuses on computational biology, integrating diverse high-throughput genomic datasets to model molecular pathways in health and disease. Professor of Computer Science and Lewis-Sigler Institute for Integrative Genomics Deputy Director for Genomics, Simons Center for Data Analysis Research Interests: Troyanskaya’s work addresses challenges in bioinformatics, including algorithm development for gene expression analysis, regulatory network modeling, and disease mechanism interpretation. She combines computational methods with experimental validation using S. cerevisiae as a model organism. Scientific Trends: Recent publications emphasize single-cell multiomics, deep learning for transcriptional regulation, cancer immunotherapy design, and epigenomic analysis of immune responses. Key themes include computational modeling of genetic networks, disease-specific pathway analysis, and high-resolution omics frameworks. Collaborative roles in autism, Alzheimer’s, kidney disease, and cancer research Developed tools like HumanBase for data-driven predictions
George Vasilakopoulos is a Professor in the Department of Digital Systems at the University of Piraeus , where he also serves as Vice-Chancellor for Academic Affairs and Personnel. By law, he is President of the Quality Assurance Unit (MODIP) and the Employment and Career Structure (DASTA) of the university, overseeing the development of modern information systems. He earned his PhD from the University of London and has held leadership roles including Department President, Director of Postgraduate Programs, and Scientific Director of the Digital Health Services Laboratory. PhD: University of London Current Roles: Vice-Chancellor, Department of Digital Systems Professor Labs: Digital Health Services Laboratory His research focuses on Health Informatics , Cloud Computing , and Medical Data Security , with key contributions to: Emergency healthcare process automation Privacy-preserving personal health record systems Context-aware authorization models Cloud-based medical service frameworks Machine learning in clinical data analysis Interoperable health information systems The trends in his 15 most recent articles (2010-2015) reveal a consistent emphasis on integrating cloud infrastructure , semantic technologies , and mobile platforms to enhance emergency care, chronic disease management, and patient data security. His work bridges biomedical engineering , software architecture , and public health policy . He has held advisory roles for the Minister of Health on IT issues, served on hospital boards, and contributed to national committees for healthcare technology standards. His professional activities include project evaluation for Greek and European research programs and authoring three books on health informatics.
Jerome Hastings is a Research Professor at the Photon Science Directorate , Stanford University, and a Principal Investigator at the Stanford PULSE Institute. He is affiliated with the SLAC National Accelerator Laboratory and holds the academic rank of Research Professor (A.R.). His research focuses on advanced X-ray scattering techniques, femtosecond laser interactions, and high-energy-density material physics. Currently on leave from June 15, 2025, to September 15, 2025, Hastings has taught courses such as Advanced Topics in X-ray Scattering (APPPHYS 322) and Principles of X-ray Scattering (APPPHYS 222, PHOTON 222). Teaching : 2025-26: Advanced Topics in X-ray Scattering (Spr), Principles of X-ray Scattering (Win), Directed Studies (Aut/Wi/Spr), Research (Aut/Wi/Spr) Prior courses (2024-25, 2023-24) include similar offerings. Research Interests : His work explores the intersection of photon science and material dynamics, utilizing free-electron lasers to probe ultrafast structural changes, phonon hardening, and electronic responses in materials under extreme conditions. Key areas include X-ray diffraction , time-resolved spectroscopy , and high-intensity X-ray interactions . Publications : Hastings has contributed to 47 publications, with recent studies (2024) on supercooled liquid hydrogen crystallization and phonon hardening in laser-excited gold. Earlier works (2019-2016) address X-ray split-delay systems, photodissociation dynamics, and anomalous Compton scattering. Scientific Contributions : Notable projects include the development of compact X-ray diagnostics and phase-contrast imaging instruments at LCLS, enabling nanoscale temporal and spatial resolution for high-energy-density experiments. Students : He has advised doctoral candidates Arijit Majumdar, Chance Ornelas-Skarin, Madison Singleton, and Catherine Weibel. Contact : Academic email jerome.hastings@stanford.edu
Dr. Sana Jahanshahi Anbuhi is an Associate Professor at the Department of Chemical and Materials Engineering , Gina Cody School of Engineering and Computer Science , Concordia University. She holds the Concordia University Research Chair Tier II in Stable Bio/Chemo-Sensors and serves as the Graduate Program Director for PhD and MASc programs. Her research focuses on Paper-based microfluidic devices and thermal stabilization of biologics for portable diagnostic applications. Education: Ph.D. in Chemical Engineering (2015), McMaster University , Canada B.Sc. in Chemical Engineering, Sharif University of Technology , Iran Her work emphasizes point-of-care diagnostics , bio-sensing , and detection of pesticides , heavy metals , and microorganisms . Recent publications highlight gold nanoparticle-based tablets for colorimetric assays in environmental monitoring and food safety . She has also contributed to flow control in paper microfluidics and vaccine stabilization using sugar films . Scientific patents include methods for stabilizing molecules without refrigeration and pullulan mixtures for preserving chemicals. Her teaching activities include courses on Advanced Separation Processes , Thermodynamics I , and Research Protocols and Safety . She actively mentors researchers and has participated in numerous international conferences and media features, including interviews in Le Devoir and The Globe and Mail .
