Tommaso Vincenzo Bartolotta is a Full Professor in the Department of Biomedicine, Neuroscience and Advanced Diagnostics at the University of Palermo's School of Medicine and Surgery. He specializes in advanced diagnostic imaging techniques, with office hours held at the Institute of Radiology within Palermo University Hospital. His research focuses on: Innovations in medical imaging (MRI, ultrasound, contrast-enhanced techniques) AI-driven diagnostics for oncology (breast, liver, prostate, brain tumors) Radiomics and quantitative imaging biomarker development Clinical applications of elastography and microvascular ultrasound Recent publications demonstrate a strong emphasis on artificial intelligence integration into radiological workflows, particularly for breast cancer characterization, liver disease assessment, and therapeutic response prediction. No scientific awards or student advising relationships were documented in the provided materials. Contact is available via institutional email.
Oliver Geißendörfer is a Research Associate at the Chair of Engineering Geodesy within the Technical University of Munich . His work focuses on LiDAR technology, point cloud processing, and geodetic monitoring systems, with applications in structural analysis and environmental engineering. Education: Master of Science in Geodesy and Geoinformation (2018-2021) Bachelor of Science in Geodesy and Geoinformation (2014-2018) His research interests include spatio-temporal analysis of vibration responses, sensor fusion (LiDAR, GNSS, IMU), and efficient point cloud processing algorithms. Recent work emphasizes combining LiDAR with time-domain frequency analysis for enhanced structural monitoring. He has supervised multiple theses on topics like steel component detection in point clouds, MEMS LiDAR comparisons, GNSS accuracy studies, and boundary point setting techniques.
Professor Vikram Krishnamurthy is a distinguished academic at Cornell University , affiliated with the School of Electrical & Computer Engineering , Center for Applied Mathematics , and Mechanical & Aerospace Engineering . He leads the Cornell Statistical Signal Processing Lab and is part of the Foundations of Information, Network, and Decision Systems (FIND) collaborative. His career spans institutions like the University of British Columbia (Canada Research Chair, 2002-2016) and University of Melbourne (1994-2002). His research bridges statistical signal processing , stochastic control (POMDPs), and network science , with applications in social networks , cognitive radar , and ion channel biosensors . Key themes include human-machine interfacing , inverse reinforcement learning , and behavioral economics . Recent publications focus on adaptive inverse reinforcement learning , LLM agent interactions , and quantum decision systems , reflecting his work in machine learning , stochastic optimization , and social network analytics . His book Partially Observed Markov Decision Processes (2nd ed., 2025) is a seminal text in the field. Scientific Awards: Fellow of the Institute of Electrical and Electronics Engineers (IEEE) Distinguished Lecturer, IEEE Signal Processing Society Editor-in-Chief, IEEE Journal on Selected Topics in Signal Processing Honorary Doctorate from KTH Royal Institute of Technology, Sweden Jean Pierre LeCadre Award (2019) He currently advises PhD students including Shashwat Jain, Luke Snow, Adit Jain, and Yiming Zhang. His teaching includes advanced courses like Bayesian Estimation and Stochastic Optimization (ECE 7230) and Data Science for Engineers (ECE 2720).
Noemi Mauro is a Tenure-track Assistant Professor in the Department of Computer Science at the University of Torino, Italy. She holds a PhD in Computer Science with honors from the same institution, supervised by Prof. Liliana Ardissono. Her research focuses on personalization, recommender systems, user modeling, and information retrieval, with a strong emphasis on inclusive technologies for people with Autism Spectrum Disorders (ASD). PhD in Computer Science with Honors, University of Turin (2016–2019) Master’s in Computer Science, University of Turin (2014–2016), 110/110 summa cum laude Bachelor’s in Computer Science, University of Turin (2011–2014), 110/110 Visiting PhD at Alpen-Adria-Universität Klagenfurt (2018–2019) Visiting PhD at University College Dublin (2017–2018) Her research interests include Recommender Systems , Personalization , User Modeling , Information Retrieval , Accessibility , and Cultural Heritage . She has made significant contributions to inclusive technologies, particularly through systems that support people with autism in tourism and urban navigation. Her work integrates ethical and sustainable dimensions into recommendation algorithms. Her recent publications (2023–2025) reflect a strong trend toward explainable AI , sustainable consumption , cultural heritage exploration , and inclusive design . She frequently publishes in top venues such as ACM UMAP, RecSys, IEEE Access, and Springer journals. Her research often involves multimodal interfaces, service-oriented architectures, and user-centered evaluations. Best Paper Award, UMAP 2020 Young Researcher Award, University of Turin (2022) Women in RecSys Journal Paper of the Year (2022) Outstanding PC Member, HT 2020 Best Master’s Thesis Award, University of Turin (2017) Noemi Mauro actively supervises PhD and master’s students and has advised numerous bachelor’s theses on topics ranging from accessibility to gamification and ethical recommendation. She leads major research projects such as SPACES (Fondazione CRT) and ACCESS (PRIN), focusing on social inclusion and anxiety management for people with ASD. She also plays key roles in national and European initiatives like RevIs and NODES . In teaching, she delivers courses on databases and recommender systems. She is deeply embedded in the academic community as a workshop co-chair (PATCH series), editorial board member of UMUAI, and co-editor of special issues on AI for social good and inclusive systems. She leads and contributes to labs and research teams focused on intelligent user interfaces , personalized access to cultural heritage , and inclusive recommender systems . Her work is conducted within collaborative environments such as the co3project (H2020) and the OnToMap platform, emphasizing semantic data interoperability and public engagement.
