Find Academic Supervisors

Rosario GiustolisiView profile

Associate Professor

• Computer Security
• Cryptographic Protocols
• Decision Systems
• +7 more

Dr. Rosario Giustolisi is an Associate Professor in the Department of Computer Science at the IT University of Copenhagen . His research centers on computer security with a focus on cryptographic protocols for decision systems (e.g., voting and exams), automated security analysis, accountability frameworks, and sociotechnical security aspects. Before joining ITU, he held postdoctoral roles at SICS RISE and Lund University, Sweden, and earned his PhD from the University of Luxembourg with work on secure exam protocols, culminating in his book Modelling and Verification of Secure Exams (Springer, 2018). Research Trends: His 15 most recent articles (2016–2025) span cryptographic protocol design, coercion-resistant voting/exams, zk-SNARK applications, differential privacy, automated security analysis, and sociotechnical threat modeling. Key subfields include secure decision systems, privacy-preserving mechanisms, and formal verification. Scientific Awards: Best Paper Award, NordSec 2017 Best Paper Award, SECRYPT 2014 Villum Experiment Grant (Sole PI) 2020 ICT TNG Postdoc Grant (Sole PI) 2016 CSC Best PhD Thesis Award 2016 Acknowledgments from Apple for Security Advisory Professional Service: Organized cybersecurity breakfast talks at ITU and served on conference committees for ACM SAC (Security track), STAST, E-VOTE ID, and NordSec. He also contributed as a journal referee and sub-reviewer for multiple conferences.

• Data Stream Management
• Real-time Data Analytics
• Data Quality
• +7 more

Sandra Geisler is a Junior Professor for Data Stream Management and Analysis at the Department of Computer Science, RWTH Aachen University, a position she has held since September 2021. She is also the leader of the Digital Health Spaces group at the Fraunhofer Institute for Applied Information Technology (FIT) in St. Augustin, reflecting her dual expertise in academic research and applied digital health solutions. Bachelor/Master: Diploma in Computer Science, RWTH Aachen University (2008) PhD: Doctoral degree in Computer Science, RWTH Aachen University (2016) Her research focuses on data stream systems, real-time analytics, data quality, and their applications in digital health and industrial processes. She has made significant contributions to ontology-based data quality management, edge computing for stream processing, and FAIR data principles. Recent work explores the integration of large language models into data management workflows and the development of privacy-preserving platforms for industrial data exchange. Her recent publications demonstrate a strong trend in distributed and edge-based stream processing, interdisciplinary applications in healthcare and supply chains, and the use of AI for data discoverability and quality. Topics include in-network computing, simulation of edge queries, self-tonometry for glaucoma, and cross-company data sharing with privacy awareness. She has served as Associate Editor for the Data & Knowledge Engineering Journal (Elsevier), Public Relation Chair for QDB Workshop (VLDB 2016), and Workshop Chair for IMMoA and HIMoA workshops. She has also edited a special issue on Information Management in Mobile Applications in the Pervasive and Mobile Computing Journal. Geisler has supervised multiple theses on topics including LLM-based ontology integration, edge anomaly detection, and data ecosystem modeling. She has been actively involved in research grants and projects related to industrial data processing, digital health, and sustainable production. She teaches courses such as Data Stream Management and Analysis and Data Ecosystems Lab. She leads the Digital Health Spaces research group at Fraunhofer FIT, focusing on innovative solutions for health data management and patient-centric digital tools. Her work bridges computer science, healthcare, and industrial applications, promoting secure, efficient, and intelligent data ecosystems.

Abdelhak M. ZoubirView profile

Professor

• Statistical Signal Processing
• Cooperative Sensor Communications
• Radar Imaging
• +5 more

