Find Academic Supervisors

• Machine Learning
• Natural Language Processing
• Predictive Maintenance
• +4 more

Tony Lindgren is an Associate Professor at the Department of Computer and Systems Science, Stockholm University, affiliated with the Data Science Research Group and Natural Language Processing Research Group. His work bridges data science and NLP , focusing on interpretable models, constraint programming, and predictive maintenance systems. Research interests include: Machine Learning for explainability and fairness Constraint Programming in maintenance optimization Natural Language Processing for risk analytics and troubleshooting Recent publications demonstrate trends in multi-objective optimization (2025 satellite scheduling), conformal prediction (2024 CoPAL), and fault detection (2024 Automotive Nowcasting). His work often integrates domain-specific constraints with scalable algorithms across applications like food safety and autonomous vehicles. Software tools developed by Lindgren include: Example-based Feature Tweaking Rule Indexing Frameworks His research groups focus on AI-driven decision support for high-stakes domains, combining technical innovation with societal impact considerations.

Gerhard WeberView profile

Professor

• Accessible Computing
• Assistive Technologies
• Human-Computer Interaction
• +4 more

Prof. Gerhard Weber holds the Chair in Human-Computer Interaction at Technische Universität Dresden, Germany. Previously, he served as Chair for Human-Centered Interfaces at Christian-Albrechts-Universität zu Kiel (2000–2007) and Professor for Operating Systems and Graphical User Interfaces at Harz University of Applied Sciences (1996–2000). His research focuses on accessible computing, assistive technologies, haptics, and multimodal interaction. Key projects include development of tactile charts (SVGPlott), robotic guidance systems (HapticRein), and indoor navigation solutions for visually impaired users. Current work explores voice interfaces for social robots, autism-inclusive technologies, and accessibility maturity models for higher education institutions. Over 70 publications span conferences like CHI, IEEE, and ACM, emphasizing practical applications in assistive tech. Education & Professional Journey: 2007–Present: Chair in Human-Computer Interaction, TU Dresden 2000–2007: Chair for Human-Centered Interfaces, Kiel University 1996–2000: Professor of Operating Systems and GUIs, Harz University Research Interests: Prof. Weber's work bridges theory and practice in accessibility, emphasizing tactile interfaces, inclusive design, and assistive robotics. Recent projects include: Mosaik : Enabling blind users to create and share graphics via audio-tactile tools Cloud4All : Personalized web accessibility solutions Range-IT : Real-time object detection for navigation aids Advising & Grants: Managed €3.2M in EU and national grants (2011–2020) Supervised 12+ graduate projects on assistive tech Labs & Teams: Leads TU Dresden's Human-Computer Interaction Lab, collaborating with industry partners like Siemens and rehabilitation centers to deploy assistive systems in real-world settings.

• Bioinformatics
• Computational Biology
• Pharmaceutical Drug Discovery & Development
• +13 more

Leonard Wesley is an Associate Professor in the Department of Computer Science at the College Of Science, San Jose State University. His research spans interdisciplinary domains at the intersection of Bioinformatics , Computational Biology , and Machine Learning , with specific applications in Pharmaceutical Drug Discovery , Genomic Data Analysis , and Autonomous Robotics . Education: Ph.D. in Computer Science, University of Massachusetts M.S. in Computer Science, University of Massachusetts B.A. in Physics and Math, Northeastern University Research Interests include Approximate Reasoning (probabilistic, evidential, and fuzzy logic), Agent-Oriented Systems , and Sensor Fusion . His work applies these methodologies to Drug Portfolio Management , Protein Structure Scoring , and Medical Diagnostics . Publication Trends show a consistent focus on Computational Biology , Robotics , and Uncertainty Quantification over four decades. Early work in Computer Vision evolved into modern applications in Pharmaceutical Analytics and AI in Aerospace . Key Projects include SVM-based drug affinity prediction, evidence-driven decision support systems for biopharma, and real-time agent development frameworks like ROADS. He has contributed to CFD code control and Mobile Network Congestion solutions. Collaborations with institutions like NASA, Los Alamos National Laboratory, and international conferences (WMSCI, ICINCO, AIAA) highlight his cross-disciplinary impact. His teaching includes Artificial Intelligence and Bioinformatics courses.

