جست‌وجوی استاد و پژوهشگر

Alison Langmeadمشاهده پروفایل

دانشیار بالینی

• Digital Humanities
• Digital Art History
• Visual Culture Studies
• +۳ مورد دیگر

Alison Langmead serves as Clinical Associate Professor and Director of the Visual Media Workshop in the Department of Art History and Architecture at the University of Pittsburgh's Dietrich School of Arts and Sciences, with a joint appointment as Associate Professor in the School of Computing and Information. Her work bridges digital humanities, visual culture studies, and information management history through mindful technological application. Education: PhD, Columbia University MLIS, University of California at Los Angeles Langmead's research centers on the intersection of digital methods and visual/material culture, examining historical information practices alongside contemporary computational approaches. She pioneers sustainable digital scholarship frameworks while critically analyzing AI's role in art historical connoisseurship and cultural preservation. Her work emphasizes intentional technology use that respects scholarly integrity and humanistic values. Recent publications reveal consistent focus on collaborative digital art history methodologies, computational modeling of visual data, and sustainable infrastructure development. Key trends include network analysis applications, role-based collaboration frameworks, and ethical considerations in AI-driven art scholarship, demonstrating evolution from technical implementation toward systemic sustainability and human-centered design. Scientific Awards: Award for Excellence in Graduate Mentoring, Dietrich School of Arts and Sciences, University of Pittsburgh, May 2023 Langmead actively mentors graduate students through the DHRX initiative while securing significant research funding. Her current grants include 'Teaching Art History with AI' (PI, 2023-present), 'InfoEco Cookbook' (2021-2022), and 'The Socio-Technical Sustainability Roadmap' (PI, 2015-2018, ongoing dissemination), reflecting her commitment to practical digital scholarship frameworks. As Director of the Visual Media Workshop, Langmead cultivates interdisciplinary collaboration across campus, creating spaces where faculty and students develop innovative digital research tools while critically examining technology's role in scholarly practice and cultural preservation.

Jian Kangمشاهده پروفایل

استاد

• Biostatistics
• Bayesian Methods
• Gaussian Processes
• +۱۱ مورد دیگر

Jian Kang is a Professor and Associate Chair for Research at the University of Michigan School of Public Health , specializing in Biostatistics . His work focuses on developing advanced statistical methods for large-scale biomedical data , with applications to precision medicine , neuroimaging , and genomics . Education: PhD in Biostatistics, University of Michigan (2011) MS in Mathematics (Statistics), Tsinghua University (2007) BS in Statistics, Beijing Normal University (2005) Research Interests include Bayesian nonparametric methods , deep learning for medical imaging , ultra-high-dimensional variable selection , and graphical models for network inference . His 2025-2023 publications demonstrate expertise in Bayesian hierarchical modeling , spatial statistics , and machine learning for healthcare . Scientific Awards : Michigan SPH Excellence in Research Award (2025) ICSA President's Citation Award (2024) Statistics in Biopharmaceutical Research Best Paper (2023) Best Paper in Biometrics by IBS Member (2022) Fellow, American Statistical Association (2021) Grants include NSF-IIS (2021-2025) for BCI statistical learning , NIGMS (2020-2022) for metabolomics biomarker selection , NIDA (2020-2025) for imaging data analysis , and NIMH (2014-2025) for multidimensional neuroimaging methods . Labs and Teams develop Bayesian computational tools for neuroimaging and spatial transcriptomics , collaborating with institutions like Emory University and University of North Carolina.

