Find Academic Supervisors

• Optical Nanoscopy
• Quantitative Phase Imaging
• Deep Learning in Microscopy
• +5 more

Krishna Agarwal is a Professor in Ultrasound, Microwaves and Optics at the Department of Physics and Technology, UiT The Arctic University of Norway. His research spans multiple interdisciplinary fields including optical nanoscopy, quantitative phase imaging, and computational imaging techniques. He is an active member of the Ultrasound, Microwaves and Optics research group, with specialized focus on Optical Nanoscopy, and participates in research projects including VirtualStain and NanoAI. Professor Agarwal's research interests center on advanced imaging techniques, particularly in optical nanoscopy and quantitative phase imaging. His work bridges physics, computer science, and biology, developing novel computational methods for microscopy enhancement. His research focuses on applying deep learning to improve imaging resolution, developing frameworks for quantitative phase reconstruction, and creating new methodologies for 3D imaging of biological specimens. His work has significant applications in biomedical imaging, cellular analysis, and diagnostic technologies. Recent publications demonstrate a strong trend toward integrating artificial intelligence with traditional optical techniques, with increasing emphasis on computational approaches to solve longstanding challenges in microscopy. His research shows consistent progression from theoretical optical methods toward practical applications in biological imaging and medical diagnostics, with numerous publications in high-impact optics and imaging journals. Professor Agarwal teaches Optisk nanoskopi (Course FYS-3029) at UiT, contributing to advanced optics education. His research group appears to collaborate extensively with international researchers across multiple institutions, suggesting active grant funding and collaborative research efforts. Based at Teknologibygget Tromsø 3.058, Professor Agarwal leads research in the Optical Nanoscopy group, focusing on developing next-generation imaging technologies that combine optical physics with computational methods. His team appears to work at the intersection of physics, computer science, and biology, developing tools that push the boundaries of what's possible in cellular and sub-cellular imaging.

• Automata Theory
• Formal Verification
• Logic in Computer Science
• +3 more

Christof Löding , currently an Adjunct Professor at the Lehrstuhl für Logik und Theorie diskreter Systeme (Informatik 7) department of RWTH Aachen University , is a leading researcher in Automata Theory , Formal Verification , and Logic in Computer Science . His work bridges theoretical foundations with practical applications in software verification, automata minimization, and game theory. Research Interests include automata theory, formal verification, logic, tree automata, game theory, and computational models. Publications span topics like Finite-valued Streaming String Transducers , Deterministic Parity Automata , and Stochastic Game Strategies . Collaborations with researchers like Emmanuel Filiot , Sarah Winter , and León Bohn highlight his contributions to automata and verification. Email : loeding@informatik.rwth-aachen.de He has actively published in venues such as ICALP , LICS , and STACS , focusing on deterministic automata, transducers, and logic-based computational systems. His work on Hyperlogic for Strategies in Stochastic Games (2025) and Minimal History-Deterministic Automata (2025) showcases his ongoing influence in formal methods and automata theory.

• Database Systems
• Integration of heterogeneous databases
• Data quality and data integrity
• +6 more

Thomas Kudraß serves as Professor for Database Systems at the Faculty of Computer Science, Mathematics and Natural Sciences (IMN) at Leipzig University of Applied Sciences (HTWK Leipzig). With over 25 years of academic and industry experience, he teaches courses including Database Basics, Database Application Programming, Data Warehousing, and Big Data Technologies. His leadership roles include Internship Coordinator for Computer Science since 2001, Member of the Academic Senate since 2011, and Contact person for the IMN faculty alumni association since 2005. Dr. Kudraß earned his Dipl.-Ing. in Computer Science from Technical University of Dresden (1985-1990) and completed his doctorate at Darmstadt University of Technology (1992-1997), where his dissertation received the prestigious Jos Schepens Memorial Award. Prior to academia, he worked as an Information Systems Architect at UBS AG Zurich and Database Specialist at Swiss Bank Corporation Basel. His research spans database technologies with focus on heterogeneous database integration, data quality, data privacy, and modern database concepts. Recent work explores cloud-native billing applications for 5G, NoSQL databases, and privacy-preserving record linkage techniques. His publication record shows continuous evolution from traditional database systems to contemporary challenges in big data and distributed systems. Jos Schepens Memorial Award for doctoral dissertation (1997) Active participation in German Informatics Society (GI) specialist groups Organizer of multiple database-related workshops and conferences Professor Kudraß has significantly contributed to academic governance as E-Learning Officer (2000-02), Faculty Council member (2009-12), and liaison lecturer for the German Society for Computer Science (2001-14). He has coordinated numerous student projects and served on program committees for major conferences including INFORMATIK 2017 and BTW series.

