Find Academic Supervisors

Josef UrbanView profile

Researcher

• Automated Reasoning
• Machine Learning
• Formal Mathematics
• +3 more

Josef Urban is a distinguished researcher at the Czech Institute of Informatics, Robotics and Cybernetics (CIIRC) , Czech Technical University in Prague. He leads the ERC Consolidator project AI4REASON and has held positions at Radboud University Nijmegen, Charles University, and the University of Miami. His work focuses on combining automated reasoning with machine learning in large formal knowledge bases, particularly in mathematics. Research & Projects Urban develops systems like MaLARea (Machine Learning Connection Prover) and ENIGMA (learning-based inference guiding). He contributed to the MizAR project for Mizar proof automation and created tools like BliStr (Blind Strategymaker) and xsl4mizar (XML API for Mizar). Scientific Contributions ERC Grant : AI4REASON (formal math and AI synergy) Marie-Curie Fellowship : 2011-2013 POPL Committee : 2016-2023 Students & Collaborations Current and former PhD students include Mark Adams , Yutaka Nagashima , and Krystof Hoder . He collaborates with institutions like Radboud University , Charles University , and contributes to projects such as MathWiki and ProofGold .

• Cyber-Physical Systems
• Mobile Systems Security
• Wireless Systems Security
• +3 more

Daniele Antonioli is an Assistant Professor in Digital Security at EURECOM, France. His research focuses on securing Cyber-Physical Systems (CPS), Mobile/Wireless Systems, Embedded/IoT devices, and Industrial Control Systems (ICS). He specializes in applied cryptography and system-level security, addressing vulnerabilities in emerging technologies such as Bluetooth, FIDO2, and vehicular networks. Maintains a lab focused on reverse engineering, hardware-software co-analysis, and automated security testing frameworks. Developed tools like MiniCPS and CPSBot for CPS/IoT security research. Research interests include: - Bluetooth Exploitation : BIAS, KNOB, BLURtooth attacks. - Embedded Systems Security : E-Trojans, E-Spoofer, Breakmi. - Privacy-Preserving Systems : Decentralized contact tracing protocols. - IOT/IICS Threat Modeling : AttackDefense Framework. Publications highlight both technical contributions (e.g., SimProcess simulation framework) and practical impact (e.g., EmuOCPP for EV charging security). Recipient of Singaporean Presidential Graduate Fellowship (2015-2019) and ST Engineering Research Excellence Award (2017). Active in international collaborations, including EU-funded projects. Advises on CPSBot botnet simulation and FP-tracer browser fingerprinting detection systems. Engages in standardization efforts for secure industrial communication protocols.

• Computational Linguistics
• Natural Language Processing
• Lexical Semantics
• +3 more

Nicoletta Calzolari is a leading researcher at the Institute for Computational Linguistics (ILC) under the National Research Council of Italy (CNR) in Pisa. Her career spans decades of influential work in computational linguistics, language resource development, and standardization initiatives. She has co-chaired major conferences like LREC and COLING and contributed to EU projects (e.g., FLaReNet, META-NET) focused on multilingual NLP infrastructure. Research Interests: Calzolari specializes in: Lexical semantics and ontology development (e.g., Lexical Markup Framework). Multilingual language resource creation and interoperability. Corpus annotation standards and semantic lexicons. Reproducibility in language technology research. Publications: Her recent work emphasizes collaborative frameworks for resource sharing, large-scale lexical databases (e.g., WordNet integration), and infrastructure for sustainable language technology. Dominant themes include standardization, cross-lingual interoperability, and community-driven knowledge ecosystems. Leadership: She coordinates international consortia and editorial efforts, advancing tools and best practices for NLP resource documentation, access, and preservation.