Koroush Shirvan is the Atlantic Richfield Career Development Professor in Energy Studies and a tenured faculty member in MIT's Department of Nuclear Science and Engineering within the School of Engineering. Joined in July 2017, he directs the Reactor Technology Course for Utility Executives and leads the Fission Materials in Extreme Environments Lab. His work bridges nuclear engineering with practical industrial applications for decarbonization. His research focuses on reactor design economics, materials testing under irradiation, nuclear safety, and boiling heat transfer. He accelerates innovations in nuclear fuels, small modular reactors, and space propulsion through multi-scale physics integration. Current projects include accident-tolerant fuels, high-temperature materials for microreactors, and AI-driven optimization of reactor systems. His approach combines experimental irradiation testing at MITR with advanced computational modeling. Recent publications reveal strong trends toward economic nuclear deployment via advanced fuel technologies and small modular reactors. AI/ML applications dominate optimization research, particularly for core reload and uncertainty quantification. Materials science under extreme conditions remains central, with growing emphasis on space nuclear applications and horizontal reactor configurations for cost reduction. His scientific recognition includes: Nuclear News 40 under 40 (2024) American Nuclear Society Landis Young Member Engineering Achievement Award (2023) American Nuclear Society Reactor Technology Award (2022) Teaching responsibilities span Sustainable Energy (22.811/081), Graduate Reactor Physics, and Nuclear Design courses. Research grants support experimental programs at MIT Reactor Lab and computational frameworks for reactor-to-repository analysis. He mentors students through senior design projects and graduate research in nuclear fuel cycles. He directs the Fission Materials in Extreme Environments Lab and co-leads MIT's Space Nuclear initiative with AeroAstro. The team conducts irradiation experiments using MITR's high-temperature hydrogen flow capabilities and advanced diagnostics for post-irradiation examination. Current thrusts include nuclear thermal rocket materials testing and fission surface power development for lunar/Mars missions.
Prof. Dr. Michael Schäferling is a Professor of Photonic Materials at the Department of Chemical Engineering (CIW), FH Münster - University of Applied Sciences. His research focuses on optical chemical sensors, upconversion nanomaterials, and surface functionalization for chemical sensing. He teaches courses in Functional Materials , Materials Science , and advanced topics like Chemical Sensors and Technology of Coatings . University : FH Münster - University of Applied Sciences School : Department of Chemical Engineering Department : Laboratory for Photonic Materials His recent publications (2019–2024) address fluorescence imaging for medical diagnostics, upconversion crystal synthesis , and sensor design for corrosion monitoring . Key trends include the development of ratiometric measurement techniques , core-shell nanoprobes , and environmentally stable sensor materials . Prof. Schäferling’s work emphasizes surface functionalization of nanomaterials for energy transfer systems and tailoring crystal morphology to optimize luminescence. He has contributed to applied inorganic chemistry and nanostructured materials for analytical applications. Contact: michael.schaeferling@fh-muenster.de
Paul J Benkeser is a Professor and Senior Associate Chair in the Wallace H. Coulter Department of Biomedical Engineering at the Georgia Institute of Technology and Emory University. He has been a member of the Georgia Tech faculty since 1985 and was a founding faculty member of the Coulter Department in 1998, serving as its first associate chair for undergraduate studies. Education: BS in Electrical Engineering from Purdue University MS in Electrical Engineering from University of Illinois at Urbana-Champaign PhD in Electrical Engineering from University of Illinois at Urbana-Champaign Research Interests: Dr. Benkeser's work spans biomedical engineering education, ultrasound applications in medicine, biomedical signal/image processing, cancer biology, and regenerative medicine. After initial research in therapeutic/diagnostic ultrasound, he shifted focus to enhancing undergraduate curricula through problem-driven learning and global experiential opportunities. Grants: His initiatives have received funding from the National Institutes of Health (NIH), National Science Foundation (NSF), Department of Veterans Affairs, and Whitaker Foundation. Professional Activities: An active ABET participant since 2002, he has served as program evaluator, EAC Commissioner, and board delegate. His affiliations include: American Institute for Medical and Biological Engineering Biomedical Engineering Society American Society for Engineering Education Senior member of IEEE