Sima Siami-NaminiView profile

Lecturer

• macroeconomics
• monetary policy
• time series analysis
• +5 more

Sima Siami-Namini serves as a Lecturer at Johns Hopkins University, teaching in the MS in Applied Economics program with extensive experience in undergraduate and graduate instruction across economics, statistics, and finance disciplines. Her academic credentials include advanced interdisciplinary training: PhD in Applied Economics (minor: Statistics), Texas Tech University, 2020 Master's in Statistics, Texas Tech University, 2022 Master's in Artificial Intelligence (Machine Learning focus), University of North Texas, 2023 Her research program integrates macroeconomic theory with cutting-edge computational methods, specializing in monetary policy analysis, time series econometrics, and AI-driven forecasting. She bridges traditional economic modeling with machine learning applications, particularly in anomaly detection, data visualization, and large language model implementations for economic forecasting. Analysis of her publication trajectory (2020-2024) reveals three dominant research streams: (1) deep learning architectures (LSTM, TCN) for time series forecasting and anomaly detection, (2) monetary policy impacts on income inequality using FAVAR/SVECM models, and (3) natural language processing applications for Federal Reserve communication analysis. Her recent work increasingly incorporates large language models for domain-specific economic analysis and code generation. No documented scientific awards or major honors appear in the available records. She mentors students in the Applied Economics program with emphasis on quantitative research methods, though specific grant funding details remain undisclosed. Her teaching methodology incorporates experiential learning techniques adapted from digital forensics education frameworks. No dedicated research laboratories or institutional teams are referenced in the source materials.

• Epistemology
• Research Theory and Methodology
• Social Media Analytics
• +5 more

Claudia Freire is a Postdoctoral Researcher at the Center for Communication and Culture Studies (CECC) at Catholic University of Lisbon . She holds a PhD in Communication Sciences from the University of São Paulo (2015) and has held roles at institutions including the University of São Paulo, Online University of Viçosa, and the National Council for Scientific and Technological Development (CNPq). Her work intersects with the UN Sustainable Development Goal for Quality Education. Education PhD in Communication Sciences, University of São Paulo (2015) Master's in Communication Sciences, University of São Paulo (2009) Bachelor's in Communication Sciences (Marketing), Pontifical Catholic University of Minas Gerais (1997) Bachelor's in Humanities and Arts, Federal University of Minas Gerais (1999) Her research focuses on epistemology , social media analytics , algorithms , and television fiction with a strong emphasis on data visualization and digital engagement. She has published extensively on topics like social media monitoring , fan communities , and transmedia storytelling . Claudia's publications highlight the evolution of social media monitoring techniques , algorithmic gatekeeping in digital platforms, and methodological approaches to television fiction . Her work bridges theoretical frameworks with practical tools for analyzing digital communication. Peer Review Reviewer for MATRIZes (2023) Reviewer for Conexión (2023) Claudia Freire contributes to academic discourse through peer review and media commentary, focusing on digital communication , civil diplomacy , and educational diversity . Her career spans roles in research, content production, and methodology development.

Adam BatesView profile

Associate Professor

• Data Provenance
• Cybersecurity
• Computer Systems
• +7 more

Adam Bates is an Associate Professor at the University of Illinois at Urbana-Champaign, with affiliations in the Department of Computer Science and the Electrical & Computer Engineering Department. His research focuses on data provenance, cybersecurity, and secure system design. He received his PhD from the University of Florida under Professor Kevin Butler, collaborating with the Florida Institute for Cybersecurity Research. His work addresses security challenges in SSL/TLS, cloud computing, USB attack vectors, and telephony infrastructure, with notable contributions to provenance-aware systems. Education: PhD in Computer Science (University of Florida, advised by Kevin Butler) Research Interests: Secure data provenance systems Endpoint detection and response Privacy in smart homes and IoT Serverless computing security USB and cloud security Scientific Awards: NSF CISE Research Initiation Initiative (CRII) Award (2017) NSF CAREER Award (2018) Labs & Teams: Principal Investigator at the STS Lab