Brad A. MyersView profile

Professor

• Human-Computer Interaction
• Programming Environments
• End-User Software Engineering
• +5 more

Brad A. Myers is the Charles M. Geschke Director and Professor in the Human-Computer Interaction Institute (HCII) at Carnegie Mellon University's School of Computer Science, with an affiliated faculty appointment in the Software and Societal Systems Department. He leads research focused on making programming more accessible through human-centered methods. Education: PhD in Computer Science, University of Toronto MS and BSc degrees, Massachusetts Institute of Technology Research: Myers' work spans user interface software, programming environments, end-user software engineering (EUSE), API usability, and interaction techniques. His Natural Programming Lab develops tools to democratize programming through novel interaction paradigms and AI-assisted development tools, with recent focus on LLM integration and developer experience (DevX) optimization. Publication Trends: Recent articles demonstrate a strong focus on human-AI collaboration in software development, particularly in API usability, automated testing, documentation systems, and programming assistance tools. His work consistently bridges HCI principles with practical software engineering challenges. Awards: ACM SIGCHI Lifetime Achievement Award in Research (2017) Alan J. Perlis Award for Imagination in Computer Science (2022) CBI Human-Computer Interaction History Prize (2025) IEEE Fellow, ACM Fellow, CHI Academy Member 19 Best Paper Awards, 6 Most Influential Paper Awards Students & Projects: Has advised over 30 PhD/Master's students on projects including Natural Programming, Pebbles (handheld computing), RADAR (adaptive reasoning systems), and ConstraintJS. Current projects explore API usability, conversational agents for programming, and developer sensemaking tools. Labs & Affiliations: Directs the Natural Programming Lab at HCII. Consults for over 90 companies on UI design/implementation. Teaches courses on interaction techniques and user interface software.

Natalie Hempel de IbarraView profile

Associate Professor

• Animal vision
• Learning and memory
• Insect behaviour and active sensing
• +7 more

Dr. Natalie Hempel de Ibarra is an Associate Professor in Neuroethology at the University of Exeter's Psychology Department . She co-directs postgraduate research training and leads the Exeter Bee Lab, which investigates insect cognition, sensory processing, and pollinator-plant interactions . Her work combines behavioral experiments , physiological studies , and spectral data analysis to understand how Apis mellifera and Bombus terrestris navigate complex environments. Academic Leadership: Co-Director of Postgraduate Research for Psychology Research Focus: Sensory ecology, insect navigation, cognitive stressors Collaborations: H. Somanathan (IISER Thiruvananthapuram, India) Research Themes Insect Vision: Modeling photometric data to understand flower perception under natural illuminations Cognitive Stressors: Studying pesticide/pathogen effects on foraging and navigation Active Sensing: Analyzing learning flights and sensory acquisition strategies Media Impact Featured in BBC News , The New York Times , and SciShow for discoveries about floral humidity detection and temperature cues Collaborative work on magpie behavior highlighted in The Guardian and The Washington Post She has held visiting appointments at Sokendai (Japan) and Freie Universität Berlin. Funding sources include BBSRC , Leverhulme Trust , and Royal Society .

Remco DijkmanView profile

Professor

• Business Process Management
• Data-driven Optimization
• Quantitative Business Process Analysis
• +4 more

