Find Academic Supervisors

David Dreyer LassenView profile

Professor

• Social Data Science
• Political Economy
• Public Finance
• +7 more

David Dreyer Lassen is Professor of Economics and currently serves as Rector of the University of Copenhagen, a position he assumed in 2025. He is affiliated with the Faculty of Social Sciences and the Department of Economics, and was previously the Center Director of the Copenhagen Center for Social Data Science (SODAS) and Vice-Chancellor for Research (2021–2025). His educational background includes a PhD in Economics (2002) and an M.Sc. in Economics (1998), both from the University of Copenhagen, with additional training as a visiting student at Harvard University (1999–2000). Lassen's research focuses on social data science , political economy , and public finance . He integrates applied machine learning, text-as-data methods, and administrative data to model social and economic life courses. His recent work emphasizes predictive analytics, privacy, and the societal implications of data science. The 15 most recent publications reflect a strong interdisciplinary trend, combining economics, political science, and computer science. Key themes include nation-scale social network analysis, climate change perception, behavioral public policy, urban sustainability, and the ethics and efficacy of big data in prediction. These works appear in high-impact journals such as Nature Climate Change , PNAS , and Journal of Politics . ERC Advanced Grant (co-PI, 2020–) ERC Starting Grant (PI, 2013–2017) Villum Foundation Synergy Grant (Joint PI, 2020–) Sapere Aude Research Leader (2011–2014) UCPH Interdisciplinary Grant 'Social Fabric' (PI, 2013–2017) DNRF Center of Excellence (CEBI) (co-PI, 2017–) Lassen has supervised 14 completed PhDs, 7 ongoing, and over 150 M.Sc. students. He founded the Master’s program in Social Data Science at the University of Copenhagen. He has received significant research funding as principal or joint investigator, demonstrating sustained leadership in large-scale academic projects. His advisory roles include the Independent Research Fund Denmark (chairman, 2019–2020), Statistics Denmark, and the Danish Competition Council. He leads or contributes to major research initiatives such as SODAS and the 'Social Fabric' project, fostering interdisciplinary collaboration between economics, computer science, and social policy. His work is frequently presented at elite institutions including Harvard, MIT, Stanford, and the World Bank.

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +5 more

António Raimundo is an Assistant Professor at Iscte - University Institute of Lisbon's School of Applied Digital Technologies, where he coordinates the Bachelor's program in Digital Technologies and Artificial Intelligence. He serves as an Integrated Researcher at ISTAR-Iscte focusing on Information Systems. His educational background includes a PhD (2023), Master's (2016), and Bachelor's (2015) in Computer Engineering/Information Sciences from the same institution. Research interests span: Core AI/ML : Deep Learning, Large-Scale Language Models, Neural Architecture Search Applied Technologies : Computer Vision for industrial inspections, UAV/drone systems for rescue operations Cross-disciplinary : IoT-enabled rehabilitation systems, telecom network optimization, and air transport analytics Publications demonstrate strong focus on industrial AI applications (65%) and real-time systems (35%), with recurring themes in sensor fusion, UAV autonomy, and efficiency optimization. Most works appear in Q1 journals like Sensors and IEEE Access .

• Multi-Criteria Decision Making
• Operations Research
• Optimization Algorithms
• +5 more

Grzegorz Filcek is a Researcher at the Department of Computer Science and Systems Engineering , Faculty of Information and Communication Technology , Wrocław University of Science and Technology, Poland. His work focuses on multi-criteria optimization , evolutionary algorithms , and scheduling with applications in transportation systems , logistics , and industrial automation . Email: grzegorz.filcek@pwr.edu.pl Office: Building C-3, Room 14, Janiszewskiego 11/17, 50-372 Wrocław His research spans multi-criteria decision-making , location-scheduling integration , and transportation network optimization . Recent work includes frameworks for Pareto optimal solutions in MIP and rescheduling trains under track closures . He also explores evolutionary computation for freight parking planning and carpooling systems . Key trends in his publications include multi-criteria optimization (2019-2024), evolutionary algorithms (2020-2021), and transportation/logistics applications (2016-2023). His work often combines mathematical programming with real-world problem-solving in supply chains , railways , and emergency power systems .