Jinghui ChengView profile

Associate Professor

• Human-Computer Interaction
• Software Engineering
• User-Centered Design
• +3 more

Jinghui Cheng is an Associate Professor at the Department of Computer Engineering and Software Engineering at Polytechnique Montréal . He holds a PhD in Computer Science from DePaul University (2017), preceded by an MSE and BSE from Xi’an Jiaotong University, China. His research uniquely bridges Human-Computer Interaction (HCI) with Software Engineering , focusing on technologies that support domain experts with specialized information needs. Awards : Canada Research Chair Tier 2 in User Experience Design of Data-Driven Systems His recent work examines playful AI interactions (e.g., ChatGPT), designer-developer collaboration , and privacy motivation in UI/UX. He actively supervises PhD and Master’s students in the HCD Lab , with over 20 completed theses. Collaborations span institutions like the École Polytechnique and partnerships with researchers such as Jin L. C. Guo and Bram Adams . Cheng’s 15 most recent publications (2023-2025) reflect trends in AI-assisted design , usability in open-source communities , and ethical technology development . His grants include the AUDACE grant (2020) co-led with Dr. Gabrielle Pagé, focusing on healthcare applications.

Fajar Juang EkaputraView profile

Academic

• Semantic Web
• Knowledge Graphs
• Neurosymbolic AI
• +4 more

Fajar Juang Ekaputra is a Tenure Track Assistant Professor at the Institute of Data, Process, and Knowledge Management (DPKM), WU Vienna and a part-time Postdoctoral Researcher at the Data Science research unit, TU Wien . With a focus on Semantic Web , Knowledge Graphs , and their integration with Machine Learning in Neurosymbolic AI systems, his work spans domains like Cyber-Physical Systems and Materials Engineering . Education: Dr.techn. (2018), TU Wien M.T. (2010) and S.T. (2008), Institute Teknologi Bandung (ITB) Research Interests center on hybrid AI systems combining Semantic Web and Machine Learning , with applications in Cyber-Physical Systems (e.g., smart grids, smart buildings), data privacy in smart cities, and materials engineering . His 102+ publications include frameworks like SWeMLS-KG and SHACL4Protege . Recent Articles (2024) address explainable AI in cyber-physical systems, privacy trust in data infrastructures, and neurosymbolic frameworks . Earlier works (2023–2022) explore ontology-based data management , auditable AI , and hybrid system architectures . Scientific Awards: Best Paper Awards (ICoDSE 2023, ICoDSE 2016) Best Poster Nomination (SEMANTiCS 2019) PhD Scholarship (Austria’s Agency for Education and Internationalisation, 2012) Advising includes supervising PhD students (e.g., Majlinda Llugiqi, Katrin Schreiberhuber) and master’s theses on topics like knowledge graph characteristics and data quality assessment . He leads projects such as FAIR-AI (FFG-funded, 2024–2026) and SENSE (Horizon Europe, 2023–2025).

• Systematic Review Automation
• Machine Learning
• Natural Language Processing
• +7 more

Lena Schmidt is a Research Fellow at the University College London (UCL) Social Research Institute , specializing in methods development for systematic reviews , evidence maps , and living evidence syntheses . She leverages machine learning and neural networks to optimize data mining and classification during the screening process. Her work emphasizes automation tools for large-scale literature analysis and addressing reproducibility in evaluations. MSc Applied Health Sciences , Furtwangen University (2018) NIHR Systematic Reviews Fellowship (2018–2020) Predoctoral Fellowship in Living Reviews and Automation Her research focuses on enhancing systematic review efficiency through NLP , AI , and data engineering , particularly for grey literature in health research. Recent publications address pandemic impacts on mental health , automation in evidence synthesis , and knowledge graph development for toxicology. Scientific awards include the NIHR Fellowship and Intelligent and Adaptive Systems Certification from the University of Sussex. She actively collaborates with organizations like the Campbell Collaboration and ICASR , co-organizing automation workshops and contributing to methodological frameworks.