Abdelhak M. Zoubir is a Professor of Signal Processing and Head of the Signal Processing Group at Technische Universität Darmstadt, Germany. He has held leadership roles including Head of the Department of Electrical Engineering and Information Technology (2012–2014 and 2020–2022), and President of the European Association for Signal Processing (EURASIP, 2017–2018). His research focuses on statistical signal processing with applications in radar imaging, biomedical engineering, and automotive systems. Zoubir has authored over 500 publications and is a Fellow of IEEE and EURASIP. He currently leads projects on radar communication integration, robust signal processing algorithms, and radiation-hardened sensor development. Education: Dipl.-Ing. (BSc/MSc) from Fachhochschule Niederrhein and Ruhr-Universität Bochum, followed by a Dr.-Ing. (PhD) in Electrical Engineering from Ruhr-Universität Bochum (1992). Research Interests: Bootstrap techniques, robust detection/estimation, cooperative sensor networks, radar for landmine detection, and automotive safety systems. He has pioneered methods in robust statistical signal processing, including low-rank matrix completion and sparsity-aware algorithms. Recognition: Recipient of the IEEE Meritorious Service Award (2018), IEEE Signal Processing Magazine Best Paper Award (2017), and the M. Barry Carlton Award (2014). He has been a keynote speaker at major conferences such as ICASSP and EUSIPCO, and served as Editor-in-Chief of the IEEE Signal Processing Magazine (2012–2014). Current Projects: Focus on automotive radar signal processing, radiation-hardened sensors (MALTA), and distributed learning robustness. His work bridges theoretical advancements with practical applications in defense, healthcare, and automotive industries.

• Physical Geography
• Soil Erosion
• Hydrology
• +7 more

Artemio Cerda Bolinches is a Professor in the Department of Geography at the Faculty of Geography and History, University of Valencia, Spain. His academic work centers on Physical Geography, with a strong emphasis on soil erosion, hydrological processes, land degradation, and wildfire impacts. He leads the SEDER (Soil Erosion Rates and Runoff Generation) research group, reflecting his leadership in environmental process studies. His educational background includes a PhD from the Universitat de València in 1993, with a thesis on soil infiltration in the Valencian region, supervised by Dr. Adolfo Calvo Cases. This foundational research has evolved into a prolific career in geomorphology and environmental change. Cerda Bolinches’ research interests span soil erosion dynamics , wildfire-soil interactions , sustainable land management , and Mediterranean environmental systems . His work integrates field experiments, modeling, and global meta-analyses, often using GIS and machine learning to analyze spatial patterns of erosion and degradation. He explores biological influences on hydrology, post-fire recovery, and nature-based solutions for flood and erosion control. His recent publications (2022–2025) reveal a strong trend in interdisciplinary environmental science, with frequent studies on machine learning applications in soil mapping, fire impacts on hydrology, and sustainability in agricultural systems. His work spans regions including Spain, Iran, China, Ethiopia, and Bangladesh, indicating broad international collaboration and relevance. While no specific scientific awards are listed in the provided text, his leadership in special issues and editorial contributions (e.g., introducing FIRElinks and fire-hydrology special issues) highlights recognition in the academic community. He is actively involved in advising and research supervision, implied by his PhD and research group leadership. His projects often address applied environmental problems, including soil conservation in vineyards, wildfire management, and climate change adaptation. He has contributed to policy-relevant studies, such as the EU Soil Observatory’s role in erosion monitoring. Cerda Bolinches is affiliated with the SEDER research group, which conducts long-term experimental studies on soil erosion, such as at the El Teularet-Sierra de Enguera experimental station in Valencia. This lab supports field-based research on erosion processes, land management, and sustainable viticulture.

Mehmet Fatih TuysuzView profile

Senior Lecturer

• Mobile and Wireless Multimedia Communications
• QoE Optimization
• Mobile Edge Computing
• +4 more

Mehmet Fatih Tuysuz is a Senior Lecturer at Northumbria University's Department of Computer and Information Science, joining in August 2020. He holds a PhD from Gebze Technical University (2013) and previously worked as a Research Assistant (2007–2013) and Assistant Professor (2013–2018) in Turkey. He also served as a Visiting Research Fellow at Middlesex University (2019). His research focuses on Mobile and Wireless Multimedia Communications, QoE optimization, Mobile Edge Computing for 5G/6G, Energy-efficient Techniques, Handover Strategies, and Software-Defined Networks. He has secured funding from national/international bodies and published extensively in top-tier venues. Recent work explores Edge Computing advancements for 6G, low-latency data aggregation, and QoE-driven video streaming. His articles address challenges in network resource optimization, sustainable IoT, and vehicular edge computing. He actively mentors students and welcomes applications for PhD/Master's programs in his research areas.

• Acoustic Pollution
• Low-Cost Noise Sensors
• Digital Signal Processing
• +1 more

Guillermo Quintero Perez is a Senior Lecturer at the Department of Mechanical Engineering , Technical University of Catalonia . His work focuses on acoustic pollution , low-cost noise sensors , digital signal processing , and noise mapping . He collaborates with researchers like Jordi Romeu and Andreu Balastegui on urban noise monitoring projects. Research Interests : Developing low-cost noise sensors for scalable urban monitoring Optimizing noise mapping through mobile sampling and data stratification Applying digital signal processing to environmental acoustics Investigating sound insulation properties of metamaterial structures Publications : His recent work (2024) includes studies on broadband noise reduction in acoustic windows and compliance testing for low-power sensors. Earlier contributions (2023-2017) explore statistical models for noise estimation, cluster analysis for temporal stratification, and sensor network deployment.