• Strategic Studies
• Military Strategy
• Cyber Strategy
• +17 more

Benjamin Jensen is an Adjunct Hurst Professorial Lecturer at American University's School of International Service and a professor of strategic studies at the Marine Corps University School of Advanced Warfighting. He also serves as Director of the Futures Lab and Senior Fellow in the Defense and Security Department at the Center for Strategic and International Studies (CSIS), where he leads research on AI, data science, and wargaming in modern conflict. His academic background includes a PhD and MA from American University, an MS from the National Intelligence University, and a BA from the University of Wisconsin-Madison. Dr. Jensen’s research centers on the evolving character of political violence, military innovation, and the integration of artificial intelligence into warfare. His work spans strategic studies, cyber strategy, wargaming, defense technology, and future operational art. He has led initiatives with DARPA, NATO, the U.S. Army, and other agencies to develop scenario-driven exercises and wargames. His focus includes AI benchmarking, drone warfare, and adapting military doctrine for the digital age. His recent publications, from 2022 to 2025, demonstrate a strong trend toward analyzing AI in statecraft, drone saturation strategies in Ukraine, and the transformation of military operations through technology. Themes include battlefield adaptation, deterrence through rare earths, and reimagining reserve forces as drone brigades. His work combines academic rigor with policy relevance, often bridging theoretical concepts with real-world military applications. Scientific awards include: American University School of International Service Award for Outstanding Teaching by a PhD Candidate (2008) Smith Richardson Foundation World Politics and Statecraft Fellowship (2008) Dr. Jensen has advised and collaborated with numerous government agencies and foundations, including the Office of Naval Research, OSD Minerva Initiative, Hewlett Foundation, and the U.S. Cyberspace Solarium Commission, where he served as senior research director. He has also supported ECOWAS in developing human security frameworks. His leadership in research grants and policy projects underscores his influence in national and international security discourse. He leads the Futures Lab at CSIS, which pioneers AI applications in wargames and scenario exercises, covering topics from major war and national mobilization to economic security and energy politics. His work fosters interdisciplinary teams focused on defense innovation and future conflict modeling.

Sasikumar PunnekkatView profile

Professor

• Dependable Software Engineering
• Real-time Systems
• Safety-Critical Systems
• +5 more

Roles & Affiliations: Professor in Dependable Software Engineering at Mälardalen University (MDU), leading the Dependable Software Engineering research group. Former Head of Software Test & Reliability Engineering at Indian Space Research Organization (ISRO), Director of BITS Pilani KK Birla Goa Campus (Mar 2015–Aug 2016), and Visiting Researcher at Ericsson since 2022 (funded by SSF's strategic mobility program). Education: PhD in Computer Science from University of York, UK (1997), focusing on schedulability analysis of fault-tolerant systems (awarded Commonwealth Scholarship). Research Interests: Real-time systems, dependability, software engineering, safety-critical systems, cybersecurity, and industrial IoT. Key focus areas include fault-tolerant scheduling, safety-critical software design, and system-of-systems analysis. Funding & Projects: Led major EU projects (InSecTT, SUCCESS, DAIS, EUROWEB series) and national initiatives. Coordinated large EU educational collaborations with Western Balkans/Asia. Active in projects like FORA fog computing platform and TSN networks. Awards & Recognition: 6 Best Paper Awards, Senior Member of IEEE, and frequent contributor to conference program committees (ETFA, HASE, DATE, etc.). Grants & Labs: Recipient of SSF strategic mobility funding. Research group develops solutions for automotive systems, industrial automation, and safety-critical infrastructure.

• Wireless Communications
• Machine Learning
• Network Security
• +6 more

Demosthenes Vouyioukas is an Associate Professor at the Department of Digital Systems, University of Piraeus. Previously, he served as a Professor at the University of the Aegean (2011–2024), Head of the Department of Information and Communication Systems Engineering (2019–2022), and Director of the MSc program 'IoT: Intelligent Environments in Next-Generation Networks' (2018–2022). He holds a Ph.D. in Electrical and Computer Engineering from NTUA and has extensive experience in R&D projects across Europe and Greece. Education: Ph.D., Electrical and Computer Engineering, National Technical University of Athens (2003) M.Sc. in Engineering-Economics, NTUA (2004) Diploma in Electrical and Computer Engineering, NTUA (1996) His research focuses on mobile and wireless communications, machine learning for network optimization, UAV/aerial systems, IoT, 5G/6G technologies, and network security . He has authored over 140 publications and serves as an Associate Editor for journals like Telecommunication Systems and Frontiers in Space Technologies . His work emphasizes secure UAV deployments, hybrid satellite-terrestrial networks, and AI-driven path loss prediction . Recent studies explore energy-efficient solutions and spectrum monitoring for next-generation systems. Awards & Memberships: Senior Member, IEEE Member, ACM and IFIP Member, Technical Chamber of Greece He has advised numerous projects, including the General Chair of the International Summer School on 5G Networks. His lab focuses on integrating emerging technologies for smart communication systems.