Deepti RaghavanView profile

Assistant Professor

• Operating Systems
• Networking
• Machine Learning Systems
• +2 more

Deepti Raghavan serves as Assistant Professor in Brown University's Department of Computer Science, specializing in operating systems, networking, and machine learning systems. Her research develops novel networked abstractions to optimize data movement in distributed applications through API redesign. Her educational background includes: PhD in Computer Science from Stanford University (2024) MEng in Computer Science from Massachusetts Institute of Technology (2018) BS in Computer Science from Massachusetts Institute of Technology (2017) Her research integrates systems infrastructure with machine learning workloads , focusing on performance-critical communication patterns. Key innovations include zero-copy serialization techniques and network orchestrators for compound AI systems, bridging theoretical advances with practical deployment in cloud environments. Publication trends (2018-2024) reveal consistent contributions to high-performance networking and ML systems, with increasing focus on AI infrastructure. Her work shows strong collaboration patterns with Stanford/MIT researchers and addresses fundamental challenges in data movement efficiency across distributed systems. Scientific recognition includes: National Science Foundation Graduate Research Fellowship (2019) Stanford School of Engineering Fellowship (2018-2019) Distinguished Artifact Award at SOSP 2023 Best Paper Award at Usenix ATC 2018 She actively recruits PhD students for her research group and teaches advanced systems courses including Cloud and Datacenter Operating Systems. Her research is supported by prestigious fellowships and likely NSF grants, with teaching responsibilities spanning graduate seminars and core undergraduate systems education. Her research group collaborates with Stanford's Systems Lab and MIT's CSAIL Networks group, maintaining strong ties to the Networks and Mobile Systems research community. Current projects focus on next-generation abstractions for AI-driven networked applications.

Simone Paolo PonzettoView profile

Assistant Professor

• Knowledge acquisition
• Natural Language Processing
• Semantic Web technologies
• +5 more

Simone Paolo Ponzetto is an Assistant Professor (Juniorprofessor) at the University of Mannheim since 2013, affiliated with the Research Group Data and Web Science. His research focuses on Semantic Web technologies, Natural Language Processing (NLP), and knowledge acquisition, particularly leveraging collaboratively built resources like Wikipedia. Prior to Mannheim, he held postdoctoral roles at Sapienza University of Rome and research positions at the University of Heidelberg and Stuttgart. His work includes pioneering projects like BabelNet, a multilingual semantic network. Ponzetto earned his PhD in Computational Linguistics from the University of Stuttgart, with interdisciplinary contributions to coreference resolution, semantic relatedness, and ontology learning. Research Interests: Unsupervised/weakly-supervised knowledge extraction Multilingual ontology learning and semantic networks Lexical semantics (word sense disambiguation, semantic similarity) Discourse semantics (coreference resolution, coherence modeling) Professional Contributions: Guest editor for a Artificial Intelligence Journal special issue on AI and Wikipedia Area chair for EMNLP-CoNLL 2012 and EACL 2014 Program committee member for ACL, AAAI, and other top conferences Lab/Team: Active in the Research Group Data and Web Science at Mannheim, advancing AI and NLP applications in collaborative knowledge systems.

• Information Visualization
• Data Visualization
• Human-Computer Interaction
• +4 more

Dr. Stuart Marshall serves as Associate Dean of Academic Development in the Faculty of Science and Engineering at Victoria University of Wellington - Te Herenga Waka, where he also holds the academic rank of Senior Lecturer. Previously, he served as Head of School for the School of Engineering and Computer Science from 2015-2021 after joining the institution as a Lecturer in 2003. His academic journey includes completing his BSc, MSc, and PhD in Computer Science at Victoria University of Wellington, with his doctoral research focusing on software reuse. Marshall's research interests center on information and data visualization, particularly exploring how visualization can function as collaborative tools in team environments rather than single-user applications. He also investigates explainable AI and mobile user interface design with emphasis on promoting healthy device usage patterns. His work bridges theoretical computer science with practical applications in education and environmental analysis. Analysis of his publication record reveals a consistent focus on visualization techniques, with recent work shifting toward immersive analytics and virtual reality applications for complex data analysis, particularly in ecosystem services. Earlier publications concentrated on mobile learning applications grounded in transactional distance theory, software visualization for large codebases, and graph layout algorithms. Marshall has supervised six PhD students and eight Masters students to completion, with current doctoral supervision spanning immersive environments for reading assistance, medical diagnosis interfaces, and cardiac procedure simulation. His grant portfolio includes multiple ACM ISS 2022 projects with industry partners including Sensor Holdings Limited, Niantic, Autodesk, and Northeastern University, along with an Australian Research Council grant for digital games preservation. Teaching responsibilities encompass foundational programming, safety-critical systems, human-computer interaction, and data visualization across undergraduate and graduate courses. He teaches subjects including SWEN326 (Safety-Critical Systems), CGRA151 (Introduction to Computer Graphics and Games), and DATA301 (Data Science in Practice), with teaching assignments scheduled through 2026.

