Vadim Bulitko is a Professor in the Faculty of Science at the University of Alberta, affiliated with the Department of Computing Science. He holds a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign. Research Interests: His work spans heuristic search, program synthesis, and deep learning applications for sound. Recent projects focus on AI-driven puzzle generation, pathfinding in dynamic game environments, and neural network classification. Publications: His 15 most recent articles explore AI advancements in puzzle design, video-game navigation, and bioacoustic classification, emphasizing heuristic optimization and explainable AI techniques.
Dr. M. Montserrat Feu Lopez (also known as Montse Feu) is an Associate Professor of Spanish in the World Languages & Cultures department at Sam Houston State University, where she teaches courses ranging from intermediate Spanish language instruction to specialized topics including Spanish for Criminal Justice and Contemporary Spanish American Literature at both undergraduate and graduate levels. Dr. Feu earned her MA in Humanities Studies at Hood College and her PhD in Hispanic Studies at the University of Houston. She has also obtained graduate certificates in Language Teaching Pedagogy, Women's Studies, and Fascism, Modernity, and Politics, reflecting the interdisciplinary nature of her scholarly work. Her research focuses on US Hispanic print culture , with particular expertise in antifascist movements , Spanish Civil War exile communities , and Hispanic anarchism in the United States . Dr. Feu examines how Spanish-language publications served as vehicles for political expression, cultural preservation, and community building among Hispanic populations across American history. She curates the digital project "Fighting Fascist Spain—The Exhibits," which showcases historical materials related to antifascist movements and exile communities. Her scholarly trajectory reveals consistent engagement with how Hispanic communities in America have used print media to navigate identity, politics, and cultural expression across different historical periods—from early 20th century Spanish-language newspapers to contemporary issues of refugee experiences—demonstrating her commitment to documenting marginalized voices and political resistance through meticulous archival research. Her notable recognition includes: Research Society for American Periodicals Article Prize (2016) for "The US Hispanic Flapper: Pelonas and Flapperismo in Spanish-language Newspapers 1920-1929" Dr. Feu has co-edited significant scholarly works including "Histories and Cultures of Latinas: Suffrage, Activism, and Women's Rights" (2023), "Writing Revolution: Hispanic Anarchism in the United States" (2019), and "Serving Refugee Children: Listening to Stories of Detention in the USA" (2021), demonstrating her commitment to both historical scholarship and contemporary social issues. Through her curation of "Fighting Fascist Spain—The Exhibits," Dr. Feu has established an important digital resource for scholars and students interested in transnational antifascist movements, Spanish Civil War exile communities, and the role of print culture in political resistance.
Dr Jonny Huck is a Senior Lecturer in Geographical Information Science at the University of Manchester's Department of Geography. He holds additional roles as Honorary Professor at Gulu University, Uganda, and chairs several key groups including GISRUK National Steering Committee, Mapping & GIS Innovation Group, and Digital Humanities GIS Lead. His academic background includes a BSc (First Class) from Lancaster University, an MSc (Distinction) from the University of Leeds, and a PhD from Lancaster University. Research focuses on computational geography, particularly applying GIS to global health, environmental restoration, and urban segregation. Key interests include participatory GIS (PGIS), volunteered geographical information (VGI), and geographical simulation models. He developed the Map-Me PGIS platform and Shed Earth tool for geological analysis. Professional experience includes prior roles as Technical Manager in a UK wind farm developer and ongoing consultancy via Lune Geographic . Awards include three University of Manchester Making a Difference Awards for projects like Community Mapping Uganda and a Furness College Fellowship. His work aligns with UN SDGs related to health, environment, and innovation. Active in interdisciplinary projects such as the MEaSURE urban ecosystem initiative and Belfast Mobility Project analyzing sectarian spatial divides. Supervises research on prosthetics accessibility in Uganda and integrates AI with historical mapping data. Leads equipment management for the Small Uncrewed Aerial Systems facility.