• Economic theory
• Microeconomics
• Game theory
• +1 more

Robert Ferenc Veszteg is a Professor at Waseda University's Faculty of Political Science and Economics, specializing in microeconomic theory, game theory, and experimental economics. He holds a PhD from Universitat Autònoma de Barcelona (2004) and has held academic positions at Osaka University, Universidad Carlos III de Madrid, and other international institutions before joining Waseda in 2010. Research Focus: His work centers on experimental validation of economic theories, particularly in bargaining, market design, and decision-making under institutional constraints. Key research streams include: Bargaining dynamics and axiomatic validation Matching markets with friction Behavioral impacts of stress and social contexts Mechanism design for public goods provision Publication Trends: His 24 articles demonstrate consistent focus on experimental validation of game-theoretic models, with recent work emphasizing bargaining under asymmetric information and stress-induced behavioral changes. Cross-cultural studies and methodological critiques of experimental design form secondary themes. Awards & Recognition: Waseda Teaching Award (2016) for Microeconomics A Research Leadership: Principal investigator for multiple JSPS grants including: Experiments on unstructured bargaining (2023-2026) New theory of coalition formation (2017-2022) Behavioral models of decentralization (2020) Educational Leadership: Director of English-based degree programs at Waseda (2016-2018, 2021-2022) and developer of graduate courses in experimental methodology.

• Internet Law
• Data Protection Law
• Information Technology Law
• +3 more

Sebastian Brüggemann is a German legal scholar specialising in Internet, data-protection and IT law. Since 2013 he has been a part-time lecturer (Lehrbeauftragter) at the Faculty of Law of Eberhard Karls University of Tübingen, and he holds parallel teaching appointments in data-protection and IT law at the Universities of Applied Sciences in Kehl and Ludwigsburg as well as at ZHAW School of Management and Law in Winterthur, Switzerland. In private practice he works as in-house counsel (Syndikusrechtsanwalt) for a large international IT company, focusing on data-protection and technology law. Education: 2003-2011: Studies of Law and General Rhetoric, Eberhard Karls University of Tübingen 2009: First State Law Examination, Tübingen 2011: Magister Artium in General Rhetoric, Tübingen 2010-2012: Legal clerkship (Referendariat), including stages at the German University of Administrative Sciences Speyer and eco – Verband der Internetwirtschaft 2012: Doctorate in Law (Dr. iur.), Tübingen – dissertation on third-party disclosure claims against Internet providers in copyright enforcement 2013: Admission as attorney (Rechtsanwalt) 2013-2015: Part-time LL.M. in Information Technology Law, Carl von Ossietzky University of Oldenburg Research interests span the intersection of law and digital technology: data-protection compliance under the GDPR, cybersecurity regulation, copyright in digital media, network neutrality, M2M/IoT legal issues, and the legal framework of behavioural advertising. His work frequently analyses German, European and comparative US developments. He has authored a monograph, numerous commentaries to GDPR/BDSG provisions, model IT contracts, and more than two dozen peer-reviewed articles and case notes since 2013, identifying recurring themes such as data portability, ISP liability, streaming and copyright, and the challenges of Industrie 4.0. Professional memberships & science communication: editorial board of Privacy in Germany , core team member of the Telemedicus IT-law portal, member of IAPP, DGRI and GRUR, and co-author of sector guidelines issued by Bitkom and eco association. There is no indication of supervised doctoral or master’s students in the supplied material; his teaching activities concentrate on specialised continuing-education courses and part-time lectures.

