Herodotos Herodotou, Ph.D.
Dr. Herodotos Herodotou is an Assistant Professor in the Department of Electrical Engineering and Computer Engineering and Informatics at the Cyprus University of Technology. He received his Ph.D. in Computer Science from Duke University in May 2012. His Ph.D. dissertation work received the SIGMOD Jim Gray Doctoral Dissertation Award Honorable Mention as well as the Outstanding Ph.D. Dissertation Award in Computer Science at Duke. Before joining CUT, he held research positions at Microsoft Research, Yahoo! Labs, and Aster Data as well as software engineering positions at Microsoft and RWD Technologies. His research interests are in large-scale Data Processing Systems and Database Systems. In particular, his work focuses on ease-of-use, manageability, and automated tuning of both centralized and distributed data-intensive computing systems. In addition, he is interested in applying database techniques in other areas like maritime informatics, smart power grid/microgrids, scientific computing, bioinformatics, and social computing. His research work to date has been published in several top scientific conferences and journals (e.g., PVLDB, SIGMOD, SoCC, CIDR), two books, and one book chapter. Learn more...
Elena Kakoulli, Ph.D.
Elena Kakoulli acquired a Ph.D. degree in Computer Engineering at the Department of Electrical and Computer Engineering and Informatics of the Cyprus University of Technology. She holds a Master’s degree in Computer Science from the University of Cyprus. Her research interests lie in the fields of computer architecture, on-chip interconnection networks, photonics, and systems for large-scale data analytics. She is funded by the "Distributed Multi-tier Storage for Cluster Computing" project.
Nicos Evmides holds a M.Sc. in Data Communication and Distributed Systems from University College London (UCL), UK and a B.Sc. in Computer Science from University of Indianapolis, USA. With a long-standing involvement in both Information Technologies and Business, Nicos is focusing in the research areas of data collection, data management, and data analysis methodologies aimed to address real world business needs in the maritime domain. He is funded by "Sea Traffic Management Validation Project" and "STEAM: Sea Traffic Management in the Eastern Mediterranean".
Sheraz Aslam received his M.Sc. degree in Computer Science with a specialization in energy optimization in smart grids from the COMSATS University Islamabad (CUI), Pakistan, in 2018. During his M.Sc. studies, he also worked as a Research Associate at CUI. He has authored more than 30 research publications in ISI-indexed international journals and conferences. His research interests include intelligent shipping, data analytics, generative adversarial networks, wireless networks, and smart grid/microgrids. He is funded by "STEAM: Sea Traffic Management in the Eastern Mediterranean".
Lambros Odysseos acquired his M.Sc. in Data Science and Engineering (2019) and his B.Sc. in Computer Engineering and Informatics (2017) from Cyprus University of Technology both with first student in class award. He has been working as a research associate in the past few years and his research interests include data analytics and visualizations, smart data processing, Internet of Things (IoT), machine learning, deep convolutional generative adversarial networks, and mixtures of factor analysis. He is funded by "STEAM: Sea Traffic Management in the Eastern Mediterranean".
Research Topic: Employing Data-Driven Analytics for Improving the Efficiency of Maritime Operations
Research Interests: Distributed Systems; Smart Data Collection and Analysis; Maritime Information Management Systems; Data Analysis for Business Applications
Research Topic: Smart Resource Management in Distributed Stream Data Processing Systems
Research Interests: Smart data processing; Data analytics and visualizations; Internet of Things (IoT); Deep convolutional generative adversarial networks; Data stream processing
Research Topic: Intelligent Data Analysis and Decision Support in the Maritime Industry
Research Interests: Intelligent Shipping; Data Analytics; Generative Adversarial Networks; Wireless Networks; Smart Grid/Microgrids
Research Interests: Scalable Databases; Big Data Systems; Data Integration; Wireless Sensor Networks; IoT
Co-advised with Dr. Michael Sirivianos
Topic: A Unified Mobile Framework for Multi-Wearable Applications
Topic: Bioinformatics Pipeline Optimization
Topic: Ship Monitoring and Early Warning System Using AIS Data
Topic: Visualizing Ship Routes in Real Time using AIS Data
Michael A. Georgiou, Ph.D. 2020, Enabling Workload Scalability, Strong Consistency, and Elasticity with Transactional Database Replication
Panagiotis Giangou, M.Sc. 2020, Streaming Detection of Cyberbullying in Social Media Using Supervised Classification Models
Dimitris Antoniou, M.Sc. 2020, Air Quality Modeling in Smart Cities with Wireless Sensor Network
Michael Panayiotou, M.Sc. 2018, Web Administration Interface for the Hihooi Database Replication Middleware
Theodoros Danos, M.Sc. 2018, SMACC: A Smart Cloud Caching System for Data-Intensive Applications
Omiros Polycarpou, M.Sc. 2018, MapReduce Task Scheduling over OctopusFS, a Storage-Aware Distributed File System
Υiangos N. Vitsaides, M.Sc. 2018, Key Performance Indicator Analysis for Port Collaborative Decision Making
Theodoros Theodorou, B.Sc. 2019, Performance Optimizations for a Smart Cloud Caching System
Salomi Xatzimilti, B.Sc. 2019, A Data Analytics Platform for Environmental Health Data
Elizabeth Pieri, B.Sc. 2019, Real-time Monitoring of Ships using AIS Data
Charalampos Kozis, B.Sc. 2018, Cuttlefish: A Middleware Platform for Connecting Heterogeneous IoT Devices
Christodoulos Hayiannis, B.Sc. 2018, WorkOmics: A Data Management Platform for Environmental Health Studies
Nicolas Karmiris, B.Sc. 2017, Web Interface for OctopusFS, a Storage-Aware Distributed File System
Maria Hadjigeorgiou, B.Sc. 2017, JDBC Driver for Hihooi, a Replication-based Database Middleware System
Ioanna Kyriakou, B.Sc. 2017, Performance-based Recommendation Tool for Differentiating Storage Tiers