Find Academic Supervisors

Shuhao FuView profile

Research Fellow

• Machine Learning
• Cognitive Science
• Relational Reasoning
• +3 more

Shuhao Fu is a Program Postdoctoral Fellow at the Santa Fe Institute (SFI) researching the intersection of machine learning and cognitive science. He completed his Ph.D. in Psychology at UCLA under advisors Hongjing Lu and Ying Nian Wu, following a B.S. in Computer Science and Mathematics from Hong Kong University of Science and Technology. His research examines human-like relational reasoning in AI systems through cognitive modeling and computational approaches. Research focuses on: Bridging human-machine reasoning gaps via analogical mapping Developing explicit relational representations in vision models Structural cognitive modeling for compositional understanding Multimodal reasoning and scene interpretation Relational knowledge representation in biological and artificial systems Publication trends show concentrated work in computational cognitive science (2021-2025), with evolving focus from visual analogy fundamentals to applications in 3D recognition, social interaction modeling, and mental health diagnostics. Recent work demonstrates increased emphasis on transformer architectures, multimodal integration, and human-AI comparative studies. Professional experience includes research internships at Google X and Mineral.ai, with prior affiliation at Johns Hopkins University's CCVL lab under Alan Yuille. Currently serves as reviewer for ICML, ICCV, and Cognitive Science Society conferences.

Irene V. SmallView profile

Professor

• Contemporary Art
• Latin American Art
• Art Criticism
• +4 more

Irene V. Small is a Professor in the Department of Art & Archaeology at Princeton University, specializing in contemporary art and criticism within global and transnational contexts. Her work critically engages with experimental practices from the 1960s–1970s, legacies of abstraction, and the social implications of form, with concentrated focus on Latin American art—particularly Brazil. She actively contributes to interdisciplinary initiatives including the Program in Media and Modernity, the Brazil Lab, and the Program in Latin American Studies. Her research traverses radical pedagogy, expanded cinema, decolonial interventions, and the politics of medium specificity. Central to her scholarship is the interrogation of modernism’s topological field through concepts like Lygia Clark’s 'organic line,' which she deploys to analyze works ranging from Malevich’s Black Square to contemporary practices. She investigates how truncated media forms facilitate itinerancy and connectivity across Brazilian art history, from 19th-century proto-photography to digital remediation. Small’s publications reveal consistent engagement with Brazilian avant-garde movements, examining artists like Hélio Oiticica, Lygia Clark, and Tarsila do Amaral through frameworks of participation, embodiment, and geopolitical critique. Her recent work expands to address free speech, afterlives of slavery, and the decolonization of art institutions, demonstrating evolving focus on art’s capacity to reconfigure social and political realities. Scientific Awards and Grants: Francine and Sterling Clark Art Institute Fellowship Graham Foundation Fellowship Getty Research Foundation Fellowship Dedalus Foundation Fellowship Creative Capital and Andy Warhol Foundation Arts Writers Grant Lemann Institute of Brazilian Studies Fellowship Research Board of the University of Illinois at Urbana-Champaign Grant Small serves on advisory boards for October , Ars , and Texte zur Kunst , and has curated exhibitions including Blind Field (2013) and Multitude (2002). Her teaching spans global contemporary art surveys, modern/contemporary Latin American art, and specialized seminars on decoloniality, gender, and experimentalism. She is affiliated with Princeton’s Department of Spanish & Portuguese, Brazil Lab, Gauss Seminars in Criticism, and Edward Said Memorial Lecture series.