Wing LamView profile

Assistant Professor

• Software Engineering
• Software Testing and Analysis
• AI and Software Engineering
• +4 more

Wing Lam is an Assistant Professor at George Mason University's Department of Computer Science. His research focuses on Software Engineering, with an emphasis on Flaky Tests, Software Testing and Analysis, AI integration, and Dependability. He holds a PhD from the University of Illinois at Urbana-Champaign and a Bachelor's from the University of Washington. Lam has received prestigious awards including the 2024 GMU Research Rising Star Award and the ACM SIGSOFT Doctoral Dissertation Award for his work on flaky tests. His NSF-funded projects include CAREER initiatives to enhance software regression testing and a collaborative dataset for Android testing. Lam actively organizes workshops and serves on conference committees like ICSE 2025 and FSE 2024. He advises multiple graduate and undergraduate students in research areas such as test prioritization, automated debugging, and mobile app testing. His work bridges empirical software engineering practices with innovative tool development. Education: PhD in Computer Science, University of Illinois at Urbana-Champaign Bachelor's in Computer Science with Distinction, University of Washington Research Interests: Flaky Test Detection and Mitigation Continuous Integration/Deployment Optimization Automated Test Input Generation AI-Driven Software Testing Mobile App Testing Infrastructure Awards: 2024 GMU Computer Science Outstanding Research Rising Star Award ACM SIGSOFT Outstanding Doctoral Dissertation Award 2022 Google – CMD-IT FLIP Fellowship 2020 Advising & Grants: CAREER Grant: $618K for Flaky Test Research (NSF) Collaborative Research on Android Testing: $66K (NSF) Advises 6 PhD/Master's students and multiple undergraduates Labs/Teams: Leads a research group focused on automated software engineering and testing tool development, collaborating with institutions worldwide.

Haoran QiuView profile

Researcher

• AI/ML Systems
• ML for Systems/AIOps
• Distributed Systems
• +3 more

Haoran Qiu is a Systems Researcher at Microsoft Azure Research – Systems (AzRS), focusing on AI-driven cloud systems efficiency. He holds a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign (UIUC), advised by Prof. Ravishankar K. Iyer, and a B.Eng. in Computer Science from the University of Hong Kong (HKU). His research interests span AI/ML systems, cloud computing, distributed systems, and sustainability. He has interned at Google, Microsoft Research, and IBM Research. Notable awards include the 2023 ML Systems Rising Stars by MLCommons and the Mavis Future Faculty Fellowship. Education: Ph.D., Computer Science, UIUC (2024) B.Eng., Computer Science, HKU (2019) Visiting Student, University of Wisconsin-Madison (2018) Research Interests: Designing learning-based solutions for cloud systems Energy-efficient LLM serving and resource management Resilience and sustainability in hyperscale datacenters AIOps and ML-driven systems management Recent Contributions Include: Advances in thermal-aware scheduling for LLMs (TAPAS) Green computing strategies balancing SLOs and carbon emissions Queue management for large language models (QLM) Awards: Best Paper Finalist (L4DC 2024) Best Presentation Award (COMPSYS 2022) Multiple Fellowships and Scholarships Labs/Teams: Active in Microsoft Azure Research, contributing to cutting-edge ML-centric cloud systems projects. Collaborates widely with industry (Google, IBM) and academic institutions.

Huy VoView profile

Associate Professor

• Big Data Systems
• Data Science
• High-Performance Computing
• +3 more

Huy Vo is an Associate Professor in the Department of Computer Science at the City College of New York (CCNY), part of the City University of New York (CUNY) system. His research focuses on Big Data Systems, Data Science, High-Performance Computing, Large-Scale Visualization, and Scalable Display Building. He is affiliated with CCNY's School of Engineering and maintains an active website at https://www-cs.ccny.cuny.edu/~hvo/ . His work spans urban analytics, visualization technologies, and machine learning applications. Notable contributions include analyzing global urban road networks using GNNs, developing semiconductor-specific large language models (SemiKong), and optimizing fleet management for ride-pooling in NYC. He also explores public health technologies, such as asthma self-management apps and pandemic policy impact visualizations. Vo's research often integrates interdisciplinary approaches, combining geospatial data, computational modeling, and real-time systems. His recent work highlights trends in scalable computing, AR visualization, and data-driven decision-making in urban environments. No scientific awards are explicitly mentioned in the provided text. His advising and grants sections remain unspecified, but his extensive publication record indicates active research collaborations and grant-funded projects. The SAT-Hub project exemplifies his focus on smart urban infrastructure, while his work on visualization frameworks like Unitypic underscores innovations in interactive 3D systems.