• Sleep
• Circadian rhythms
• Bioinformatics
• +۴ مورد دیگر

Ron C Anafi serves as Associate Professor of Medicine (Sleep Medicine) at the Hospital of the University of Pennsylvania and holds key affiliations as Faculty Scholar at the Penn Institute for Bioinformatics, Co-Investigator at the Center for Subcellular Genomics, and member of both the Chronobiology and Sleep Institute and ITMAT. His work bridges computational biology with clinical sleep medicine within the Perelman School of Medicine. His educational trajectory includes a B.S.E. in Biomedical Engineering and Philosophy from Tulane University (1995), followed by a Ph.D. in Applied Mechanics (2002) and M.D. (2004) from the University of Minnesota. This dual training underpins his unique approach to circadian research. Dr. Anafi's laboratory pioneers computational methods to decode sleep and circadian influences on human physiology, focusing on neurodegeneration and cancer. By applying machine learning and systems biology to large-scale omics data, his team reconstructs molecular rhythms from cross-sectional human tissue databases—overcoming the critical barrier of limited longitudinal sampling in patients. His research demonstrates how circadian disruptions in ribosomal function link to Alzheimer's pathology and how tumor clock strength predicts breast cancer outcomes. Analysis of his 15 most recent publications (2022-2025) reveals intensifying focus on cell-type-specific circadian disruptions in neurodegenerative diseases, with significant expansion into cancer chronobiology and contactless sleep monitoring technologies. His methodological innovations like CYCLOPS enable rhythmic signal extraction across diverse tissues—from brain to skin—while increasingly integrating multi-omics layers to identify therapeutic targets. As mentor in the Genomics and Computational Biology and Neuroscience graduate groups, he guides students through rotation projects at his Translational Research Laboratories facility (Suite 2100, 125 South 31st Street). His research is supported by NIH grants investigating circadian mechanisms in Alzheimer's disease and cancer progression, with recent work exploring sex-specific metabolic impacts of circadian genes and non-invasive sleep monitoring.

Noah P. Molotchمشاهده پروفایل

استاد

• Mountain Hydrology
• Snow Hydrology
• Ecohydrology
• +۴ مورد دیگر

Noah P. Molotch is a Professor in the Department of Geography at the University of Colorado Boulder, leading the Mountain Hydrology Group and affiliated with the Cryosphere and Surface Processes Lab and Niwot Ridge Long-Term Ecological Research program. His work integrates ground observations, remote sensing, and computational modeling to advance understanding of mountain hydrology, water resources, and ecohydrology in changing climates. His educational background includes: PhD in Hydrology and Water Resources from the University of Arizona (2004) MS in Environmental Science and Management from the University of California, Santa Barbara (2000) BA from the University of Colorado Boulder (1997) Molotch's research focuses on snow hydrology , ecohydrology , and remote sensing with emphasis on snowmelt distribution, soil moisture dynamics, and streamflow generation. He investigates how climate change alters snowpack characteristics and hydrological partitioning, affecting forest productivity and carbon cycling in montane ecosystems. His work spans from the Colorado Front Range to Chilean Andes, addressing critical water security challenges through field studies and satellite data integration. Recent publications (2024-2025) reveal three dominant research thrusts: (1) Advanced snow water equivalent estimation using machine learning and airborne remote sensing, (2) Climate impacts on snowmelt timing and hydrological partitioning across mountain systems, and (3) Ecohydrological feedbacks between snow dynamics and vegetation productivity. These studies increasingly incorporate drone-based multispectral imaging and cross-scale data fusion to resolve spatial heterogeneity in alpine environments. Molotch mentors PhD students Millie Spencer and Emma Tyrrell, with Spencer documenting glacier retreat in Chile through CUAHSI-funded research. His group has secured significant grants from the U.S. Bureau of Reclamation for developing operational snowpack datasets, while collaborating with NASA, NOAA, and water management agencies on real-time monitoring systems. Community engagement includes art-science collaborations like the Colorado Arts Science Environment Program to communicate climate impacts. The Mountain Hydrology Group operates cutting-edge facilities including the Cryosphere and Surface Processes Lab and contributes to the Niwot Ridge Long-Term Ecological Research site. They deploy airborne lidar, drone-based thermal imaging, and wireless sensor networks to map snow properties at unprecedented resolutions, directly informing water resource management during drought and flood events across the Western U.S.

• Fuzzy Logic
• Soft-Computing
• Health Monitoring
• +۹ مورد دیگر

Nishchal K. Verma is a Professor at the Department of Electrical Engineering, Indian Institute of Technology Kanpur. He holds a PhD from IIT Delhi (2007), an M.Tech from IIT Roorkee (2003), and a B.Tech from DEI Agra (1996). His postdoctoral research includes work at the University of Tennessee (2009) and Louisiana Tech University (2008). Specialization: Fuzzy Logic, Health Monitoring, Intelligent Informatics Current Research Interests: Intelligent Data Mining, Computer Vision, Smart Grids, Biomedical Applications His research focuses on Fuzzy Systems , Machine Learning , and Health Monitoring with applications to power systems, biomedical data, and wireless sensor networks. He has developed technologies like the Transducers and Instrumentation Virtual Laboratory and Brain Computer Interface Laboratory , emphasizing predictive modeling and fault diagnosis. Key sponsored projects include DST-funded Fuzzy Rule-Based Image Prediction and DRDO-supported Visual Surveillance Systems . His work spans 15+ years of interdisciplinary publications in journals and conferences. Scientific Awards : Devendra Shukla Young Faculty Research Fellowship (2013-16) He has served as Associate Editor for journals and Chairman of IEEE chapters, with leadership roles in academic administration at IIT Kanpur.