Alla ShefferView profile

Professor

• Geometry Processing
• Computer Graphics
• Discrete Geometry
• +7 more

Alla Sheffer is a Professor and Associate Head of Faculty Affairs in the Department of Computer Science at the University of British Columbia, Faculty of Science. She is affiliated with multiple research centers including CAIDA (Centre for Artificial Intelligence Decision-making and Action), the Institute of Applied Mathematics, and ICICS (Institute for Computing, Information and Cognitive Systems). B.Sc., Hebrew University, Jerusalem (1991) M.Sc., Hebrew University, Jerusalem (1995) Ph.D., Hebrew University, Jerusalem (1999) Postdoctoral Research Associate, University of Illinois, Urbana-Champaign (1999-2001) Assistant Professor, Technion, Israel (2001-2003) Assistant Professor, University of British Columbia (2003-2008) Associate Professor, University of British Columbia (2008-present) Professor Sheffer's research focuses on geometry processing, addressing algorithmic challenges in digital shape modeling and manipulation. Her work primarily deals with discrete geometry representations, specifically meshes (polygonal model representations), with applications in computer graphics and computer-aided engineering. She utilizes tools from computational and differential geometry, discrete mathematics, and graph theory to generate, manipulate, and edit discrete geometric models. Her research spans virtual and augmented reality, visual computing, and 3D modeling, with significant contributions to sketch-based modeling, mesh processing, and cloth simulation. The 15 most recent publications reveal a consistent research trajectory in geometry processing, with recent work focusing on vector sketch processing, VR drawing tools, and advanced mesh manipulation techniques. Her work demonstrates a strong connection between human perception and computational methods, particularly in the interpretation of freehand sketches and the generation of perceptually-accurate geometric representations. The recurring themes across her publications include flowlines, curve networks, mesh parameterization, and the application of perceptual studies to improve algorithmic outputs. Eurographics Fellow ACM Fellow IEEE Fellow Royal Society of Canada Fellow SIGGRAPH Academy Member UBC Killam Research Prize NSERC Discovery Accelerator Supplement IBM Faculty Award Professor Sheffer has supervised numerous doctoral and master's students, with recent theses focusing on geometric mesh processing, vector sketch interpretation, VR drawing tools, and garment modeling. Her research group maintains strong connections with industry through various partnerships and has received substantial grant funding to support their innovative work in geometry processing and computer graphics. She teaches courses in computer graphics, geometric modeling, and video game programming, contributing significantly to both undergraduate and graduate education in computer science.

Michael BenzaquenView profile

Research Professor

• Statistical Physics of Complex Systems
• Hydrodynamics at Interfaces
• Econophysics
• +3 more

Michael Benzaquen is a CNRS Research Scientist and accredited research director (HDR) based at École Polytechnique, where he founded and currently holds the Chair of Econophysics & Complex Systems. He is affiliated with LadHyX (UMR CNRS 7646), a research laboratory focused on hydrodynamics and complex systems at the intersection of physics, economics, and social sciences. Dr. Benzaquen's research spans multiple interdisciplinary fields, with primary interests in: Statistical physics of complex systems Hydrodynamics at interfaces Econophysics and quantitative finance Socio-physics and behavioral modeling Applications of physics to economics and social sciences Physical approaches to market microstructure and price formation His work demonstrates a unique methodology applying physical principles to understand complex phenomena in financial markets, social dynamics, and ecological systems. Dr. Benzaquen has made significant contributions to understanding market impact, price formation, and the statistical properties of economic systems from a physics perspective, while also maintaining strong research in fundamental fluid dynamics and interfacial phenomena. Analysis of Dr. Benzaquen's extensive publication record reveals a consistent trend toward interdisciplinary integration, with recent work increasingly bridging statistical physics, econophysics, and complex systems theory to address real-world problems. His publications span from fundamental research on ship wakes, liquid crystals, and thin films to applied studies in quantitative finance, ecological economics, and social dynamics, demonstrating remarkable breadth while maintaining methodological coherence through statistical physics approaches. As an accredited research director (HDR), Dr. Benzaquen supervises PhD students and postdoctoral researchers, leading an active research group focused on econophysics and complex systems. His group maintains strong collaborations across disciplines and regularly publishes in high-impact journals spanning physics, finance, and interdisciplinary sciences. The group's work is supported by various research funding sources enabling ambitious projects at the intersection of physics and social sciences. Dr. Benzaquen's laboratory at LadHyX brings together researchers from diverse backgrounds including physics, mathematics, economics, and computer science to tackle complex problems using quantitative approaches. His research has practical applications in financial market regulation, ecological conservation, and materials science, reflecting the real-world impact of his interdisciplinary methodology.