• Deep Learning
• Reinforcement Learning
• Robotics
• +7 more

Glen Berseth is an Assistant Professor in the Department of Computer Science and Operations Research (DIRO) at Université de Montréal and a core academic member of Mila – Quebec Artificial Intelligence Institute. He holds the prestigious Canada CIFAR AI Chair position and co-directs the Robotics and Embodied AI Lab (REAL). Previously, he was a postdoctoral researcher at Berkeley Artificial Intelligence Research (BAIR) working with Sergey Levine. Dr. Berseth's research focuses on solving sequential decision-making problems for real-world autonomous learning systems, with particular emphasis on human-robot collaboration, reinforcement learning, and various advanced learning paradigms including continual, meta, multi-agent, and hierarchical learning. His work bridges theoretical machine learning with practical robotics applications, aiming to create more capable and adaptable robotic systems. He has published extensively in top venues for robotics, machine learning, and computer animation. His recent publications demonstrate a strong focus on exploration strategies, representation learning, and efficient reinforcement learning algorithms. These works address critical challenges in scaling RL to real-world applications, improving generalization across different robot morphologies, and enabling autonomous learning without extensive human supervision. His research has practical implications for robotics, power grid control, and other complex systems requiring adaptive decision-making. Canada CIFAR AI Chair Dr. Berseth mentors a large group of graduate students across multiple institutions, supervising PhD and Master's candidates working on diverse aspects of robot learning and reinforcement learning. His lab receives significant research funding through his CIFAR AI Chair position and likely other grants supporting his robotics and AI research. The Robotics and Embodied AI Lab (REAL) he co-directs serves as a hub for interdisciplinary research at the intersection of machine learning and physical systems, fostering collaboration between computer scientists, roboticists, and domain experts.

• Supply Chain Management
• Operations Research
• Logistics
• +3 more

Dr. Zehai Zhou is an Associate Professor in the Department of Finance, Information Systems, Economics, and Risk Management at the University of Houston - Downtown , where he has taught courses in information systems, database management, Java programming, and e-commerce since 2006. His academic focus spans supply chain management , operations research , logistics , and data-driven analytics and optimization . PhD in Management Information Systems from the University of Arizona MS in Forestry from the University of Illinois at Urbana-Champaign BAgri in Forestry from Agricultural University of Central China His research integrates information systems with business analytics , emphasizing supply chain solutions , database optimization , and educational technology . Recent publications (2003–2017) focus on e-commerce analysis, algorithm design, and pedagogical evaluations, reflecting interdisciplinary expertise in computer science , business , and education . Dr. Zhou actively contributes to academic governance through roles such as Committee Member on General Education, Web Oversight, and Faculty Senate, and serves as a Distributed Reader for the College Board’s AP® Computer Science A exam. He has reviewed conference papers for the International Conference on Cyber Warfare and Security and participated in curriculum development for computer forensics and cybersecurity.

Hang LiuView profile

Assistant Professor

• High-Performance Computing
• Graph Analytics
• Machine Learning
• +3 more

Dr. Hang Liu is an Assistant Professor in the Department of Electrical and Computer Engineering at Rutgers University. He previously held faculty positions at Stevens Institute of Technology (2019-2022) and University of Massachusetts Lowell (2017-2019). His research focuses on high-performance computing systems leveraging GPUs, FPGAs, and SSDs for graph analytics, machine learning, and numerical methods. He holds a Ph.D. from George Washington University (2017) and a B.E. from Huazhong University of Science & Technology (2011). Education: Ph.D. Electrical and Computer Engineering, George Washington University, 2017 B.E. Software Engineering, Huazhong University of Science and Technology, 2011 Research Interests: Dr. Liu's work spans high-performance computing (HPC), graph algorithms, machine learning acceleration, and numerical methods optimization. He develops novel architectures and algorithms for efficient processing of large-scale graphs and ML models on heterogeneous hardware, with applications in scientific computing and data analytics. His systems research emphasizes algorithm-hardware co-design for FPGAs and GPUs to achieve energy-efficient performance. Awards: Notable achievements include the IEEE CS TCHPC Early Career Award (2022), NSF CAREER Award (2021), and multiple best paper awards. He leads projects funded by NSF and industry partnerships, including AWS and Lawrence Berkeley National Lab. Advising & Grants: Advisor for multiple award-winning senior design projects and research grants. His work on AWS GraphChallenge and Berkeley Lab SRP Fellowships demonstrates sustained industry-academia collaboration. Labs/Teams: Active in the Rutgers High-Performance Systems (RHPS) lab, focusing on scalable graph analytics and ML infrastructure. Collaborates with interdisciplinary teams on AI-driven scientific discovery initiatives like DeepSpeed4Science.