Remco Dijkman is a Full Professor in Information Systems and chair of the Information Systems group at Eindhoven University of Technology (TU/e) within the Industrial Engineering and Innovation Sciences school. He leads research in Business Process Management with a focus on data-driven optimization of business processes. His work bridges theoretical advancements with practical applications in transportation and high-tech supply chains. Dr. Dijkman received his PhD and Master's degrees in computer science from the University of Twente. His academic journey includes visiting positions at New York University, Hasso Plattner Institute, IBM Zurich Research Lab, Humboldt-University Berlin, and Queensland University of Technology. PhD in Computer Science - University of Twente Master's in Computer Science - University of Twente Professor Dijkman's research focuses on the detection, diagnosis and prediction of optimal execution scenarios, mathematical models for quantitative analysis of business processes, and resource assignment optimization. His work integrates advanced techniques including queueing models, stochastic programming, and deep reinforcement learning to solve complex business process challenges. He has particular expertise in applying these methods to transportation logistics and high-tech supply chain planning, where he investigates how data-driven predictions can improve transport order assignment and supply chain planning. His recent publications demonstrate a strong trend toward integrating artificial intelligence techniques with traditional operations research methods. The research shows increasing sophistication in handling uncertainty in business processes, with a growing emphasis on real-time decision making and optimization. His work spans theoretical advancements in process modeling and practical applications in logistics and supply chain management, reflecting his commitment to bridging academic research with industry needs. Professor Dijkman serves on the editorial board of Information Systems journal and has published over 100 papers in prestigious venues including Information Systems, Computers in Industry, and Transactions on Software Engineering and Methodology. He currently leads or participates in several major research projects including DynaPlex, CERTIF-AI, SLEM, and FENIX. Additionally, he serves as research director for high-tech supply chain at the European Supply Chain Forum, a networking organization with over 50 multinational companies. His adjunct professorship at Queensland University of Technology demonstrates his international academic engagement. Professor Dijkman's research group focuses on developing advanced methods for business process analysis and optimization, with particular emphasis on handling uncertainty and making real-time decisions in complex business environments. The team works closely with industry partners to ensure practical relevance of their research, particularly in transportation and high-tech manufacturing sectors.

Rafael Ferreira da SilvaView profile

Assistant Professor

• Scientific Workflows
• Parallel and Distributed Computing
• High Performance Computing
• +7 more

Rafael Ferreira da Silva is a Research Assistant Professor in the Department of Computer Science at University of Southern California and a Senior Research Scientist at Oak Ridge National Laboratory. He serves as Group Leader for the Workflow and Ecosystem Services group at ORNL's National Center for Computational Sciences and is the Founder and Executive Director of the Workflows Community Initiative. Additionally, he is the Special Content Editor for the Future Generation Computer Systems journal and holds Senior Member status with both IEEE and ACM. Dr. Ferreira da Silva specializes in modeling and simulation of parallel and distributed computing systems, with expertise spanning scientific workflows, hybrid quantum classical systems, and autonomous science. His technical proficiency includes sophisticated scheduling algorithms, high fidelity modeling and simulation, multi-objective optimization, fault tolerant system design, and energy efficient computing across cloud, edge, and HPC environments. His research focuses on creating resilient digital infrastructures that dynamically adapt to changing research demands, accelerating scientific discovery through robust computational foundations. His recent publications demonstrate significant contributions to exascale workflow applications, HPC-quantum convergence, agentic workflow control mechanisms, and terminology standardization for scientific workflow systems. His work bridges multiple disciplines including high-performance computing, artificial intelligence, quantum computing, and autonomous laboratory systems, reflecting a broad research impact across computational science. Professional Recognition: Senior Member of IEEE Senior Member of ACM Special Content Editor for Future Generation Computer Systems journal With 149 scientific publications, 22 chair roles in conferences, 69 PC member roles in conferences, 18 research grants, and involvement in 270+ research projects, Dr. Ferreira da Silva maintains an extensive research portfolio and leadership position in the computational science community. His Workflows Community Initiative has fostered a thriving network of 51 international workflow users, developers, and researchers. As Group Leader at ORNL, he directs research efforts focused on advancing workflow technologies and their applications across scientific domains, with particular emphasis on creating interoperable systems that can operate across multiple computing facilities and environments.