• Robotics
• Artificial Intelligence
• Tactile Sensing
• +6 more

Satoshi Funabashi is an Assistant Professor in the Department of Intermedia Art and Science at Waseda University's School of Fundamental Science and Engineering, Japan. He is affiliated with the Graduate Program for Embodiment Informatics under Waseda University's Program for Leading Graduate Schools and contributes to multiple graduate schools including the Graduate School of Creative Science and Engineering. Education: Doctor of Engineering (Waseda University, 2017-2021) Research Focus: Robotics, tactile sensing, deep learning, and embodiment informatics Academic Appointments: Assistant Professor (non-tenure-track) His research centers on symbiotic robotics and tactile-driven manipulation, with recent publications exploring graph convolutional networks, vision-touch fusion, and morphology-specific deep learning for robotic hands. He has secured multiple competitive research grants including JSPS KAKENHI and JST ACT-I programs. Scientific Awards: Grant-in-Aid for Scientific Research (B) (KAKENHI), JSPS (2024-2027) Grant-in-Aid for Early-Career Scientists, JSPS (2022-2024) JST ACT-I Research Fellow (2020-2022, 2018-2020) JSPS Research Fellowship DC1 (2017-2020) He collaborates with the Intelligent Dynamics and Representation Lab (Prof. Tetsuya Ogata) and the Intelligent Machine Lab (Prof. Shigeki Sugano) at Waseda University. He has interned at MIT's CSAIL (2018-2019) and conducted research at UC Davis (2015). His work has been cited over 500 times with an h-index of 14 according to Google Scholar.

• Computer Graphics
• Computer Vision
• Augmented Reality
• +3 more

Aditi Majumder is a Professor of Computer Science at the University of California, Irvine (UCI), affiliated with the School of Engineering and Information Sciences. Her research focuses on multi-projector display systems, augmented reality (AR), and their applications in scientific and medical fields. She holds a Ph.D. from the University of North Carolina, Chapel Hill (2003). Her work addresses challenges in geometric, chromatic, and luminescent corrections for tiled displays, with applications in surgical assistance and deformable surface visualization. Recent projects include precision stencils for surgical sites and dynamic projection mapping on non-rigid surfaces. Notable achievements include the Inaugural Hasso Plattner Endowed Chair in Artificial Intelligence (2025). Her research spans AR in medicine, real-time multi-projector synchronization, and color gamut optimization. Dr. Majumder also engages in public discourse on computer science education, emphasizing its societal importance and foundational skills like programming and discrete mathematics. Her 15 most recent articles (2021–2024) highlight advancements in surgical AR, deformable surface projection systems, and medical visualization. These contributions bridge computer graphics, vision, and biomedical engineering, reflecting her interdisciplinary approach to solving complex display and interaction challenges.

• Perception Engineering
• Extended Reality
• Virtual Reality
• +7 more

Mark Bo Jensen is an Assistant Professor (tenure track) at the Department of Engineering Technology and Didactics, Technical University of Denmark (DTU), specializing in Energy Technology and Computer Science. His research is centered on Perception Engineering and Extended Reality technologies, particularly Virtual Reality (VR), with applications in human cognition, computer graphics, and scientific visualization. His research interests lie at the intersection of engineering and cognitive sciences, focusing on creating immersive and convincing extended reality experiences. Jensen applies his over 10 years of expertise in real-time computer graphics to advance VR systems for perception modeling, geometric data visualization, and material appearance simulation. His work contributes to fields such as medical diagnostics, 3D annotation, and photorealistic rendering. The recent publications highlight a strong trend in leveraging VR for scientific tasks, such as anatomical landmark annotation and visual field testing, as well as advancing core graphics techniques like meshlet optimization and diffusion-based stereo image generation. His research integrates computer vision, graphics algorithms, and human-centered design. While no scientific awards are currently listed, his active participation in research projects and consistent publication output indicate a growing academic profile. He has contributed to interdisciplinary collaborations involving medical, biological, and engineering domains. Jensen has been involved in advising and research projects, including serving as a PhD student in the 'Virtual Reality-Based Visualization of Geometric Data' project and currently as a project participant in 'AL-EYE: The Visual Aid'. These projects reflect his focus on applied VR solutions and data understanding. His work is conducted within the Energy Technology and Computer Science division at DTU, where he contributes to advancing perception-driven technologies and their practical implementation in scientific and medical contexts.