• Biomedical Engineering
• Electrical and Electronic Engineering
• Artificial Intelligence and Image Processing
• +3 more

Professor Dinesh Kumar is a faculty member in the School of Engineering at RMIT University, specializing in Biomedical Engineering and Artificial Intelligence. He holds the role of Chair of the IEEE Biosignals and Biorobotics Conference since 2009, demonstrating leadership in interdisciplinary research. His research focuses on biomedical signal processing, medical imaging, and AI-driven diagnostics, with applications in neurology, cardiology, and telemedicine. Professor Kumar oversees projects addressing challenges like Parkinson’s disease diagnosis, cardiac arrhythmia classification, and wound assessment using advanced computational methods. His work bridges clinical and engineering domains, emphasizing practical solutions for healthcare challenges. Recent contributions include developing algorithms for ECG analysis, facial expression recognition for neurological disorders, and chatbot-based vocal screening systems. Despite no explicit mention of awards, his extensive publication record and conference leadership highlight significant scholarly impact. Professor Kumar collaborates with industry and academic partners to advance technologies such as thermal imaging for ulcers, deep learning for medical image segmentation, and wearable sensors for gait analysis. His research often involves interdisciplinary teams, reflecting a commitment to translating technical innovations into real-world healthcare tools.

Gail KaiserView profile

Professor

• Software Systems
• Static and Dynamic Program Analysis
• Software Testing
• +3 more

Dr. Gail Kaiser is a Professor of Computer Science at Columbia University, where she has served for 40 years. She directs the Programming Systems Lab (PSL) and is affiliated with the Software Systems Lab (SSL). Her research focuses on software systems, program analysis, testing, security, and AI-driven software engineering. She earned her PhD from Carnegie Mellon University and a BS from MIT. Education: PhD in Computer Science, Carnegie Mellon University (1985) MS in Computer Science, Carnegie Mellon University (1980) BS in Computer Science and Engineering, MIT (1979) Research & Teaching: Dr. Kaiser teaches COMS W4156 (Advanced Software Engineering) and COMS E6156 (Topics in Software Engineering). Her work spans metamorphic testing for machine learning, secure computing, and AI in SE. Notable contributions include pioneering metamorphic testing for classifiers and secure containers research. Awards & Grants: 2025 Distinguished Journal Award (ICST) NSF grants totaling over $2M for secure computing and software assurance ACM SIGSOFT Distinguished Paper Awards (2023, 2014) Labs & Collaborations: Her labs (PSL and SSL) drive innovation in program analysis and security. Collaborations include DARPA, NIH, and industry partners like IBM and Microsoft.

Daniel GermanView profile

Professor

• Software Engineering
• Software Evolution
• Open Source Software Development
• +4 more

Dr. Daniel German is a Professor in the Department of Computer Science at the University of Victoria, part of the Faculty of Engineering and Computer Science. He holds a PhD from the University of Waterloo, specializing in software engineering and open source ecosystems. His research focuses on software evolution, open source development practices, intellectual property issues in software systems, and licensing compliance challenges in modern AI/ML environments. German has contributed extensively to understanding dependency management, developer workflows, and legal aspects of software development. His work includes seminal studies on code provenance tracking (e.g., Cregit), library dependency management, and the sociotechnical dynamics of open source communities like the Linux kernel and GitHub ecosystems. German has explored critical topics such as licensing inconsistencies in software projects, ethical implications of AI-generated code, and the integration of open source components into proprietary systems. He is actively involved in software engineering education, examining how students engage with open source projects and the challenges of maintaining code quality in large-scale distributed systems. German’s research has practical implications for both academic and industrial software development practices, addressing real-world issues like security vulnerabilities in dependency chains and the legal risks of AI training data usage.