Mauro Ferrariمشاهده پروفایل

استاد

• Cancer therapeutics
• Nanomedicine
• Drug delivery technology
• +۲ مورد دیگر

Mauro Ferrari is a distinguished Professor in the Department of Pharmaceutics at the University of Washington , joining in 2019. Previously, he served as tenured professor in engineering and/or medicine at institutions including the University of Texas, University of California Berkeley, Ohio State University, and Weill Cornell Medicine. He led the Houston Methodist Research Institute as President & CEO and held leadership roles at the European Research Council. Dottore in Matematica, Universita di Padova, Italy PhD and MS in Mechanical Engineering, University of California, Berkeley Executive education at Harvard Business School and Wharton As a pioneer of nanomedicine and transport oncophysics, his research focuses on cancer therapeutics , nanomedicine , drug delivery technology , mathematical oncology , and biological mass transport . His laboratory leads a DOD-funded initiative for metastatic breast cancer cures. His selected publications highlight trends in nanoparticle design , molecular transport , cancer nanotherapy , and multistage delivery systems . Scientific leadership includes clinical translation of dozens of drugs and medical devices . Current entrepreneurial roles: CEO of DXT Pharmaceuticals, Director at Arrowhead Pharmaceuticals, and Scientific Founder of BrYet US.

• Image Analysis
• Artificial Intelligence
• Deep Learning
• +۵ مورد دیگر

Joakim Lindblad is a Professor at the Department of Information Technology, Uppsala University , and holds affiliated roles as Senior Research Associate at the Mathematical Institute of the Serbian Academy of Sciences and Arts, and Head of Research at Topgolf Sweden AB. With over two decades of expertise in image analysis and machine learning , his work bridges computational methods with biomedical applications. Key affiliations: Uppsala University, Serbian Academy of Sciences, Topgolf Sweden Specializations: Deep Learning, Multimodal Image Registration, Quantitative Microscopy His research focuses on reliable image processing frameworks that integrate intensity and spatial information , particularly for biomedical applications . Recent publications highlight innovations in autofluorescence-based cancer detection , self-supervised one-class learning for sparse instance identification, and rotation-equivariant CNNs for robust analysis of cytology images. Recent article trends demonstrate expertise in multimodal image analysis (2024: 3 papers), oral cancer detection (2025: 2 papers), and multiscale biomedical imaging . His 2025 work on the Uppsala Storytelling Dataset introduces novel frameworks for multimodal dataset creation in AI research. While no scientific awards are explicitly mentioned, his extensive publication record (2000-2025) across top venues like Pattern Recognition , PLOS ONE , and IEEE Transactions indicates significant academic impact. His methodological contributions span stochastic distance transforms , fuzzy set defuzzification , and multimodal image registration techniques. Collaborative work with researchers like Nataša Sladoje and interdisciplinary teams has produced innovations in automated cytology analysis , TEM image enhancement , and AI-driven medical diagnostics . His 2021-2022 projects introduced contrastive learning approaches for multimodal image registration and explainable AI frameworks for infant engagement analysis.

• Tumor Microenvironment
• Extracellular Vesicles
• Exosomes
• +۵ مورد دیگر

Nao Nishida serves as Assistant Professor at Waseda University's Institute for Advanced Study since 2022, following appointments at Tokyo Medical University and Fred Hutchinson Cancer Center. Her research bridges cancer biology and cell-cell communication mechanisms within tumor microenvironments. Her educational background includes: PhD in Agriculture (2014) from Kyoto University Master's in Applied Life Sciences (2011) from Kyoto University Bachelor's in Applied Life Sciences (2009) from Kyoto University Nishida's research centers on extracellular vesicle-mediated tumor-stroma crosstalk, with particular focus on exosome-driven metastasis, tumor-associated macrophage reprogramming, and organotypic culture modeling. She investigates how lipid composition and serine metabolism in cancer-derived EVs regulate microenvironmental remodeling and therapeutic resistance. Her work integrates advanced lipidomics, real-time tissue imaging, and spatial EV distribution analysis to uncover metastatic mechanisms. Analysis of her 17 publications reveals dominant themes in exosome biology (71% of works), cancer microenvironment dynamics (63%), and therapeutic targeting strategies (41%). Recent work increasingly incorporates spatial tissue context (2022-2024) and clinical translation potential. Her awards include: ISEV2025 New Parents Scholarship Japan Society for Promotion of Science Outstanding Researcher Candidate (2021) ISEV2017 Junior Member Scholarship Young Researcher Excellent Presentation Award (2015) Nishida directs multiple active grants including JSPS KAKENHI projects on EV secretion mechanisms (2023-2026) and nutritional stress adaptation (2025-2028), plus Mitsubishi Foundation and Uehara Memorial Foundation awards. She mentors through Waseda's bioscience curriculum while developing organotypic slice platforms for drug screening. Her laboratory utilizes advanced tumor slice culture systems and spatial EV mapping techniques to dissect microenvironmental heterogeneity, with current work focusing on stromal contribution to therapeutic resistance and organ-specific metastatic niches.