María Luz Gil Docampo is a researcher at the University of Santiago de Compostela's Department of Agroforestry Engineering, focusing on photogrammetry, remote sensing, and 3D modeling applications. She collaborates extensively with colleagues like Juan Ortiz Sanz and Santiago Martínez Rodríguez, contributing to interdisciplinary projects in heritage conservation, structural analysis, and environmental monitoring. Education : PhD in Agroforestry Engineering (2001, University of Santiago de Compostela), with a thesis on satellite imagery applications. Research : Specializes in low-cost photogrammetric systems, 3D documentation of cultural heritage, biomass determination in agriculture, and land-use change detection using LiDAR and satellite data. Publications : 15+ journal articles and book chapters spanning 2001-2024, with recent work on full-scale timber structure monitoring (2024) and ethical considerations in multimedia systems (2021). Supervision : Directed 6 doctoral theses including UAV-based biomass monitoring (2022), agroforest plantation survival analysis (2016), and photogrammetry applications in archaeology (2020). Projects : Key member of GI-2114 Group (USCAN3D), developing cost-effective 3D scanning solutions for cultural assets and rural infrastructure. Her work bridges technical innovation with practical applications in agriculture , forestry , and cultural heritage preservation , often involving multidisciplinary methodologies like UAV integration, open-source software, and LiDAR data analysis.
Ruaridh Clark is a Senior Research Fellow in the Department of Electronic and Electrical Engineering at the University of Strathclyde, United Kingdom. He is actively engaged in research, supervising PhD students, and contributing to multiple funded projects in biomedical signal processing and neurotechnology. His research interests lie at the intersection of biomedical engineering, signal processing, and human-computer interaction, with a strong focus on EEG-based systems, wearable sensors, and real-time health monitoring. His work enables advancements in brain-computer interfaces, emotion recognition, seizure detection, and cognitive state assessment. The analysis of his recent publications reveals a consistent trend in developing robust, real-time, and wearable neurophysiological systems. These works emphasize adaptive signal processing, multimodal data fusion, machine learning, and low-power embedded solutions for clinical and real-world applications. 9 prizes or awards (specific names not listed in text) Ruaridh Clark supervises several PhD students, including Agathe Bouis, Joshua Gribben, and Beth Probert. He is involved in 18 research projects, indicating active grant funding and collaborative research. His work is highly interdisciplinary, bridging engineering, neuroscience, and clinical applications. He is affiliated with the research group led by Professor Malcolm Macdonald and collaborates across disciplines, including with researchers in psychology. His lab focuses on developing wearable, real-time, and intelligent systems for neurophysiological monitoring and human performance assessment.
T. Economou is affiliated with the Department of Mathematics and Computer Science at the University of Exeter, UK, where he conducts research at the intersection of statistics and meteorology. His work primarily focuses on modeling extreme weather events, particularly the serial clustering of extratropical cyclones, using climate model outputs and statistical methodologies. His research interests lie in climate statistics , spatio-temporal modeling , and extreme event analysis , with applications to atmospheric dynamics and climate change impacts. He applies advanced statistical techniques to understand patterns in storm occurrences and their variability under changing climate conditions. The two available publications show a strong trend in analyzing extreme meteorological phenomena through rigorous statistical frameworks. His work emphasizes quantifying uncertainty, modeling dispersion in storm counts, and assessing the role of large-scale climate drivers such as the North Atlantic Oscillation. These studies contribute to improving risk assessments related to clustered extreme weather events in Europe and the North Atlantic region. Scientific Awards: No awards mentioned in the provided text. Advising and Grants: There is no information available regarding students advised or grants received. However, his active involvement in CMIP5-based research suggests potential participation in collaborative, funded climate science initiatives. Labs and Teams: While no formal lab or team structure is described, T. Economou collaborates with researchers from institutions such as the University of Reading and the University of Cologne, particularly within the context of multi-model climate analysis and extratropical cyclone dynamics.