• Cloud Computing
• Big Data Analytics
• Edge Computing
• +5 more

Ashiq Anjum is Professor of Cloud Computing at the University of Derby's School of Computing and Mathematics. He has established himself as a leading researcher in cloud computing, big data analytics, and related fields with over 145 publications spanning from 2003 to 2025. His research has consistently focused on advancing cloud infrastructure, distributed systems, and data analytics techniques. Professor Anjum's research interests encompass Cloud Computing, Big Data Analytics, Edge Computing, Blockchain, Machine Learning, Video Analytics, Internet of Things, and Distributed Systems. His work bridges theoretical advancements with practical applications, particularly in developing efficient systems for data-intensive computing environments. He has made significant contributions to optimizing cloud resource management, developing novel approaches for blockchain storage, and creating efficient machine learning architectures for edge devices. His recent publications reveal a strong trend toward integrating AI/ML techniques with cloud and edge infrastructure, with particular emphasis on explainable AI, physics-informed neural networks, and energy-efficient computing. His work spans both theoretical foundations and practical implementations across various application domains including healthcare, security, and industrial IoT systems. Professor Anjum has collaborated extensively with researchers worldwide, with notable long-term collaborations with Richard McClatchey, Lu Liu, Richard Hill, and Nick Antonopoulos. His research has appeared in top-tier journals including Future Generation Computer Systems, IEEE Transactions on Cloud Computing, and Journal of Cloud Computing. His research group has developed innovative approaches for video analytics in cloud environments, blockchain-based storage solutions, and edge-enhanced deep learning systems. Current projects appear to focus on digital twin technologies, explainable AI for decision systems, and adaptive resource management for distributed computing environments.

Guanhua ChenView profile

Assistant Professor

• Natural Language Processing (NLP)
• Large Language Models (LLMs)
• Applied Machine Learning
• +4 more

Dr. Guanhua Chen is an Assistant Professor in the Department of Statistics and Data Science at Southern University of Science and Technology (SUSTech). His research focuses on Natural Language Processing (NLP), Large Language Models (LLMs), and Multimodal AI, with applications in drug discovery and urban planning. He previously earned his Ph.D. from the University of Hong Kong and B.S./M.S. from Tsinghua University, with internships at Microsoft Research Asia and Huawei Noah’s Ark Lab. Education: Ph.D. in Computer Science (University of Hong Kong, 2022), B.S. and M.S. in Computer Science (Tsinghua University, 2012 & 2014) Dr. Chen's research explores LLMs, data synthesis, multimodal systems, and model compression. He leads a lab equipped with 16 RTX 4090 GPUs, 16 L40 GPUs, and 4 A100 GPUs, providing resources for students to experiment with open-source and proprietary LLM APIs. His recent publications highlight innovations in LLM jailbreaking, parameter-efficient tuning (MiLoRA), cross-lingual transfer (mCLIP), and evaluation frameworks for robustness testing. Notably, he was awarded the Microsoft Research Asia StarTrack Scholar in 2025. Key Publications: mCLIP (ACL 2023), ImPart (ACL 2025), MiLoRA (NAACL 2025) Dr. Chen actively seeks motivated PostDoc, PhD, and Master's students. He serves as an Area Chair for ACL and EMNLP and contributes to advancing AI through open-source projects like mCLIP on GitHub.

Cyrille ArthoView profile

Associate Professor

• Software Verification
• Software Engineering
• Concurrent Systems
• +5 more

Cyrille Artho is an Associate Professor at the KTH Royal Institute of Technology's School of Computer Science and Communication. He obtained his Master's and Ph.D. degrees from ETH Zurich, with research focused on finding faults in multi-threaded programs. Before joining KTH in 2016, he held research positions at the National Institute of Informatics in Tokyo and the National Institute of Advanced Industrial Science and Technology (AIST) in Japan. His research interests include: Software verification and software engineering Concurrent and networked systems Model-based testing and runtime verification Fault injection techniques Formal methods for distributed systems His recent publications demonstrate strong focus on model checking, test generation, and verification techniques for concurrent/distributed systems, with applications ranging from IoT protocols to Android devices. Notable trends include the development of specialized testing tools and formal verification approaches. Awards and recognitions: ACM SIGSOFT Distinguished Paper Award (ASE 2015) QRS 2015 best paper award Best tool competition winner at SBST 2015 He leads development of several verification tools including Modbat (model-based tester) and Java PathFinder extensions. He is also involved in the KTH Center for Cyber Defense and Information Security management group.