• 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.

Christo WilsonView profile

Professor

• Algorithm Auditing
• Online Privacy
• Cybersecurity
• +13 more

Christo Wilson is a Full Professor in the Khoury College of Computer Sciences at Northeastern University, where he also serves as the Associate Dean of Undergraduate Programs. He is a faculty associate at the Berkman Klein Center for Internet & Society at Harvard University and an affiliate member of the Center for Law, Innovation and Creativity at Northeastern University School of Law. His research spans algorithm auditing, online privacy, cybersecurity, and the ethical implications of sociotechnical systems. His research focuses on increasing transparency and accountability in algorithmic systems. Key areas include algorithmic bias in hiring, search engine personalization, price discrimination, and online tracking. He leads the Algorithm Auditing Research Group and is co-developing the National Internet Observatory, an NSF-funded initiative to provide ethical, large-scale data on online behavior. His recent publications reveal trends in auditing major platforms like Google, Amazon, Uber, and YouTube, with a focus on fairness, transparency, and user empowerment. His work frequently appears in top venues such as IMC, CSCW, CHI, and Usenix Security, and has influenced policy debates on digital rights and AI regulation. Scientific Awards and Honors: NSF CAREER Award Sloan Fellowship (2019) Excellence in Research and Creative Activity Award, Northeastern Best Paper Award, ICWSM 2023 Outstanding Applied or Public Research Award, ICA IEEE Cybersecurity Award for Innovation (2017) Distinguished Paper Award, Usenix Security 2017 Wilson actively advises PhD and master’s students and has secured major funding from the NSF, Sloan Foundation, Mozilla Foundation, Knight Foundation, and the European Commission. He has played a pivotal role in the Sandvig v. Barr lawsuit, contributing to the Supreme Court’s decision in Van Buren v. US , which clarified the scope of the CFAA. He is also a leader in the FAccT (formerly FAT*) conference community. He leads research labs focused on algorithm auditing, PKI/TLS security, and online privacy. His team has developed open-source tools and datasets to empower researchers and regulators. The group’s work on dark patterns, ads.txt, and real-time bidding has provided critical insights into digital advertising ecosystems.

Wolfgang RhodeView profile

Professor

• Particle Physics
• Astroparticle Physics
• Cosmic Rays
• +11 more

Prof. Dr. Dr. Wolfgang Rhode is a faculty member in the Department of Physics at the Technical University of Dortmund. He is actively engaged in research on high-energy cosmic rays and multimessenger astronomy, utilizing data from Cherenkov telescopes (MAGIC, FACT, CTA/LST), neutrino telescopes (AMANDA, IceCube/GEN2), and radio telescopes (MeerKAT, GLOW). His work involves theoretical modeling and the development of simulation tools such as PROPOSAL and CORSIKA to interpret observational signatures. His research interests span particle physics, astrophysics, and data science, with a strong emphasis on machine learning and artificial intelligence. He collaborates extensively with computer scientists through the Collaborative Research Center 876 and the Competence Center Machine Learning Rhine-Ruhr (ML2R). Additionally, he explores philosophical questions concerning the epistemology of AI-driven knowledge acquisition. His group also investigates hardware requirements for experiments and applies findings to medical physics. The team contributes to teacher training programs in physics education. The recent research trajectory reflects a strong interdisciplinary approach, combining particle physics with cutting-edge computational methods, particularly in data analysis automation and simulation. These efforts are supported by national and collaborative research initiatives. Affiliation: Faculty of Physics, Technical University of Dortmund Email: wolfgang.rhode@tu-dortmund.de Office: Room CP-03-157, Otto-Hahn-Str. 4a, 44227 Dortmund Phone: +49 (0)231 755-3550 Fax: +49 (0)231 755-3688 Prof. Rhode leads a research group that participates in major international astroparticle physics collaborations. His work is supported by interdisciplinary grants, particularly through the Collaborative Research Center 876 and ML2R, which focus on machine learning applications in resource-constrained environments. The group mentors young scientists and contributes to academic training and curriculum development in physics. While no specific advisees are listed, the working group has responsibilities in teacher training, indicating involvement in student supervision and pedagogical development. The research team operates at the intersection of experimental physics, computational science, and philosophical inquiry, maintaining strong ties to both technological innovation and foundational questions in science. They are involved in hardware research for detectors and computing infrastructure, ensuring robust data acquisition and processing capabilities for large-scale experiments.