Steffen BeckerView profile

Professor

• Software Engineering
• Cloud Systems
• Model-Driven Engineering
• +7 more

Steffen Becker is a Professor at the University of Stuttgart's Faculty of Computer Science, Electrical Engineering and Information Technology, affiliated with the Institute for Software Engineering's Software Quality and Architecture group. His work focuses on software engineering, cloud systems, model-driven engineering, and cybersecurity. He leads research in architectural modeling tools like Slingshot, GUI testing frameworks (ViMoTest), and hardware security analysis. Recent studies explore AI integration in testing, education, and automotive systems (CARISMA). Research interests include elasticity modeling, self-adaptive systems, and educational technology. His 2025 publications address issues like end-user hardware comprehension, FPGA security, and LLM-driven test generation. Notable tools developed include the Slingshot Simulator for cloud-native systems and Gropius for cross-component issue management. Becker contributes to both theoretical advancements and practical implementations in software quality, security, and cloud infrastructure. Key Areas: Software Architecture, Cyber-Physical Systems, Testing, Reverse Engineering Tool Developments: ViMoTest, Slingshot, Gropius Education Focus: Online programming pedagogy and curriculum innovation His work bridges foundational research with industry applications, addressing challenges in automotive computing, cloud elasticity, and human-centric security awareness. Recent efforts emphasize explainable hardware (XHW) and AI's role in qualitative analysis automation.

Per LynggaardView profile

Professor

• Integrated Circuit Design
• Wireless Sensor Networks (WSN)
• Machine Learning
• +8 more

Per Lynggaard is a Professor of Electronics at the Technical University of Denmark (DTU) , leading the B.Eng. program in Electronics. Previously, he held an Associate Professor role at Aalborg University, combining academic excellence with a robust industrial career in technical-scientific research and development. Education: M.Sc. in Electrical Engineering and Information Technology (EE and IT) Ph.D. in Electronics from Aalborg University Research Interests: Focus on Integrated Circuit Design, Wireless Sensor Networks (WSN), Machine Learning, IoT, and Smart City Technologies . His work emphasizes energy-efficient systems, cybersecurity in IoT, AI-driven interference mitigation, and sustainable energy harvesting solutions. He has contributed to UN Sustainable Development Goals through projects addressing smart infrastructure and environmental monitoring. Projects & Collaborations: Leads and participates in EU-funded initiatives such as InnoTech (2023–2025) for green transition solutions and TransportTech (2023–2026) for Industry 4.0 logistics. Active in cybersecurity research via projects like Jamming Against Critical Wireless Communication , aiming to protect critical infrastructure. Awards: Recognized with multiple honors and rewards during his industrial career, though specific names are not listed. His work has been cited widely, with notable impact in IoT security and energy-efficient systems. Advising & Grants: Supervises Turnip T.N. in a PhD project on 6G security protocols. Engaged in securing funding for projects like F2D2: The Community for Dynamic Data (2021–2030), focusing on dynamic data systems and cybersecurity. Labs & Teams: Collaborates in interdisciplinary teams such as the InnoTech TaskForce and F2D2 Community , advancing IoT and AI integration. His research bridges academia and industry, with outputs spanning smart cities, healthcare IoT, and sustainable energy systems.

Enrico RukzioView profile

Professor

• Human-Computer Interaction (HCI)
• Automotive User Interfaces
• Extended Reality (XR)
• +5 more

Enrico Rukzio is a Full Professor of Human-Computer Interaction at the University of Ulm, leading the Human-Computer Interaction group and directing the Institute for Media Research and Media Development. His research spans interactive systems design, focusing on automotive UIs, extended reality, accessibility, and sustainable interaction. He holds a Ph.D. in Computer Science from the University of Munich and has held prior roles at Lancaster University and the Ruhr Institute for Software Technology. Roles: Faculty Dean (2017–2020), Admissions Committee Chairman, Doctoral Committee Chairman Educations: Ph.D., Munich; Lecturer qualifications from Lancaster and Duisburg-Essen Research emphasizes enabling efficient, inclusive, and sustainable interactions through novel interfaces. His work addresses automated vehicles, health-supporting tech, and accessibility for visually impaired users. Recent articles explore Bayesian optimization for UI design, automated vehicle communication, and urban air mobility visualization. Notable awards include best paper recognitions at CHI, EuroVR, and IEEE VR. His grants come from BMBF, DFG, and industry partners like Mercedes-Benz Group. Advises on over 20 funded projects and has mentored award-winning students.