Deepak D'SouzaView profile

Professor

• Program verification
• Static analysis
• Model-checking
• +4 more

Deepak D'Souza is a Professor in the Department of Computer Science and Automation at the Indian Institute of Science (IISc) Bangalore. He has been actively involved in research and teaching in theoretical computer science, particularly focusing on program verification, static analysis, and formal methods. His work bridges theoretical foundations with practical applications in software engineering and verification. His research interests span program verification, static analysis, model-checking, and models and logics for real-time systems. D'Souza has made significant contributions to automata theory, particularly in its applications to verification problems. He co-edited the book 'Modern Applications of Automata Theory' published by World Scientific, which focuses on verification and model checking technologies. His recent work shows a strong emphasis on logical LTL games, controller synthesis, and verification of embedded systems. Analysis of his publications reveals a consistent focus on verification techniques across different domains - from theoretical foundations in automata theory to practical applications in embedded systems like FreeRTOS. His work demonstrates a progression from foundational theoretical work to increasingly applied verification problems, while maintaining strong theoretical rigor. Recent publications show growing interest in synthesis techniques and applications of formal methods to real-world systems. D'Souza has mentored numerous PhD, MS, and ME students, with a current focus on verification problems. His research has been supported by significant grants from Siemens, DRDO, Robert Bosch Center for CPS, UKIERI, and Infosys, demonstrating both academic and industrial relevance of his work. He is actively engaged in the academic community, serving as General Chair for ATVA 2025, Program Committee member for numerous conferences, and previously as President of the Indian Association for Research in Computing (IARCS) from 2018-2023. He also chairs the Steering Committee for FSTTCS (2025-2027). D'Souza teaches advanced courses including Automata Theory and Computability, Formal Methods in Software Engineering, and Program Synthesis meets Machine Learning, demonstrating his commitment to educating the next generation of researchers in formal methods and verification.

Qinghua LuView profile

Professor

• Responsible AI
• Software Engineering for AI
• AI Safety
• +5 more

Dr Qinghua Lu serves as Group Leader of the Software Systems Research Group at CSIRO's Data61 in Australia, where she leads pioneering research at the intersection of artificial intelligence and software engineering. With over 200 publications in premier international venues, she has established herself as a global authority in Responsible AI and Software Engineering for AI. Her research program focuses on two critical areas: Agent Engineering and Evaluation, and AI Safety/Responsible AI. She has developed architectural patterns for foundation model-based agents, reference architectures for trustworthy AI systems, and multi-layered safety frameworks including the influential Swiss Cheese Model for AI Safety. Her work bridges theoretical research with practical applications through tools like Prompt Sapper for AI chain development and SoapOperaTG for knowledge graph-based testing. Dr Lu actively shapes national and international AI policy as a contributor to Australia's AI Safety Standard, Frontier Model Forum, OECD.AI's trustworthy AI metrics, and the EU General-Purpose AI Code of Practice. She has received numerous accolades including the 2023 Asia-Pacific Women in AI Trailblazer Award and an ACM Distinguished Paper Award for her seminal work 'Towards a Roadmap on Software Engineering for Responsible AI'. As a prolific author, her book 'Responsible AI: Best Practices for Creating Trustworthy AI Systems' (2023) became Amazon's No. 3 AI book bestseller, recognized as the world's first responsible AI book for practitioners. Her follow-up work 'Engineering AI Systems: Architecture and DevOps Essentials' (2025) further establishes her leadership in AI system engineering. Dr Lu maintains active leadership in the academic community as Area Chair of Software Engineering for AI at ICSE'26, Program Chair for AIware'25 and CAIN'25, and associate editor for IEEE Transactions on AI. Her editorial service extends to multiple prestigious journals including Engineering Applications of Artificial Intelligence and IEEE Communications Surveys and Tutorials.