Tyson Govan PhillipsView profile

Senior Lecturer

• Autonomous Systems
• Robotics
• Mining Automation
• +4 more

Dr. Tyson Phillips serves as Senior Lecturer and Director of Teaching and Learning at The University of Queensland's School of Mechanical and Mining Engineering within the Faculty of Engineering, Architecture and Information Technology. He is an active Affiliate of the Future Autonomous Systems and Technologies research group, focusing on translating robotics innovations into practical mining applications. His academic leadership includes curriculum development for engineering programs and direct industry engagement with major mining equipment manufacturers. He earned his Doctor of Philosophy (PhD) from The University of Queensland in 2016, with thesis research centered on LiDAR-based perception systems for autonomous excavators. His doctoral work established foundational methods for object pose verification in mining contexts. Phillips' research specializes in robotics perception for extreme mining environments, developing LiDAR-centric solutions for autonomous equipment operation amid dust, fog, and unstructured terrain. Key contributions include evidential reasoning frameworks for uncertainty management, real-time pose estimation algorithms, and sensor fusion techniques for excavators and bulldozers. His work bridges theoretical computer vision with industrial deployment, targeting operational safety and efficiency in mineral extraction. Publication analysis reveals consistent focus on mining robotics since 2012, with recent works (2021-2024) emphasizing minimal-sensor configurations, probabilistic terrain mapping, and vibration-assisted gripper technology. His 14 scholarly outputs demonstrate evolution from sensor evaluation (2012-2015) toward integrated autonomy systems (2018-2024), predominantly in Journal of Field Robotics and Sensors . He actively supervises graduate researchers as Principal Advisor for a PhD on multimodal perception mapping and Associate Advisor for two PhD projects involving spreader systems and physics-informed neural networks. Completed supervision includes a 2024 PhD on bulldozer terrain mapping and a 2021 Master's on shovel/hopper interaction strategies. Research funding spans 14 projects from 2012-2026, including current Australian Coal Association Research Program support (2025-2026) and major Caterpillar Inc. collaborations for ERS self-protection and articulated truck automation. Phillips operates within The University of Queensland's Future Autonomous Systems and Technologies group, which develops field-deployable autonomy solutions for mining partners. This team conducts real-world testing of perception systems using Caterpillar and FMG operational sites as validation environments.

Jacob WhitehillView profile

Associate Professor

• Applied Machine Learning
• Speech and Speaker Recognition
• Educational Data Mining
• +3 more

Jacob Whitehill is an Associate Professor in the Department of Computer Science at Worcester Polytechnic Institute (WPI), affiliated with the Learning Science & Technologies (LST) program. His research focuses on applying machine learning to education and human-computer interaction, including speech recognition, emotion analysis, and automated classroom observation. He leads the NSF-funded project Developing New Scientific Instruments for Classroom Observation and collaborates on the AI Institute for Student-AI Teaming (iSAT) . His research interests span Applied Machine Learning (e.g., multi-modal systems, speaker diarization), AI for Education (e.g., automated instructional evaluation, child speech recognition), and Emotion Recognition (e.g., affective computing in classrooms). Recent work emphasizes classroom observation tools and improving student-teacher interaction analysis through video and audio data. Notable projects include: NSF-funded classroom observation tools AI Institute for Student-AI Teaming (iSAT) Schmidt Futures-funded Hybrid Human-Agent Tutoring for math education His team includes PhD students Xinlu He (Data Science), Jiani Wang (Computer Science), and Yiwen Guan (Computer Science), along with visiting scholar Cecilia Tivir. He advises students on topics like speaker recognition, educational data mining, and computer vision in classroom settings. Grants and collaborations include NSF, Schmidt Futures, and industry partnerships. His lab develops tools for automated feedback on teaching practices, leveraging LLMs and multimodal data. For more details, contact jrwhitehill@wpi.edu .

Jean PonceView profile

Professor

• Computer Vision
• Machine Learning
• Robotics
• +3 more

Jean Ponce is a Professor of Computer Science at Ecole Normale Superieure (ENS) in Paris and a Part-Time Global Distinguished Professor at New York University's Courant Institute of Mathematical Sciences and Center for Data Science (CDS). He previously served as Director of the ENS Computer Science Department (2011-2017) and held positions at Inria (2017-2022), University of Illinois at Urbana-Champaign (1998-2006), MIT, Stanford, and Inria (1982-1985). Academic Leadership: Scientific Director of PRAIRIE Interdisciplinary AI Research Institute in Paris Startup Involvement: Co-founder and CEO of Enhance Lab (2022) Editorial Roles: Senior Editor-in-Chief of International Journal of Computer Vision (2019-2022) Conference Leadership: Chair of IEEE CVPR (1997,2000), ECCV (2008), and upcoming ICCV (2023) Research Focus: Computer vision, machine learning, robotics, and AI with applications in exoplanet imaging, 3D reconstruction, and image quality assessment. His work bridges statistical learning and deep learning approaches. Awards: IEEE Fellow (2003) ELLIS Fellow (2019) ERC Advanced Grant (2011) IEEE CVPR Longuet-Higgins Prizes (2016,2020) ICML Test-of-Time Award (2019) Patents & Publications: Co-author of influential textbook Computer Vision: A Modern Approach (translated into Chinese, Japanese, Russian). Holds two US patents and one pending French patent. Google Scholar h-index of 78 with over 55,000 citations.