Mitra BaratchiView profile

Associate Professor

• Spatio-Temporal Data Analysis
• Machine Learning
• Mobility Data Modeling
• +5 more

Mitra Baratchi is an Associate Professor at the Leiden Institute of Advanced Computer Science (LIACS) , Leiden University. She leads the Spatio-temporal data Analysis and Reasoning (STAR) research group, co-leads the Automated Design of Algorithms (ADA) group, and founded the Special Interest Group on Spatio-Temporal Data Mining (SIG-SDTM) . PhD from University of Twente (Mobility Data) Master’s/Bachelor’s in Computer Engineering, Iran Research Interests focus on automated pattern extraction from spatio-temporal data across urban, environmental, and industrial domains. Key applications include: Automated Machine Learning (AutoML) for Earth Observations Time-Series Forecasting for public health (e.g., pandemic modeling) Urban Mobility Optimization with ESA, Honda, and municipalities Reliable Vehicular Communication Systems Smart Garments for Health Risk Detection Geocast Protocols for Internet-wide Communication Grant Highlights include €120K NWO-Aspasia, €2.9M Marie Skłodowska-Curie, €350K NWO-KLEIN, and €135K Center for BOLD Cities funding. She has supervised 12 PhD students and 4 current Master’s students since 2011, with notable best paper award at WWIC'16. Teaching includes Machine Learning (2020-present) and Urban Computing (2018-present) at Leiden, plus past courses in Data Visualization, Software Engineering, and Research Methods.

Nevins W. ToddView profile

Professor

• Interstitial Lung Disease
• Pulmonary Fibrosis
• Respiratory Physiology
• +2 more

Dr. Nevins W. Todd is a Professor in the Department of Medicine and Physiology at the University of Maryland School of Medicine. He serves as the Interim Medical Director for the University of Maryland Lung Transplant Program and former Fellowship Program Director. His clinical and research focus centers on interstitial lung disease and pulmonary fibrosis. Education: MD from University of Maryland School of Medicine (1986) Board Certifications: Internal Medicine (1989), Pulmonary Disease (1992), Critical Care Medicine (1993) Dr. Todd’s research explores interstitial lung disease (ILD) , pulmonary fibrosis , and respiratory physiology , using animal models and clinical data to elucidate disease mechanisms. His team investigates molecular abnormalities in lung tissue and correlates them with clinical outcomes. His recent publications examine fibrosis pathogenesis, including cytokine regulation (e.g., IL-33), inflammatory response mechanisms, and pharmacological inhibition of fibrotic pathways. Articles highlight the role of lymphocyte aggregation, alveolar collapse, and enzyme expression in disease progression. Dr. Todd has held leadership roles in lung transplant programs and pulmonary fibrosis networks, emphasizing clinical care integration with translational research. He collaborates with rheumatology experts to bridge immunological and respiratory disease pathways.

Jacqueline HendersonView profile

Associate Professor

• Upper Extremity Biomechanics
• Cumulative Trauma Disorders
• Carpal Tunnel Syndrome
• +3 more

Jacqueline Henderson serves as an Associate Professor in the Mechanical Engineering Department within Bradley University's Caterpillar College of Engineering & Technology. Her research focuses on biomechanics with specialization in upper extremity disorders and mathematical modeling applications. Her educational background includes a Ph.D. in Biomedical Engineering from Wayne State University, an M.S. in Mechanical Engineering from the same institution, and a B.S. in Mechanical Engineering from Prairie View A&M University. Joining Bradley in 2010, she has established herself as a key researcher in skeletal biomechanics. Ph.D., Biomedical Engineering, Wayne State University M.S., Mechanical Engineering, Wayne State University B.S., Mechanical Engineering, Prairie View A & M University Dr. Henderson's research centers on upper extremity biomechanics, particularly investigating carpal tunnel syndrome through mathematical modeling of subsynovial connective tissue shearing. Her work extends to cumulative trauma disorders and rehabilitation biomechanics, with significant collaborations between Bradley University and local medical communities. She employs advanced techniques including speckle-tracking ultrasound and finite element modeling to analyze tendon-nerve interactions in the carpal tunnel. Her publication record demonstrates consistent focus on biomechanical analysis of the carpal tunnel and spinal structures, with recent expansion into neurovascular coupling and Alzheimer's disease mechanisms. Key methodologies include ultrasound assessment, finite element modeling, and quantitative tissue property measurement. Professional recognition includes an NIH National Research Service Award fellowship at Mayo Clinic. She serves as a reviewer for the Journal of Applied Biomechanics and Journal of Clinical Biomechanics, and participates in Bradley University's Affirmative Action Committee. Dr. Henderson actively mentors STEM-interested youth and has developed educational initiatives including ME 101: Introduction to Mechanical Engineering and ME 591: Human Centered Design. Her service extends to K-12 engineering outreach programs in the Detroit Public School system.