Prof. Joanne Leal currently serves as Pro Vice Chancellor for Innovation and Academic Development at the Vice-Chancellor's Office and holds an interim role as Executive Dean of the School of Creative Arts, Culture and Communication at Birkbeck, University of London. Her academic focus spans German literature, cinema, and cultural studies with particular emphasis on post-reunification narratives, gender dynamics, and intercultural communication. Her research interrogates themes such as familial representation in media, migration experiences in urban spaces, and the ethical dimensions of contemporary German fiction. Notable works include co-editing Picturing the Family: Media, Narrative, Memory (2018), analyzing intercultural communication through cinema in The Cambridge Handbook of Intercultural Communication (2020), and examining generational conflicts in post-1968 German films. Teaching modules: The Arts: Perspectives and Possibilities (ARAR008S3), The Arts: Questioning the Contemporary World (ARAR009S3), and Arts, Humanities and the Lifecycle 1 (ARAR015S4) Advising: Currently supervising 3 doctoral researchers exploring German identity, post-GDR fiction, and generational novel studies Her contributions bridge interdisciplinary studies, emphasizing how cultural artifacts mediate memory, identity, and societal change.
Andrés Viña is an Associate Professor at Michigan State University (MSU), affiliated with the Department of Fisheries and Wildlife and the Center for Systems Integration and Sustainability. His work focuses on spatio-temporal vegetation dynamics and their impacts on human and natural systems, leveraging remote sensing technologies. Viña’s research bridges ecological processes with policy interventions, addressing global challenges like biodiversity conservation, climate change adaptation, and sustainable land use. His research interests include landscape dynamics, habitat modeling, and environmental policy, with a focus on tropical regions such as Brazil and China. He explores telecoupled systems—how distant human and environmental actions interconnect—through projects like analyzing soybean trade impacts on Amazon deforestation and climate-driven shifts in the Bering Sea. Viña’s publications often synthesize interdisciplinary approaches, combining field data with satellite imagery to inform conservation strategies. He emphasizes the need for integrated frameworks to tackle tri-sector challenges (biodiversity, climate, food security) and advocates for policies that balance economic demands with ecological preservation. Despite extensive research output, no specific scientific awards are listed, though his contributions to global environmental policy are widely recognized. His advising and grants focus on projects at the nexus of ecology, technology, and governance, though detailed grant information is not provided here. Viña is based at MSU’s Manly Miles Building and maintains an active research group within the College of Agriculture & Natural Resources.
Tobias Hönow, a Professor at the State Academy of Fine Arts Stuttgart , operates at the intersection of typography , semiotics , and media theory . His practice spans experimental typeface design , philosophical inquiry , and conceptual art production , often interrogating relationships between language systems and visual representation . Focus on indexical sign logic (diploma thesis basis) Innovative material investigations: stone dust ink , wood-based substrates Developed Starter (2018–2025), a linear neo-grotesque with 850 glyphs His 100+ design awards include the Akademiepreis and multiple TDC distinctions. Student projects like Erinnerungen / an die Hoffnung demonstrate his emphasis on material-semiotic interplay and historical contextualization in design education. 100 Beste Plakate (Germany/Austria/Switzerland) German Design Award Nominee Tokyo TDC Excellence
Changqing Lu serves as an ERCIM Fellow within the Stochastics department at Centrum Wiskunde & Informatica (CWI), specializing in the integration of spatial statistics and machine learning for environmental risk modeling. Primary research focuses on Dutch fire risk prediction using advanced point process methodologies. Lu's work bridges theoretical statistics with practical applications, particularly through tree-based algorithms like XGBoostPP for intensity function estimation. Key research domains include spatio-temporal point process modeling, environmental variable integration, and data-driven hazard assessment, with emphasis on chimney fire prediction in residential contexts. Recent publications (2022-2025) demonstrate consistent progression toward operational fire risk systems, combining journal articles in Journal of Computational and Graphical Statistics and Annals of Applied Statistics with conference presentations at the ISI World Statistics Congress. The research trajectory shows increasing methodological sophistication in machine learning applications for spatial risk modeling. Scientific recognition includes the competitive ERCIM Fellowship. No student advising records or additional awards are documented in current materials. Lu maintains active research collaboration with M.-C. van Lieshout and contributes to discussion papers in leading statistical journals.