Diego PatiñoView profile

Assistant Professor

• Machine Learning
• Geometric Computer Vision
• 3D Reconstruction
• +7 more

Diego Patiño is an Assistant Professor in the Department of Computer Science and Engineering at the University of Texas at Arlington (UTA), a position he began in September 2024. He earned his Ph.D. in Computer Engineering from the National University of Colombia in 2020, following M.S. and B.S. degrees from the same institution. Prior to joining UTA, he served as a Postdoctoral Fellow at Drexel University and a Postdoctoral Researcher at the GRASP Laboratory, University of Pennsylvania. B.S. in Computer Engineering, National University of Colombia, 2010 M.S. in Computer Engineering, National University of Colombia, 2012 Ph.D. in Computer Engineering, National University of Colombia, 2020 Dr. Patiño's research centers on geometric computer vision and machine learning, with applications in robotics and 3D vision. His primary interests include 3D reconstruction, graph neural networks, symmetry detection, physics-informed machine learning, and reinforcement learning. He develops algorithms that integrate geometric priors and physical constraints into deep learning models to improve robustness and generalization in real-world robotic systems. His recent publications demonstrate a strong trend in leveraging implicit neural representations for 3D shape reconstruction, applying graph neural networks to swarm robotics, and enhancing computer vision tasks with self-supervised and physics-informed learning. Work spans high-impact venues such as IEEE RA-L, ICRA, ICPR, and MICCAI, showing a consistent focus on geometric reasoning, robotic perception, and medical imaging applications. His scientific contributions have been recognized with awards from the UTA Division of Student Affairs for exceptional dedication and positive impact (2024 and 2025). He is actively involved in securing research funding, with multiple grants under review from NSF, Air Force SBIR, and industry partners like Sony. Exceptional dedication and positive impact recognition, UTA Division of Student Affairs (December 9, 2024) Exceptional dedication and positive impact recognition, UTA Division of Student Affairs (April 30, 2025) Dr. Patiño advises and serves on committees for multiple graduate students in computer science and engineering, including doctoral and master’s candidates. He is also leading or co-leading several research grants under review, covering topics such as aerial swarm navigation, neuromorphic sensing, and industrial computer vision. He teaches graduate courses in computer vision and is involved in service roles including PhD admissions and faculty appointments committees. He is affiliated with research initiatives at UTA, including the UTARI Research Institute, where he has presented on geometric modeling and physics-informed learning. His lab focuses on developing next-generation computer vision algorithms for robotics, industrial inspection, and safety-critical systems.

Hamidreza MahyarView profile

Assistant Professor

• Machine Learning
• Network Science
• Natural Language Processing
• +3 more

Hamidreza Mahyar is an Assistant Professor at the Faculty of Engineering , McMaster University , and an Associate Member of the Computing and Software department. His academic journey includes postdoctoral work at Boston University and TU Wien , and a Ph.D. in Computer Science from Sharif University of Technology . Research Focus: Mahyar's work bridges machine learning and network science , emphasizing graph neural networks for applications in social networks , recommendation systems , drug discovery , and generative AI . His research spans industrial AI (Industry 4.0 projects at Infineon Technologies), biomedical engineering (organoid morphology analysis), and semiconductor manufacturing (wafermap modeling). Scientific Recognition: McMaster Teaching Merit Award (2022) Vector Scholarship in AI (2023) NSERC USRA Award (2022) Google Cloud Platform for Research Award (2018) Best Paper Selection, Complex Networks (2018) Academic Leadership: He mentors PhD students (Taraneh Ghandi) and MSc students (Reza Namazi, Mohammad Khodadad, Ali Shiraei), while leading AI initiatives at Mind Lab 56 and BrainMaven . Former mentees include industry leaders at Google, Accenture, and ETH Zurich.