Daniel Huttenlocher is the Dean of the MIT Stephen A. Schwarzman College of Computing and holds the Henry Ellis Warren (1894) Professorship in Computer Science and Artificial Intelligence + Decision-making (AI+D). He leads the interdisciplinary College of Computing while maintaining academic ties to the Electrical Engineering & Computer Science Department. His research focuses on AI ethics, societal impact of technology, machine learning applications, and vision systems. Key research areas include AI governance frameworks, adaptive public health strategies, and large-scale computer vision algorithms. He has pioneered work on decentralized collaboration systems, social media dynamics, and generative AI's societal implications. Huttenlocher’s recent publications address challenges in epidemic testing optimization and the evolving role of AI in knowledge ecosystems like Wikipedia. His leadership roles include steering MIT’s computing initiatives and fostering industry partnerships, such as the MIT Generative AI Impact Consortium. Despite no explicitly listed awards, his contributions to AI ethics and technical systems reflect significant academic influence. Advising and grant activities remain unspecified in available records. His work bridges technical innovation with societal challenges, emphasizing the ethical deployment of AI across healthcare, education, and digital economies.
Dr. Wenbin Li is a Senior Lecturer (Associate Professor) in Robotics at the University of Bath's Department of Computer Science. He leads the Pering Laboratory (Perceptual Intelligence Laboratory), affiliated with the AI & Machine Learning and Visual Computing groups. Previously, he held postdoctoral positions at Imperial College London (2016-2018) and UCL (2014-2016), and earned his PhD from the University of Bath in 2013, with earlier degrees from Imperial College London (MSc, 2009) and Xidian University (B.Eng, 2008). His research focuses on unified autonomous systems, including multi-sensory localization/mapping, dynamic motion capture, and uncontrolled scene understanding with applications in manufacturing and professional capture. Key areas include Robotics, Computer Vision, Graphics, and Machine Learning. He actively supervises doctoral students in these fields and has funded PhD openings. Dr. Li has been involved in major initiatives such as the My World - Strength in Places Fund (2021–2027), SLAM with Reinforcement Learning (2022–2023), and the CAMERA MC2 Award (2019–2023). His work aligns with UN Sustainable Development Goals, particularly in advancing technology for societal benefit. Recent publications emphasize aerial robotics, autonomous systems, and computer vision applications, including UAV package delivery reviews, Bayesian optimization for balloon station-keeping, and generative models for intrinsic image decomposition.
John Rinzel is a Professor of Neural Science and Mathematics at New York University, affiliated with the Center for Neural Science and the Courant Institute. He holds academic positions within the College of Arts and Science and the Graduate School of Arts and Science. His research focuses on computational neuroscience, integrating biophysical mechanisms with mathematical modeling to understand neural computations at cellular and network levels. Education: Ph.D. in Mathematics (1973) and M.S. in Mathematics (1968) from NYU’s Courant Institute, and a B.S. in Engineering from the University of Florida (1967). Ph.D. in Mathematics, NYU Courant Institute (1973) M.S. in Mathematics, NYU Courant Institute (1968) B.S. in Engineering, University of Florida (1967) Research Interests: Rinzel studies biophysical mechanisms underlying neural computations, including dendritic computation, neuronal excitability, auditory pathway modeling, perceptual bistability, and rhythmic timing. His work combines theoretical models with experimental collaborations, emphasizing reduced biophysical models for cellular and network-level dynamics. Recent research trends include auditory streaming, perceptual dynamics, and rhythmic beat generation in music. His models explore gamma oscillations, thalamic spindle rhythms, and sleep-related neural excitability. Publications highlight applications in sensory processing, neural network oscillations, and cognitive functions like attention and memory coordination. No scientific awards explicitly listed. Rinzel leads a research group focusing on computational neuroscience, collaborating on projects involving auditory neuroscience, mathematical biology, and theoretical neurophysiology. His lab is part of NYU’s Center for Neural Science, fostering interdisciplinary approaches to brain function.