Prof. Dr. Andreas Wieser is a Visiting Professor at ETH Zurich and a Full Professor at the Department of Civil, Environmental and Geomatic Engineering . His expertise lies in geodetic monitoring, sensor system development, and applications of laser scanning technologies in engineering and environmental contexts. Education: Habilitation in Applied Geodesy (Graz University of Technology, 2007) PhD in Geodesy (Graz University of Technology, 2001) Diploma in Geodesy (Vienna University of Technology, 1995) Andreas Wieser's research focuses on geodetic monitoring of structures and surfaces , terrestrial and hyperspectral laser scanning , and optimization of geodetic sensor systems . His recent publications emphasize applications in avalanche risk assessment, infrastructure deformation analysis, and radiometric calibration techniques. Key contributions include: Development of low-cost lidar monitoring systems for avalanche zones Advancements in automatic radiometric calibration for laser scanners Innovations in 3D displacement estimation with uncertainty quantification Scientific recognition includes: Karl-Rinner Award (Austrian Geodetic Commission, 2006) Erwin-Schrödinger Fellowship (Austrian Science Fund, 2003) Josef Krainer-Award for Young Scientists (Government of Styria, 2002) Multiple Best Presentation Awards at international conferences He has served as: Referee/Co-referee for over 30 doctoral theses Guest Professor at University of Stuttgart (2023) Leadership roles in academic commissions and editorial boards
Li Zhang is a Senior Academic Councillor and Group Leader at the Institute of Engineering Geodesy (IIGS) within the University of Stuttgart's Faculty 6: Aerospace Engineering and Geodesy. Her work focuses on holistic quality models for construction processes, low-cost GNSS monitoring systems , and multi-sensor fusion in infrastructure projects. She leads the Quality Modeling and Sensor Fusion group within the Cluster of Excellence IntCDC, which emphasizes integrative computational design for architecture. PhD in Geodesy (2016, University of Stuttgart) Specializes in GNSS error mitigation , construction process digitization , and digital map applications for transport security Her recent publications analyze geospatial data fusion for rock cliff monitoring, real-time quality assurance in residential construction, and cost-effective positioning for mobile manipulators. She supervises students on topics ranging from terrestrial laser scanning to indoor robot localization , balancing technical precision with sustainability. Li Zhang actively contributes to the FIG Working Group 5.6 "Cost Effective Positioning" and leads the DVW working group "Quality Assurance" . Her teaching portfolio includes courses on deformation analysis , multi-sensor systems , and statistical methods for engineering students.
Dr. Andy Lücking is a postdoctoral researcher at Goethe University Frankfurt, specializing in multimodal communication and cognitive semantics. He serves as Principal Investigator for the GeMDiS project within the ViCom SPP initiative, and previously held research fellowships at Université Paris Cité's Laboratoire de Linguistique Formelle and Frankfurt's Text Technology Lab. Current research focuses on neurocognitive semantics Developed iconic gesture theory with TTR/RTT frameworks Created multimodal corpora (FraGA, DoTT, TGVCorp) Active in computational educational linguistics Contributed to annotation tools (TextAnnotator, DependencyAnnotator) His work combines theoretical modeling with experimental methods, spanning over a decade of contributions to dialogue semantics, gesture-speech integration, and semantic role labeling. Recent projects explore VR-based multimodal research (Va.Si.Li-Lab) and diachronic dependency parsing. He has co-authored 20+ publications including proceedings in SemDial, LREC, and Springer HCI volumes. Collaboration network includes: Jonathan Ginzburg (dialogue theory), Alexander Mehler (computational linguistics), Alexander Henlein (VR research), and Max Planck Institute researchers. Key methodologies involve corpus creation, machine learning, and cognitive modeling of referential phenomena.
Professor Zhengyu Liu is a distinguished climate scientist at the University of Wisconsin-Madison's Department of Atmospheric and Oceanic Sciences. With an extensive publication record spanning nearly three decades (from 1989 to 2017), he has established himself as a leading researcher in climate dynamics and ocean-atmosphere interactions. His work bridges theoretical climate science with practical climate modeling applications, contributing significantly to our understanding of global climate systems. Professor Liu's research interests encompass a broad spectrum of climate science topics. He specializes in climate dynamics, with particular expertise in ocean-atmosphere interactions, paleoclimatology, monsoon systems, and climate modeling. His work on the Atlantic Meridional Overturning Circulation (AMOC) has provided critical insights into climate stability and potential tipping points. He has made significant contributions to understanding Bjerknes compensation mechanisms, El Niño-Southern Oscillation (ENSO) dynamics, and the complex interactions between tropical and extratropical climate systems. Analysis of Professor Liu's recent publications (2016-2017) reveals a continued focus on fundamental climate mechanisms while addressing pressing contemporary climate questions. His work demonstrates a consistent pattern of investigating climate feedbacks, ocean circulation dynamics, and regional climate responses to global changes. The research spans multiple temporal scales from seasonal to millennial, reflecting his comprehensive approach to climate science. His publications appear in top-tier journals including Science Advances, PNAS, Journal of Climate, and Nature Communications, indicating the high impact of his work within the climate science community. Professor Liu has maintained extensive collaborative networks throughout his career, working with researchers from institutions worldwide. His publications show consistent collaboration with scientists from Chinese institutions, suggesting strong international partnerships that have contributed to his research on Asian monsoon systems and regional climate phenomena. His work often integrates modeling approaches with observational data to advance our understanding of climate processes.