Zenun Kastrati is an Associate Professor at the Department of Informatics, Linnaeus University. His research focuses on Artificial Intelligence, Natural Language Processing, Machine Learning, Semantic Web, Sentiment Analysis, and Learning Technologies. He contributes to the Data-driven Business Innovation (DBI) and Interaction Design Research Groups, leading projects like Forest 4.0, RAPID, and IGNITE. His recent work involves Explainable AI, medical imaging, and multilingual NLP. Ph.D. in Computer Science (NTNU, 2018) Master's in Computer Science (EU TEMPUS Programme) Previous Lecturer/Researcher at University of Prishtina His research spans AI applications in medical diagnostics , NLP , sentiment analysis , and semantic technologies . Key projects include Forest 4.0 (environment monitoring) and RAPID (online education in Pakistan). Publications highlight his expertise in deep learning , transformer models , and context-aware systems . Recent publications demonstrate trends in Explainable AI (XAI) for healthcare, medical imaging techniques, and multilingual NLP frameworks. Other work explores social media analytics , student feedback analysis , and pedagogical document classification . Zenun's teaching includes Fundamentals of Programming , Object-Oriented Programming , Web Applications , Data Analytics , and Adaptive Web courses at BSc and MSc levels.
Irena Koprinska is a prominent researcher at the University of Sydney with over 150 publications from 1996 to 2025. Her work spans multiple interdisciplinary domains with significant contributions to machine learning applications in educational technology, time series forecasting, and health informatics. She maintains strong research collaborations, particularly with Kalina Yacef (38 joint publications), Mashud Rana (26 papers), and Bryn Jeffries (22 papers), indicating leadership in her research group. Her research interests focus on practical applications of machine learning across diverse domains. In educational data mining, she has pioneered methods for predicting student performance in programming courses, analyzing syntax errors, and developing automated hint generation systems. Her work in time series forecasting has made significant contributions to solar power prediction using advanced neural network architectures. Additionally, she has applied machine learning techniques to medical domains, particularly in sleep disorder detection and analysis. The analysis of her 15 most recent publications (2022-2025) reveals a continued focus on educational technology and time series analysis, with increasing attention to interpretable methods and health applications. Her work demonstrates a consistent trajectory of applying sophisticated machine learning techniques to solve real-world problems across multiple domains, with particular emphasis on creating practical tools for education and renewable energy management. Notable Research Contributions: Development of the HINTS framework for automated programming hint generation Innovative approaches to multistep-ahead time series forecasting Applications of deep learning to sleep disorder detection Methods for predicting student performance in programming education Her publication record in top venues including Machine Learning journal, AIED, EDM, and IJCNN demonstrates significant impact in both machine learning and educational technology communities. The consistent output of high-quality research over nearly three decades indicates sustained scholarly productivity and leadership in her fields of expertise.
Dr Charlie Ryan is an Associate Professor in the School of Engineering at the University of Southampton , specializing in low-cost micropropulsion systems for small spacecraft. He leads the Astronautics Group and has a primary research focus on electrospray thrusters , Hall-effect thrusters , and small chemical propulsion systems using hydrogen peroxide. PhD in electrospray voltage effects from Queen Mary University of London (2011) Postdoctoral work on MEMS electrospray thrusters for cubesats (2011-2013, European Commission FP7 'MicroThrust') Post Doctoral Research Fellow at University of Surrey’s Space Centre (2014-2015) developing low-cost Hall-effect thrusters His recent research involves experimental characterization of ionic liquid ion sources , porous electrospray thrusters , and in-situ lunar propellants . Current projects include Protolaunch and SPRINT (Research England), Cryptalabs , and collaborations with SmallSpark. He has supervised 10 PhD students in propulsion technology and related fields. Publications demonstrate expertise in: Electrospray thruster diagnostics Dual-species ion emission mechanisms Flight-ready microthruster development Alternative propellants for Hall thrusters Lunar regolith-derived propulsion Modular thruster design Research funded by EPSRC , Royal Society , and Research England . His hardware has flown on space missions including the International Space Station.