• Transnational Literary History
• European Myth of the Emotional Subject
• Bucolic Poetry and Pathos
• +۶ مورد دیگر

Karin Peters is a Full Professor of Romance Literature and Cultural Studies with a Focus on Ibero-Romania at the University of Bonn since 2023. Her academic journey includes a habilitation at Johannes Gutenberg University Mainz (2021-2022), a doctorate from LMU Munich (2010), and a Magister Artium from the same institution (2006). Her research spans transnational literary history, affect theory, pastoral poetry, and intersections of gender and politics in Spanish and Argentinian literatures. Key projects include co-editing The Face as Scene. Virtuality and Embodiment of Affect and leading the network 'Comic Literacies. Cultural Techniques of the Comic' at KWI Essen. She has supervised doctoral work on Iberoamerican Baroque theater and published extensively on Roland Barthes, Georges Bataille, and contemporary Latin American narratives. Her recent publications analyze the European myth of the emotional subject, pastoral masks in Cervantes, and affective economies in 18th-century literature. She has received scholarships from DAAD, Studienstiftung des deutschen Volkes, and e-fellows.net, and actively contributes to academic organizations including the Romanistenverband and the Bonn Center for Dependency Studies.

Brandon Luciaمشاهده پروفایل

استاد

• Intermittent Computing
• Energy-harvesting Systems
• Concurrency
• +۷ مورد دیگر

Brandon Lucia is a Full Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University's College of Engineering. He leads the abstract research group focusing on the intersection of computer architecture, systems, and programming languages. His work bridges theoretical foundations with practical implementations in energy-constrained environments. Lucia's research centers on intermittent computing systems and edge computing in extreme environments. His work on energy-harvesting systems has established fundamental principles for batteryless computing, while his orbital edge computing research pioneers computational intelligence for nanosatellite constellations. These research thrusts address critical challenges in reliability, efficiency, and programmability for systems operating under severe power constraints. His publication record shows a clear evolution from foundational work on intermittent computing models to sophisticated applications in space computing and edge intelligence. Recent publications demonstrate increasing integration of dataflow architectures with energy-harvesting constraints, particularly in satellite constellations where computational resources must be managed across distributed, power-constrained platforms operating in extreme environments. NSF CAREER Award (2017) IEEE TCCA Young Computer Architect Award (2019) Sloan Foundation Fellowship (2021) ASPLOS Best Paper Awards (2018, 2020) OOPSLA Distinguished Paper and Artifact Awards (2015) Lucia actively mentors numerous PhD students including Brad Denby, Zhuo Cheng, and Emily Ruppel, many of whom contribute significantly to his research program. His abstract research group maintains strong industry connections while pursuing fundamental advances in computing systems. The group has developed multiple open-source tools including Legerdemain for program analysis and MultiCacheSim for cache coherence simulation. His laboratory work spans from theoretical foundations of intermittent computing to practical implementations in space systems. Current projects include computational nanosatellite constellations, energy-minimal dataflow architectures, and secure edge computing systems that operate reliably despite frequent power failures.