• Decision Support Systems
• Energy Management
• Sustainable Energy Planning
• +8 more

Dr. Vangelis Marinakis is an Assistant Professor at the School of Electrical and Computer Engineering (ECE) of the National Technical University of Athens (NTUA). His academic background includes an Electrical and Computer Engineering degree and a PhD in Decision Support Systems for Sustainable Energy Planning from NTUA. PhD in Decision Support Systems for Sustainable Energy Planning (NTUA) Electrical and Computer Engineer (NTUA) His research focuses on designing methodologies for intelligent energy management across Smart Homes, Buildings, Cities, and Districts, leveraging technologies like IoT, AI, and Big Data. He has contributed to over 25 European (Horizon Europe, H2020) and national projects, with more than 50 journal publications and book chapters. Key research areas include Decision Support Systems , Energy Efficiency , and Renewable Energy Integration . He has led research in AI-driven energy forecasting, federated learning for privacy-preserving data models, and blockchain applications in energy markets. His work explores the intersection of Smart Grids , Building Informatics , and Climate Resilience . Dr. Marinakis has developed frameworks for: Decarbonization-as-a-Service in building renovations Scalable Big Data architectures for smart buildings Multi-criteria optimization of EV charging stations Explainable AI in energy decision-making Climate resilience assessment for urban housing

I.V. RamakrishnanView profile

Professor

• Artificial Intelligence
• Computational Logic
• Machine Learning/Computational Logic Combination
• +2 more

I.V. Ramakrishnan is a Professor in the Department of Computer Science at Stony Brook University. His research spans Artificial Intelligence, Computational Logic, Machine Learning, Information Retrieval, and Computer Accessibility. Ph.D. in Computer Science, University of Texas at Austin (1983) His work focuses on advancing AI and machine learning to solve accessibility challenges for visually impaired users, healthcare informatics, and robotic manipulation. Key contributions include leveraging large language models for multimodal text correction, developing gesture recognition systems for blind users, and applying reinforcement learning to medical data analysis. Recent publications highlight the integration of LLMs in accessibility tools, AI-driven healthcare solutions (e.g., mortality risk prediction, physician attribution), and robotics innovations (e.g., manipulation planning, vertical farming automation). Faculty Service Award (2014) He teaches courses CSE 352 (Artificial Intelligence) and CSE 537 (AI). His research bridges theoretical and applied domains, emphasizing inclusive technology and clinical decision support systems.

• Survey Methodology
• Economic Statistics
• Big Data Analysis
• +3 more

Daniele Toninelli is an Associate Professor of Economic Statistics (SECS-S/03) at the University of Bergamo's Department of Economics, where he also serves as Director of the 'Data Analyst for Strategic Decisions' program, Internship Manager for the department, and member of the School of Economics and Management's Joint Teacher-Student Commission. His educational background includes a PhD in Marketing for Business Strategies (University of Bergamo, 2009), Master's in Statistics for Market Research (University of Milan-Bicocca, 2004), and Degree in Statistical and Economic Sciences (University of Milan-Bicocca, 2003). Toninelli's research focuses on: Survey and web survey methodology design and optimization Integration of big data for economic and social indicators Development of price indexes and composite indicators Social media analytics for economic measurement His work bridges statistical theory with applications in labor markets, sustainability metrics, and environmental data analysis. Teaching activities encompass undergraduate and graduate courses including Economic Statistics, Quantitative Methods for Business Data Analysis, Advanced Business Statistics, and specialized 'Data Skills' modules covering visualization, survey methods, and SAS certification preparation. International research collaborations include visiting positions at Statistics Canada (2008-2013), University of Ottawa (2012-2013), VŠB-Technical University of Ostrava (2012-2013), RECSM at Universitat Pompeu Fabra (2014), and guest lectures at University of Ljubljana (2018). He previously served on the management committee of the WEBDATANET network (COST Action IS1004). Professional experience includes roles at PiTre Milan, IBM Semea/Celestica, and Multiplex Arcadia, applying statistical expertise in industrial settings.