Professor Lyudmila Mihaylova is a distinguished academic at the University of Sheffield's School of Electrical and Electronic Engineering, where she holds the position of Professor of Signal Processing and Control. She has established herself as a leading researcher in the fields of signal processing, Bayesian methods, and autonomous systems, with significant contributions to particle filtering techniques for intelligent transportation systems. Her work bridges theoretical developments with practical applications across multiple domains including transportation, healthcare, and industrial automation. Prof. Mihaylova's research interests center on nonlinear filtering, sequential Monte Carlo methods, statistical signal processing, and sensor data fusion. Her work spans both theoretical advancements and practical implementations, with particular focus on high-dimensional problems including vehicular traffic flow estimation, image processing, and localization in sensor networks. She has extensive experience with various image modalities such as optical, thermal, LIDAR, SAR, and hyperspectral imaging. Her group actively develops novel methods for autonomous intelligent systems focusing on sensing, tracking, decision making, and machine learning applications. Analysis of Prof. Mihaylova's recent publications reveals a strong trend toward uncertainty quantification in machine learning models, particularly for safety-critical applications. Her work increasingly integrates traditional signal processing techniques with modern deep learning approaches, with applications spanning sewer inspection robotics, medical diagnostics (particularly sleep apnea detection), UAV swarm tracking, industrial manufacturing, and autonomous vehicle systems. A significant portion of her recent research focuses on developing robust methods that can handle incomplete or outlier-corrupted data while providing reliable uncertainty estimates. Among her notable professional achievements: President of the International Society of Information Fusion (ISIF) Senior member of the IEEE Signal Processing Society Associate Editor for IEEE Transactions on Aerospace and Electronic Systems Associate Editor for Elsevier Signal Processing Journal Prof. Mihaylova has successfully mentored numerous PhD students and postdoctoral researchers, many of whom have gone on to prominent academic and industry positions. Her research has been supported by major funding bodies including EPSRC, EU, MOD/DSTL, and industry partners, with recent projects including 'Protecting Environments with UAV Swarms' (InnovateUK, 2022-2024), 'ShiRAS: Towards Safe and Reliable Autonomy in Sensor Driven Systems' (NSF-EPSRC, 2019-2023), and 'Confident safety integration for Cobots' (Lloyd's Register Foundation, 2019-2020). Her research group follows a collaborative approach with the philosophy 'We share knowledge, we grow.' Prof. Mihaylova maintains active research collaborations with institutions worldwide and has held previous academic positions at Lancaster University (2006-2013) and University of Bristol (2004-2006), along with research visiting positions at the University of Ghent, Katholic University of Leuven, and the Bulgarian Academy of Sciences.
Hamidreza Karami is an Associate Professor in the School of Petroleum and Geological Engineering at the University of Oklahoma. His research focuses on multiphase flow, production engineering, artificial lift, and flow assurance, with applications in unconventional wells, geothermal systems, and hydrogen transportation. BSc, Petroleum Engineering, Sharif University of Technology (2009) MSc, Petroleum Engineering, The University of Tulsa (2011) PhD, Petroleum Engineering, The University of Tulsa (2015) Karami's work combines experimental and computational fluid dynamics (CFD) with machine learning to address challenges in gas lift, downhole separators, well cleanout, and leak detection. Recent publications emphasize data-driven modeling of multiphase flow systems and optimization of artificial lift methods. His lab at the University of Oklahoma investigates advanced technologies for flow assurance, including paraffin and asphaltene deposition, foam lifting, and surfactant applications. Collaborative projects involve Tulsa University Fluid Flow Projects (TUFFP) and industry stakeholders.
Prof. Dr. Norbert Sewald, Chair of Organic and Bioorganic Chemistry at Bielefeld University, is a leading figure in Bioorganic Chemistry , Chemical Biology , and Enzymatic Halogenation . As head of the Organic and Bioorganic Chemistry Group at the Center for Biotechnology (CeBiTec), he drives research on natural products and drug conjugates. Full Professor, Bielefeld University (since 1999) Founding Coordinator, International Graduate School of Chemistry and Biochemistry (2001-2003) Chairman, Institute of Biochemistry and Bioengineering at CeBiTec (2006-2008) Dean, Department of Chemistry (2008-2011) Chairman, Max-Bergmann-Kreis e.V. (since 2010) Coordinator, Marie Skłodowska-Curie Training Networks (MAGICBULLET, 2015-2018; Magicbullet::reloaded, 2020-2023) His research focuses on halogenases for mild peptide bromination, cryptophycin-based tumor targeting , and bioactive natural products from African flora. Collaborative projects span antiplasmodial agents , antibacterial compounds , and neurodegenerative disease inhibitors . Recent work highlights include: Enzymatic halogenation cascades Click-to-release drug conjugates Fluorescent probes for amyloid detection Key affiliations: Faculty of Chemistry Center for Biotechnology (CeBiTec) European Peptide Society (Scientific Affairs Officer, 2016-) Leibniz Institute of Plant Biochemistry (Scientific Advisory Board, 2010-2017)