Saidi Siuhiمشاهده پروفایل

دانشیار

• Transportation Engineering
• Traffic Safety
• Transportation Planning
• +۳ مورد دیگر

Dr. Saidi Siuhi serves as an Associate Professor of Civil Engineering at South Carolina State University, where he teaches undergraduate and graduate courses while conducting research and providing institutional service across departmental and university levels. His academic credentials include: Ph.D. in Civil Engineering from the University of Nevada, Las Vegas (2009) M.Sc. in Civil Engineering from Florida State University (2006) B.Sc. in Civil Engineering from the University of Dar-es-Salaam (2003) Specializing in transportation engineering, Dr. Siuhi's research focuses on traffic safety, transportation planning, and microscopic traffic simulation. His work addresses critical transportation challenges including distracted driving/walking behaviors, traffic management during special events (notably the 2017 solar eclipse), and the application of advanced computational methods to transportation networks. He integrates emerging technologies like virtual reality, machine learning, and deep learning to develop innovative safety solutions for complex transportation systems. Analysis of his recent publications (2021-2025) reveals a strong trajectory toward computational transportation safety, with increasing emphasis on AI-driven solutions for pedestrian safety, driver behavior analysis, and infrastructure monitoring. His work consistently bridges theoretical transportation models with practical safety applications, particularly in distracted behavior analysis and event-based traffic management. Dr. Siuhi actively mentors students through senior design projects (CE 459/460) and graduate coursework, though specific advisee names aren't documented. His service contributions span departmental, college, and university committees, supporting academic operations and strategic initiatives within the engineering program.

Geoff Dullerمشاهده پروفایل

استاد

• Luminescence Dating
• Quaternary Environmental Change
• Geomorphological Processes
• +۳ مورد دیگر

Professor Geoff Duller has been a faculty member at Aberystwyth University's Department of Geography & Earth Sciences since 1995, holding a Personal Chair since 2005. He studied Geography at St Catherine's College Oxford (BA 1987), completed his PhD in 1992 at Aberystwyth on luminescence dating of Quaternary sediments in New Zealand, and established the Aberystwyth Luminescence Research Laboratory in 2000. His research focuses on luminescence dating method development and application, particularly for Quaternary environmental change studies. Key contributions include creating single-aliquot dating methods and leading the NERC-funded BRITICE-Chrono project for ice sheet deglaciation chronology. He serves as Associate Editor of Radiation Measurements and editor of Journal of Quaternary Science , with editorial board membership at Ancient TL . His article portfolio demonstrates expertise in: Luminescence signal analysis (2025: IRPL/IRSL in feldspars; 2024: opercula thermoluminescence) Quaternary chronology (2025: Thar desert floodouts; 2024: Tibetan glaciofluvial sediments) Methodological innovation (2025: EMCCD crosstalk reduction; 2024: pIRIR protocol optimization) Scientific recognition includes the Bigsby Medal (2012). Current supervision includes PhD students Robyn Pinder, Svenja Riedesel, and Nina Ataee. He co-directs the Aberystwyth Luminescence Research Laboratory and manages specialized equipment including Risø luminescence readers.

Mariaelena Pierobonمشاهده پروفایل

دانشیار

• Biomedical Research
• Medical Proteomics
• Precision Medicine
• +۳ مورد دیگر

Mariaelena Pierobon is an Associate Professor at George Mason University's School of Systems Biology, affiliated with the Institute for Advanced Biomedical Research and the Center for Applied Proteomics and Molecular Medicine (CAPMM). Her research focuses on precision medicine for cancer patients, integrating translational studies and clinical trials with emphasis on metastatic disease and tumor microenvironment analysis. MD, University of Padova (Italy), School of Medicine MPH, George Mason University Her work leverages in vitro models and patient-derived specimens with state-of-the-art technologies to explore cancer dynamics and develop tailored therapies. Recent projects include proteogenomic profiling of breast and ovarian tumors, KRAS mutation targeting, and spatial heterogeneity mapping in gynecologic cancers. Scientific trends in her publications include precision oncology, signaling pathway inhibition in KRAS-mutant cancers, tumor microenvironment analysis, and multi-omic diagnostics for therapeutic response prediction. Fulbright Scholar (2019) Pierobon collaborates with clinical teams using reverse phase protein arrays (RPPA) and laser capture microdissection to dissect molecular mechanisms in pancreatic, breast, and ovarian cancers. Her lab contributes to databases like the Side-Out Foundation Metastatic Breast Cancer portal for open-access multi-omic research.