Kerstin Bunte is a Professor of Machine Learning for interdisciplinary data analysis at the University of Groningen, affiliated with the Faculty of Science and Engineering and the Bernoulli Institute's Intelligent Systems Group. She holds an Honorary Fellowship at the University of Birmingham and leads the Intelligent Systems Group. Her research focuses on interpretable machine learning, interdisciplinary applications (e.g., astrophysics and biomedical data), and visualization techniques. Research Interests: - Machine Learning - Artificial Intelligence - Explainable AI (XAI) - Interpretable Models - Dimensionality Reduction - Data Visualization - Astrophysical Data Analysis - Medical Imaging Awards & Grants: - DSSC XS funding (2023) - NWO VIDI grant (2020) - Rosalind Franklin Fellowship (2016–present) Advising & Students: Supervised PhD students include Elisa Oostwal, Janis Norden, Matteo Marcantoni, and Petra Awad. Research spans topics like tumor segmentation in medical imaging, astrophysical structure detection, and autonomous navigation systems. Labs & Collaborations: Leads the Intelligent Systems Group, collaborating with institutions like the University of Birmingham and the University of Warwick. Work involves interdisciplinary projects combining machine learning with astronomy, biomedical sciences, and robotics.
Prof. Dr. Sascha Schneider is an Assistant Professor of Educational Technology at the University of Zurich's Institute of Educational Science, affiliated with the Digital Society Initiative (DSI). His research focuses on optimizing digital learning media design to enhance cognitive, emotional, and motivational processes in education. He holds a PhD in Media and Instructional Psychology and has held postdoctoral positions at TU Chemnitz. His work investigates topics like decorative elements' impact, motivational effects of choice, emotional design, and adaptive learning environments, targeting K-12 students, university learners, and adults. Education: Bachelor's: Educational Science & English, University of Erfurt Master's: Continuing Education & Educational Technology, University of Erfurt PhD: Media and Instructional Psychology, TU Chemnitz (2017) Habilitation: Educational Psychology, TU Chemnitz (2022) His research emphasizes experimental and meta-analytical methods to explore multimedia learning theory extensions, including social processes and instructional design principles. Key projects include the DEEP initiative for differentiated instruction and the LiT+ educational transfer program. Prof. Schneider's awards include the Erik De Corte Award (2021), a Dissertation Prize (2019), and the Commerzbank Prize (2018). He actively contributes to academic communities, organizing conferences and serving on editorial boards. Advising & Grants: Supervises doctoral research in educational technology Leads projects funded by BMBF and Swiss National Science Foundation His team at the Chair of Educational Technology collaborates on labs like NARRATID , focusing on narrative-driven instructional design.
Dr Luca Manneschi is a Lecturer in Machine Learning at the School of Computer Science, University of Sheffield, with an IBM Liaison role. He holds a PhD in Physics from the University of Sheffield (2021) and completed a PostDoc there before his current position since March 2022. His research focuses on designing learning algorithms inspired by biological networks for physically defined systems, emphasizing neuromorphic computing, reservoir computing, and stochastic environments. Education: Bachelor's in Physics: University of Padua (Italy) Master's in Physics: Sapienza University of Rome (Italy) PhD in Physics: University of Sheffield (2021) Research Interests: Dr. Manneschi explores algorithms for physically defined networks, leveraging biological network principles to enhance computation in dynamic environments. His work bridges machine learning with neuromorphic hardware, emphasizing adaptability and energy efficiency. Key areas include reservoir computing, magnetic metamaterials, and multi-timescale learning strategies. Grants & Funding: "Real-time Reservoir Computing on Prosthetic Devices" (2023–2025, Royal Society, PI) "MARCH: Magnetic Architectures for Reservoir Computing Hardware" (2021–2025, EPSRC, Co-PI) "CausalXRL: Causal Explanations in Reinforcement Learning" (2021–2024, EPSRC, Co-PI) "ActiveAI" (2019–2024, EPSRC, Co-PI) Lab/Team Affiliation: Machine Learning Research Group, School of Computer Science.