Eric AtkinsonView profile

Assistant Professor

• Programming Languages
• Program Runtimes
• Program Analysis
• +3 more

Eric Atkinson is an Assistant Professor in the School of Computing at Binghamton University, specializing in programming languages for uncertainty and their intersections with artificial intelligence. He holds a PhD from MIT (2024), an MS from MIT (2018), and a BS from UC Berkeley (2015). Prior to Binghamton, he was a visiting researcher at INSAIT in Sofia, Bulgaria, and conducted research internships at Facebook and Mozilla. His research focuses on programming languages, program runtimes, formal methods, and AI integration. Key interests include probabilistic programming, static analysis, and runtime systems for uncertain domains. He teaches programming languages courses and advises PhD and M.Sc. students. His publications span probabilistic programming systems, compiler optimizations, and formal verification. He actively participates in academic service roles, including program committees for PLDI, LAFI, and OOPSLA, and mentors underrepresented groups in graduate school through initiatives like the MIT EECS GAAP program.

• Machine Learning
• Artificial Intelligence
• Computer Vision
• +3 more

Alessandro Betti is an Assistant Professor of Computer Science at IMT Lucca within the SySMA research unit. Previously, he held postdoctoral positions at Université Côte d’Azur (Maasai team) and Università di Siena (Siena Artificial Intelligence Lab/SAILab). He earned his Ph.D. in Computer Science (Smart Computing) from the Universities of Florence, Pisa, and Siena in 2020, and a Master’s in Theoretical Physics from the University of Pisa, focusing on large-N CP(N-1) sigma models and solitonic solutions related to QCD confinement. His research integrates theoretical foundations of machine learning with practical applications in computer vision. Key areas include data stream processing, online continual learning, and motion-invariant visual feature extraction using deep architectures. Current work explores optimal control principles for learning dynamics and formalizes a transport equation derived from discrete mancala games. He co-authored two books: Machine Learning: A Constraint-Based Approach (2023) and Deep Learning to See (2022), both foundational texts in their fields. His publications span journals like Neurocomputing and Frontiers in Artificial Intelligence , with contributions to conferences such as NeurIPS and AAAI. Research highlights include developing variational calculus frameworks for learning laws, neural time-reversed Riccati equations, and foveated neural computation models inspired by biological vision systems. Betti collaborates with institutions like SAILab and Maasai, focusing on interdisciplinary projects blending physics-inspired mathematics with AI. His work bridges theoretical rigor and applied challenges in dynamic, real-world data environments.

Michael CarbinView profile

Associate Professor

• Programming Systems
• Probabilistic Programming
• Quantum Computing
• +3 more

Michael Carbin is an Associate Professor at MIT in the Department of Electrical Engineering and Computer Science (EECS), where he leads the Programming Systems Group at the Computer Science and Artificial Intelligence Laboratory (CSAIL). His research centers on developing programming systems that handle uncertainty through probabilistic programming, quantum computing, and neural networks. Carbin's work spans programming languages, systems, and machine learning, with themes including uncertainty management, efficiency optimization, and formal verification. His publications demonstrate a strong focus on probabilistic inference methods, neural network optimization, and quantum programming frameworks. Awards and Honors: Sloan Research Fellowship (2020) Multiple Best Paper Awards (OOPSLA 2013, 2014; ICLR 2019) NSF CAREER Award (2018) Google Faculty Research Award (2018) As the head of the Programming Systems Group, he advises 10+ graduate students and postdocs, focusing on cutting-edge systems research. He has secured grants including Facebook Research Awards and NSF funding.

Elena Simona LohanView profile

Professor

• Wireless Positioning
• GNSS Algorithms
• Wearable Computing
• +7 more

Elena Simona Lohan is a Professor at Tampere University's Faculty of Information Technology and Communication Sciences , leading the Signal Processing for Wireless Positioning research group. She also holds a Visiting Professor position at Universitat Autonoma de Barcelona's SPCOMNAV group. Education : MSc in Electrical Engineering (Politehnica University of Bucharest, 1997), DEA in Econometrics (École Polytechnique, Paris, 1998), PhD in Telecommunications (Tampere University of Technology, 2003) Research Focus : GNSS algorithms, interference detection, wearable computing, and 5G positioning convergence. Her work spans signal processing for GNSS (Galileo, GPS, GLONASS, BeiDou), indoor/outdoor localization, and IoT communication. She coordinates the H2020 MSCA European Joint Doctorate A-WEAR and serves as Associate Editor for the Journal of Navigation and IET Radar, Sonar & Navigation . Notable projects include GRAMMAR (Galileo receivers), UJI IndoorLoc Platform , and SP4TE collaborations. She has authored over 250 publications and 6 patents.