• Digital Holography
• Laser Engineering
• Marine Technology
• +۶ مورد دیگر

Dr. Thangavel Thevar is a Senior Lecturer in the School of Engineering at the University of Aberdeen, where he has been teaching since 2005. He completed both his undergraduate degree (First Class Honours in Electrical Engineering) and PhD (in Laser Engineering) at the University of Aberdeen in 1989 and 1993 respectively. Prior to his academic career, he accumulated approximately 10 years of industrial R&D experience in the USA, working on solid-state laser development and holographic applications. Dr. Thevar's research focuses on several key areas: Digital holography for imaging of marine plankton and micro-particles Laser Induced Breakdown Spectroscopy (LIBS) for subsea applications Laser-based instrumentation development Development of solid-state lasers for scientific, industrial, and medical applications Engineering applications of holography His most notable recent achievement is leading a team that developed the weeHoloCam, a state-of-the-art ultracompact underwater holographic camera for imaging microorganisms. Weighing just 3.5 kg, this system is the lightest and most compact of its kind, capable of imaging 240 ml/s and continuously recording up to 200,000 holograms. The system incorporates a rapid hologram processor and an AI-based image classifier. This technology has significant applications in marine studies including spatial and temporal monitoring of plankton species, monitoring harmful plankton & micro-jellyfish, study of vertical transport of floc, and monitoring microplastic pollution in the ocean. Dr. Thevar has secured numerous research grants as Principal Investigator, including projects funded by Sustainable Aquaculture Innovation Centre (SAIC), BBSRC, DEFRA, and Defence & Security Accelerator (DSTL). His current research portfolio demonstrates strong interdisciplinary connections between optical engineering, marine science, and environmental monitoring. His scientific contributions include: Royal Academy of Engineering Visiting Teaching Fellow Award (2010-2013) US patent 8,494,012 B2 for Raman converters Development of alexandrite lasers and ruby holographic lasers during his industrial R&D period Work on US government contracts for non-destructive inspection methods for military aircraft and the space shuttle Sabbatical work at NASA Langley Research Centre developing diode pumped Thulium YALO lasers As an educator, Dr. Thevar has served as Coordinator of MSc Oil & Gas Engineering (2007-2020), Undergraduate Level 1 Coordinator, and has contributed to various committees including Quality Assurance and Students' Progression. He currently teaches courses including Principles of Electronics, Electrical & Mechanical Systems, Control Systems, and supervises individual projects at both undergraduate and postgraduate levels. He is accepting PhD students interested in Engineering research. Dr. Thevar is actively involved in professional organizations, serving as Technical Programme Chair for IEEE/OES Oceans Conference 2007, on organizing committees for various conferences, as a committee member of the Instrument Science and Technology Group (Institute of Physics), and as a member of both IET and IEEE. He also serves as a reviewer for optics-based journals.

Danijel Skočajمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Deep Learning
• +۳ مورد دیگر

Danijel Skočaj is Full Professor at the University of Ljubljana, Faculty of Computer and Information Science , and serves as Head of the Visual Cognitive Systems Laboratory . He is an internationally recognized researcher in computer vision, machine learning, and cognitive robotics , with a strong focus on deep-learning solutions for real-world visual perception tasks and their ethical implications. Education: While specific degrees are not listed in the text, Professor Skočaj’s 2002 “Best PhD paper award” confirms he holds a PhD in the relevant field. Research Interests: His work spans Computer Vision & Pattern Recognition Deep Learning & Neural Networks Cognitive Robotics & Autonomous Navigation Visual Anomaly & Surface-Defect Detection AI Ethics & Societal Impact of AI These interests manifest in both theoretical advances and practical systems deployed in industry and public infrastructure. Publication Trends: Recent papers (2020-2024) emphasize deep-learning architectures for defect detection, robotic grasping, autonomous navigation, traffic-sign recognition, and 3-D anomaly detection , demonstrating a clear trajectory toward robust, real-time, and data-efficient visual intelligence. Awards & Honors: Prometheus of Science Award 2021 (Slovenian Science Foundation) Golden Plaque, University of Ljubljana 2020 ARRS National Award for Exceptional Scientific Achievement 2011 & 2022 Multiple Best-Paper awards at ERK conferences (2013, 2017, 2019) Top-downloaded paper recognition, Journal of Intelligent Manufacturing 2020 Grants & Projects: He currently leads or co-leads five major 2025-2028 national and EU projects (RTFM, SMASH, COMET, RoDEO, MUXAD) totaling several million Euros, focusing on advanced computer vision, machine learning for science & humanities, autonomous systems, and explainable AI. Past leadership includes EU FP7 CogX, GOSTOP, ViLLarD, and many ARRS programmes. Laboratory & Team: The Visual Cognitive Systems Laboratory hosts a dynamic group of doctoral and master’s students working on cutting-edge perception systems. The lab’s open-source low-cost robotic platform and datasets are widely adopted for education and research.