Tiark RompfView profile

Assistant Professor

• Compiler Design
• Programming Languages
• Runtime Code Generation
• +8 more

Tiark Rompf is an Assistant Professor at Purdue University , with research spanning programming languages, compilers, and systems. His work bridges domains including architecture, databases, machine learning, and AI through projects like Reachability Types and Rhyme. Co-director of the Purdue Center for Programming Principles and Software Systems (PurPL) Scientific Advisor at SambaNova Systems Previously a member of the Scala team at EPFL His research focuses on: Runtime code generation and advanced compiler technology Expressive data-centric query languages (Rhyme, Datalog) Reachability type systems for memory safety and effect handling Metaprogramming and logical relations for formal verification Recent publications highlight contributions to Datalog compilation (Flan), nested data structures (Rhyme), and polymorphic reachability types. He leads projects exploring: Compiler optimizations for emerging architectures (GPU, TPU, FPGA) ML-driven compiler improvements Secure multi-party computation via metaprogramming Scientific awards include: NSF CAREER Award (2016) Google Faculty Research Awards (2017, 2018) DOE Early Career Research Award (2017) ACM SIGPLAN PL Software Award (2019) GPCE Test of Time Award (2020) Students and alumni from his group have joined institutions like Databricks, DeepMind, Galois, and Meta. He teaches advanced compiler courses including: CS 590 - Advanced Topics in Compilers CS 352 - Compilers CS 502 - Graduate Compilers

• Artificial Intelligence
• Decision Making under Uncertainty
• Machine Learning
• +6 more

Núria Agell Jané is a Full Professor in the Department of Operations, Innovation and Data Science at ESADE Business School. She also serves as a researcher at the ESADE D3 - Institute for Data-Driven Decisions. With a PhD in Applied Mathematics from UPC (Universitat Politècnica de Catalunya), her academic career spans several decades with significant contributions to artificial intelligence and decision science. Her research focuses on developing Artificial Intelligence techniques for decision making under uncertainty. Specifically, she works on systems with automatic learning, qualitative and fuzzy reasoning, multi-criteria decision making, group decision systems, recommendation systems, and consensus modeling. Her methodological approach combines theoretical foundations with practical applications in business contexts, particularly in marketing and strategic decision making. Her recent publications demonstrate a strong trend toward applying hesitant fuzzy linguistic approaches to complex decision problems across diverse domains including media analysis, food waste reduction, healthcare fraud detection, and sustainable energy planning. These works consistently integrate AI methodologies with real-world business challenges, showing her commitment to bridging theoretical research with practical applications. Professor Agell has directed or co-directed 11 doctoral theses and maintains active research collaborations with institutions including The University of Edinburgh Business School. She coordinates the Research Group Judgements and Decisions in the Market Place (JUICE), which focuses on applying AI to business decision contexts. Her research has been supported by multiple projects related to AI applications in marketing and business strategy.

B. Douglas BernheimView profile

Professor

• Behavioral Economics
• Public Economics
• Game Theory
• +7 more

B. Douglas Bernheim is the Edward Ames Edmonds Professor of Economics at Stanford University's Department of Economics. He serves as the Academic Council Faculty Director of Undergraduate Studies, overseeing academic programs and policies for undergraduate economics students. His research spans behavioral economics, public economics, game theory, and financial economics, with notable contributions to rationalizability in game theory, coalition-proofness, and behavioral welfare economics frameworks. Professor Bernheim has received prestigious recognitions including an honorary doctorate from the University of Zurich and the 2022 Exeter Prize for groundbreaking work in experimental economics. His work often bridges theoretical economics with practical policy implications, particularly in areas like financial education and addictive behaviors. Research Interests: - Behavioral Welfare Economics - Social Motives for Economic Choices - Financial Education Policies - Theories of Collusion and Market Structures His recent publications explore interventionist policies in welfare states, peer influence in financial decisions, and the empirical foundations of decision theories like cumulative prospect theory. Bernheim's work emphasizes rigorous experimental methods and real-world policy applications, reflecting his dual focus on academic theory and societal impact.