Seif HaridiView profile

Professor

• Parallel Computing
• Distributed Computing
• Cloud Computing
• +4 more

Seif Haridi is a Professor at KTH Royal Institute of Technology in Stockholm, Sweden, specializing in parallel and distributed computing systems. He holds dual roles as Chair-Professor of Computer Systems and Chief Scientific Advisor at RISE SICS. His research integrates systems engineering with theoretical foundations, focusing on programming systems, distributed computing, and big data technologies. Key contributions include co-designing SICStus Prolog, the Mozart Programming System, and Apache Flink, as well as leading the development of HOPS, a European big data platform awarded the IEEE Scale Prize 2017. He has led major EU projects like EIT-Digital’s cloud computing initiative and co-founded startups such as LogicalClocks and HiveStreaming. His teaching includes courses on distributed algorithms and peer-to-peer computing at KTH. Notable awards include the European Data Science Technology Innovation 2019. His work spans systems like HOPS, Flink, and Kompics, emphasizing scalability and robustness in distributed environments. Current projects include CDA (Continuous Deep Analytics) and ExtremeEarth for geospatial data analysis. Research interests include distributed algorithms, consensus protocols, and cloud-native systems. His lab’s contributions to scalable storage (e.g., HopsFS) and stream processing (Apache Flink) highlight his impact on both academia and industry.

Clara Bradbury-RanceView profile

Senior Lecturer

• LGBTQ+ Film and Media
• Queer Theory
• Feminist Pedagogy
• +3 more

Dr. Clara Bradbury-Rance is a Senior Lecturer in Gender and Sexuality Studies at King's College London's Department of Interdisciplinary Humanities, within the Faculty of Arts & Humanities. She holds a BA in Film Studies (University of Exeter), an MRes in Sexuality and Gender Studies (University of Exeter), and a PhD in Screen Studies (University of Manchester). Her research focuses on LGBTQ+ film and media, queer theory, and feminist pedagogy, with a particular emphasis on lesbian representation, queer masculinity, and digital media's impact on queer taste. Her notable works include the monograph Lesbian Cinema after Queer Theory (2019) and contributions to journals like Feminist Media Studies and Camera Obscura . She has been awarded a Senior Fellowship of the Higher Education Academy (2023) and sits on the editorial boards of MAI: Feminism and Visual Culture and the Screening Sex book series. Her teaching includes modules on queer screen cultures and feminist pedagogy across BA and MA programs at King's. Clara collaborates with institutions like the British Film Institute, BFI Flare, and international festivals such as the Mexico Women's Film Festival. Her current projects include a semi-autobiographical study on queer screen cultures and a BFI Classic analysis of Céline Sciamma’s Portrait of a Lady on Fire . She also leads interdisciplinary PhD workshops through Queer@King’s, fostering queer and trans studies across disciplines.

Hugo LedouxView profile

Researcher

• 3D Geoinformation
• Urban Data Science
• Remote Sensing
• +3 more

Hugo Ledoux is an academic affiliated with the Faculty of Architecture and the Built Environment at Delft University of Technology, specializing in Urban Data Science. His research focuses on 3D geospatial modeling, including CityGML standards, terrain analysis, and automated reconstruction of urban structures. He has contributed to projects like the DeltaDTM coastal terrain model and the cjdb database solution for CityGML. Education: Not explicitly detailed in text, but inferred through academic roles and publications. Research interests emphasize 3D geoinformation systems, remote sensing applications, and urban data science. His work addresses challenges in 3D city models, building reconstruction, and geospatial validation tools like Val3dity. Recent efforts include improving global terrain models using ICESat-2 and GEDI lidar data. Publications span automated building reconstruction workflows, terrain accuracy assessments, and semantic-guided facade modeling. Awards include the Best Presentation at 3DGeoInfo 2020 and the U.V. Helava Award for Best Paper in 2011. Ledoux has supervised 4 academic works and actively participates in conferences, editorial activities, and open-source software development for geospatial applications. Labs/Teams: Involved in TU Delft’s 3D geoinformation research, contributing to tools like 3dfier and CityJSON for 3D data interoperability.