Dr. Michael Burke is a Senior Lecturer and Deputy Graduate School Coordinator at the Department of Electrical and Computer Systems Engineering, Monash University. He specializes in robotics, focusing on probabilistic machine learning and computer vision for autonomous systems. His roles include research supervision, curriculum development, and fostering graduate culture. Education: PhD in Statistical Signal Processing, University of Cambridge (2012–2016) MSc in Electronic Engineering, Stellenbosch University (2009–2011) BEng in Electronic Engineering, University of Pretoria (2005–2008) Research Interests: Robot learning and control Probabilistic machine learning for robotics Interpretable robotics systems and hybrid control architectures Robot perception and visuomotor control His work bridges robotics with machine learning to develop safe, adaptive autonomous systems for applications like surgical robotics and field robotics. Awards and Recognition: Best Paper Award at AMDO 2014 Runner-Up for Best Paper at CoRL 2019 Advising & Grants: Supervising over 20 PhD and Master’s students in robotics and related fields Principal Investigator for ARC-funded projects on robotic pharmaceutical formulation and human-robot interaction (2024–2027) Labs and Teams: Past leadership of the Mobile Intelligent Autonomous Systems group at CSIR, South Africa (2009–2018) Current collaborations with researchers at the University of Edinburgh and University of Melbourne
Hassan Karimi is a Professor at the University of Pittsburgh's School of Computing and Information, Department of Informatics and Networked Systems. His research focuses on Geoinformatics, Machine Learning, Location-Based Services, and Navigation Applications, with expertise in Mobile Computing and Distributed/Parallel Computing. He holds a Ph.D. in Geomatics Engineering from the University of Calgary, along with an MS in Computer Science from the University of Calgary and a BS in Computer Science from the University of New Brunswick. His research interests encompass computational geometry, geospatial data science, and smart city technologies. Notable contributions include methodologies for obstacle detection for visually impaired navigation, collaborative wayfinding systems, and spatiotemporal activity prediction. He leads the Geoinformatics Laboratory, which explores geospatial data science, mobile computing, and navigation systems. Key publications include works on geospatial data science techniques, navigation systems, and machine learning applications. His lab develops technologies for autonomous vehicles, environmental monitoring, and precision agriculture. He is the author of several books, including *Geospatial Data Science Techniques and Applications* (Taylor & Francis, 2018) and *Big Data: Techniques and Technologies in Geoinformatics* (Taylor & Francis, 2014). His work bridges theoretical research and practical applications, addressing challenges in smart cities, environmental sustainability, and health informatics. The Geoinformatics Lab collaborates on projects such as sensor networks, spatial data mining, and geovisualization.
Yaoping Hu is a Professor in the Department of Electrical and Software Engineering at the Schulich School of Engineering, University of Calgary, and an Associate Member of the Hotchkiss Brain Institute. He holds a Ph.D. in Robotics and Neuroscience from the University of Western Ontario. His research focuses on Human-Computer Interaction within Virtual Environments, particularly in Brain-Machine Interfaces, multisensory user interaction in XR, and immersive analytics. He teaches courses such as ENSF 619.36 (Brain-Machine Interface Systems), ENSF 519.51 (Brain-Machine Interfaces), ENEL 602 (Virtual Environments), and ENSF 545 (Introduction to VR). Research interests include modeling neural mechanisms for visuomotor processes, cognitive-ergonomic interaction design, and applications in surgical planning, data visualization, and human-machine collaboration. He leads the Visualization and Interaction Laboratory, collaborating with institutions like the neuroArm Project, Fluid Dynamics Group, and international partners in France. Past and current students include Stanley Tarng, Lida Ghaemi Dizaji, and Aida Erfanian. His work spans projects like neuroSim (a surgical simulator) and BioVista (biofilm visualization tools). Collaborations with industry partners such as Nova Chemicals and Calgary Scientific Inc. support applied research in complex data analysis and virtual reality systems.