• Perception Engineering
• Extended Reality
• Virtual Reality
• +7 more

Mark Bo Jensen is an Assistant Professor (Tenure track) at the Department of Engineering Technology and Didactics, Energy Technology and Computer Science at the Technical University of Denmark (DTU). His work bridges engineering and cognitive sciences through the emerging field of Perception Engineering. His research focuses on Extended Reality (XR) and Virtual Reality (VR) technologies to model and understand human perception and cognition. With over 10 years of expertise in real-time computer graphics, he develops immersive systems for applications in data visualization, medical testing, and geometric morphometrics. His recent publications highlight a strong trend in leveraging VR for precise human interaction tasks, such as anatomical landmark annotation and visual field testing, as well as advancing rendering techniques using diffusion models and mesh optimization. This reflects a multidisciplinary approach combining computer science, perception, and real-world applications. He has contributed to multiple research projects, including AL-EYE: The Visual Aid and Virtual Reality-Based Visualization of Geometric Data, where he served both as a PhD student and a project participant. These projects emphasize VR-based tools for data understanding and visualization. Assistant Professor (Tenure track), DTU PhD in Virtual Reality-Based Visualization of Geometric Data, completed June 2023 Project participant in AL-EYE: The Visual Aid (2025) While no formal advisees are listed, his role as a faculty member suggests future student supervision. He has collaborated extensively with researchers such as Jeppe R. Frisvad, Jakob Andreas Bærentzen, and Vedrana A. Dahl.

• Digital Economy
• Social Welfare
• Consumer Behavior
• +6 more

Dr. Shaobo (Kevin) Li is a Tenured Associate Professor at the School of Business, Southern University of Science and Technology (SUSTech), with secondary appointment in the Department of Information Systems & Management Engineering. He holds a PhD in Business Administration from Nanyang Technological University (2019), Master of Business Administration (University of Virginia, 2014), Master of Finance (West Virginia University, 2012), and Bachelor of Business Administration (Lanzhou University, 2011). National High-Level Youth Talent Program awardee Overseas High-Caliber Personnel in Shenzhen City Recipient of 2018 China Scholarship Council’s Excellent Self-Funded Student Scholarship His research focuses on the intersection of digital economy, social welfare, and technology-driven marketing, employing experimental methods, empirical models, and neuroscience. He serves as Associate Editor for the Journal of Business Research and has published in top UTD-24 journals including Journal of Consumer Research, Information Systems Research, and Production and Operations Management. His work examines platform economics, brand management during crises, and consumer behavior related to AI, sustainability, and health decisions. He has led 10+ research projects (National Natural Science Foundation, Ministry of Science and Technology 2030 Program) and received multiple research awards, including Academy of Marketing Science Best Doctoral Dissertation Proposal Award (2019) and Best Paper Awards at China Marketing Science (2020,2024), China Marketing International Conference (2023), and CMAU Annual Conference (2023,2024). Teaching accolades include SUSTech’s Premier Teaching Award, Top 10 Most Popular Professor among undergraduates, and Nanyang Business School’s Best Graduate Teaching Award (2017). Teaches Financial Marketing (undergraduate) Teaches Frontiers of Management & Research Methods (PhD) Actively recruiting research assistants, postdocs, and joint PhD candidates with Hong Kong Polytechnic University

Nina FranzView profile

Researcher

• Media Theory
• History of Technology
• Military Imaging
• +5 more

Nina Franz is a Researcher at the Institute of Media Studies, Braunschweig University of Fine Arts, specializing in the Theory and History of Technology. She holds a doctorate in Cultural Studies from Humboldt University of Berlin and has held research positions at Bauhaus University Weimar and Humboldt University Berlin. Her research spans military imaging technologies from early modern period to computer age, climate catastrophe narratives in humanities and contemporary art, history of automation, and critical analysis of technological destruction narratives. She examines how imaging systems mediate power relations in warfare, medicine, and colonial contexts, with particular focus on ultrasound, drone warfare, and military surveillance systems. Her recent publications reveal strong interdisciplinary trends across Media Studies, Cultural History, and Critical Military Studies, with recurring themes of visual epistemology, technological mediation, and the weaponization of perception. Key subfields include drone warfare protocols, medical imaging interfaces, algorithmic control systems, and climate catastrophe representations. Doctoral Scholarship, Gerda Henkel Foundation (2015-2018) As a curator and educator, Franz has organized international conferences including 'Remote Control. Scales of Mediated Intervention' (2017) and co-curated exhibitions like 'A Better Version of You' (2016-2018) with Goethe-Institut Seoul. Her current teaching includes courses on military imaging and rearmament discourses, with mandatory participation in the 'Fascism and Mediality' workshop (2025). She regularly presents at academic conferences on military imaging technologies, including upcoming lectures at Staatliche Hochschule für Gestaltung Karlsruhe and Johannes Gutenberg-Universität Mainz. Her work bridges academic research with contemporary art curation, examining how military technologies permeate civilian perception through screen media and imaging systems.