Mark SpragginsView profile

Professor

• Music Composition
• Music Production
• Recording Engineering
• +2 more

Mark Spraggins serves as Professor of Music Composition and Music Production Program Director at California Lutheran University, where his compositions have been performed internationally across the U.S., Norway, Sweden, France, and Italy, including work for Discovery Network television productions. His educational background includes degrees from Auburn University, Butler University's Jordan School of Fine Arts, and USC's Flora Thorton School of Music. As an undergraduate, he studied jazz piano under Bob Richardson and performed with the Auburn Knights Big-Band Jazz Ensemble. Dr. Spraggins' research focuses on Music Composition , Music Production , and Recording Engineering , highlighted by designing Cal Lutheran's Music Production degree program that tripled department enrollment during his 2013-2018 chairmanship. He spearheaded facility expansion including multiple production rooms and a $200,000 API Vision recording console installation in the K-building studio. Currently composing for Wave Boutique's production music catalog (licensing for film/TV/commercials), he maintains active industry engagement through memberships in the Society of Composers and Lyricists, Production Music Association, and Audio Engineering Society.

• Machine Learning
• Parallel and Distributed Computing
• Graph Theory
• +6 more

Giuseppe Agapito is an Associate Professor and senior research scientist at Magna Graecia University of Catanzaro, working within the Department of Law, Economics and Sociology. His academic profile spans both teaching responsibilities and active research in computational fields. His research focuses on computational intelligence techniques applied to complex real-world problems, particularly in machine learning, parallel and distributed computing, and graph theory. His work demonstrates strong interdisciplinary applications, especially in biology and omics sciences where he develops methods to leverage the vast amounts of data being produced. Agapito has published over 100 papers in international journals and conference proceedings. His recent publications show a strong focus on graph-based machine learning approaches, sentiment analysis techniques, and bioinformatics applications. His research trajectory indicates a progression from bioinformatics applications toward more general machine learning frameworks with applications across multiple domains. As an active member of the academic community, he serves as a reviewer for scientific journals and participates as chair and program committee member for national and international conferences. His editorial work for PeerJ Computer Science demonstrates his standing in the academic community. His teaching responsibilities include courses on Computer Science and Data Analysis within the Department of Law, Economics and Sociology, suggesting an interdisciplinary approach that applies computational methods to social sciences domains.

Shilad SenView profile

Professor

• Computer Science
• Data Science
• Human-Computer Interaction
• +7 more

Shilad Sen is a Professor and Chair of Computer Science at Macalester College in St. Paul, Minnesota, with a concurrent position as Principal Scientist at Microsoft. His academic appointment is within the Mathematics, Statistics, and Computer Science (MSCS) Department at Macalester College. Professor Sen's research focuses on member-maintained websites that empower Internet users to contribute valuable information, with particular emphasis on tagging systems, recommender systems, and combinations of the two. His work draws upon the fields of Human-Computer Interaction (HCI), data-mining, psychology, and computer systems design. He has made significant contributions to understanding geographic barriers in Wikipedia content and developing systems that help users better contribute to online communities. His research trajectory shows a consistent focus on understanding how people interact with information systems and how to design better systems that support community knowledge building. His work spans both theoretical contributions to understanding online communities and practical system development, including projects like Cartograph, Localness, WikiBrain, and Macademia. His recent work at Microsoft focuses on developing AI systems for products like Microsoft Outlook. Professor Sen teaches a wide range of computer science courses including Object-Oriented Programming and Data Structures, Internet Programming, and Collective Intelligence. His research has been published in top-tier venues including CHI, with his 2015 paper 'Barriers to the Localness of Volunteered Geographic Information' being particularly influential in understanding geographic inequalities in Wikipedia content. BA in Mathematics from Northwestern University (1999) BM in Saxophone Performance from Northwestern University (1999) PhD in Computer Science from University of Minnesota (2009) Before his academic career, Sen worked at Sourcelight Technologies building movie recommenders for companies like Blockbuster Video and Comcast, and also had positions at Google, IBM Research, Thomson Reuters R&D, and Target Corporation. Outside of academia, he is an avid jazz saxophonist and squash player.