Serra Favila is an Assistant Professor in the Department of Cognitive and Psychological Sciences at Brown University, affiliated with the Carney Institute for Brain Science. She holds a BA in Human Biology from Stanford University and a PhD in Psychology from New York University, followed by postdoctoral training at Columbia University. Her research focuses on the neural mechanisms underlying episodic memory, employing methods such as functional neuroimaging, intracranial recordings, behavioral measurements, eye-tracking, and computational modeling. She teaches CLPS 1480I: Memory, Space, and the Hippocampus. Dr. Favila's work investigates how humans form flexible yet durable memories, emphasizing the interaction between environmental cues, cognitive goals, and neural processes. Her lab explores memory’s selectivity and susceptibility to interference, with implications for understanding how memory shapes future behavior. Key topics include hippocampal contributions to spatial and temporal memory, neural remapping, and memory-guided navigation. Her articles span themes like hippocampal mechanisms for resolving memory competition, visual cortex contributions to recall success, and neural underpinnings of spatial perception. She maintains an active lab website detailing ongoing projects and collaborates across disciplines to advance cognitive neuroscience. Office hours are held Mondays from 4-5pm in Metcalf Research 245.
Dora Biro is the Beverly Petterson Bishop and Charles W. Bishop Professor of Brain and Cognitive Sciences at the University of Rochester, serving as Interim Chair of the Department of Brain and Cognitive Sciences. Her research focuses on animal cognition, collective behavior, and decision-making in primates and other species. Key interests include navigation, tool use, social learning, and animal culture. She leads studies in Gorongosa National Park, Guinea-Bissau, and other野外 environments, employing deep learning technologies for behavior analysis and social network mapping. Research emphasizes primate behavioral ecology, particularly in chacma baboons and chimpanzees, exploring how environmental factors (e.g., predation, seasonality) shape social and foraging strategies. She investigates cumulative culture in animal groups, collective intelligence, and cognitive evolution through tool-use studies. Her work bridges neuroscience, ecology, and anthropology. Education: Not explicitly stated in provided text. Affiliations: School of Arts & Sciences, Department of Brain and Cognitive Sciences, University of Rochester. Recent studies analyze leadership hierarchies in homing pigeons, collective learning dynamics, and the impact of human activity on wildlife behavior. She collaborates on projects involving genomic analysis of baboon populations and fossil records in Mozambique. Her lab integrates field observations with computational models to explore emergent behaviors in animal groups.
Renate Delucchi Danhier is a researcher at the Faculty of Cultural Studies, Technical University of Dortmund, where she has held positions as Temporary Academic Councilor (2018–2026) and Research Assistant (2015–2018). She holds a Ph.D. in Comparative Linguistics from Heidelberg University and an M.A. in German as a Foreign Language, Classical Archaeology, and Egyptology. Doctorate: Comparative Linguistics, Heidelberg University (2015) Master of Arts: German as a Foreign Language Philology, Classical Archaeology, Egyptology, Heidelberg University (2008) Her research focuses on psycholinguistics, multilingualism, bilingual education, language and cognition, and the role of language in inclusion. She investigates how linguistic structures affect perception, particularly in spatial and educational contexts. Her work often integrates eye-tracking methodologies and interdisciplinary collaboration, especially with Barbara Mertins. The 15 most recent publications reveal a strong trend in psycholinguistics, with emphasis on comparative analysis of German and Spanish, syntactic features in educational texts, and multilingual cognition. Her recent work extends into data visualization and diversity in cognition, showing a growing interest in humanistic data representation. She has contributed to significant interdisciplinary projects such as 'Psycholinguistic Foundations of Inclusion' and co-edited special issues on diversity in cognition. Renate Delucchi Danhier has not received any explicitly mentioned scientific awards. She has not listed any advisees or students. There is no information about labs or research teams she leads, but her collaborative publications suggest active participation in research groups focused on language, cognition, and education.
