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Euripides G.Μ. Petrakis
Position: Professor, Lab. Director
Office: 145.A29
Phone: +30-28210-37229
Fax: +30-28210-37542
Email: petrakis   at intelligence.tuc.gr
Personal Page: http://www.intelligence.tuc.gr/~petrakis/

Short CV

Prof. Euripides Petrakis received Bachelor in Physics from the National University of Athens in 1986. He received a Ph.D in Computer Science from University of Crete, Dept. of Computer Science, since 1993. Between 1996 and 1998 he was a visiting professor at the Dept. Computer Science of York University, Toronto, Canada and a researcher at GMD/IPSI Institute, Darmstadt, Germany. He was awarded with an ERCIM fellowship in 1998. He is serving as professor at the Computer Science division, of Electrical and Computer Engineering Dept. of the Technical University of Crete (TUC), and since 2006, as director of the Intelligent Systems Laboratory. Prof. Petrakis is involved in research on computer vision and image databases (at the early stages of his career), on modern aspects of information systems (Web information systems, semantic Web) and recently, cloud computing and IoT. Prof. Petrakis has authored or co-authored over 120 papers with students he has supervised (as main or sole supervisor) in high quality journals and conferences (acceptance rate < 30%) and has over 4000 references to his published work (by Google Scholar). He is involved (as principal investigator or coordinator) in several research projects funded by the Greek Government and the EU and attracted over 2.5Meuros funding for TUC.

Education

Research Interests

Teaching

    Undergraduate Courses

    • AIS 413: Multimedia Data Management
      Description
      Processing, archiving, and searching multimedia information including documents, one-dimensional signals, still and moving images (video) in information systems and the Internet. Classic models of information retrieval (binary, relational, probabilistic), information clustering and clustering algorithms (partitional, hierarchical, hybrid algorithms), clustering applications grouping in document collections. Visualization of one-dimensional signals and images in multimedia systems. Feature extraction (color, texture, shape, and spatial relationships) from images. Retrieval methods for one-dimensional signals and images. Indexing techniques in information systems for documents and multimedia information (inverted files, k-d trees, grid files, R-trees). Design of information systems on the Internet, management and analysis of information on the Internet (PageRank and HITS methods). Basic processing techniques and analysis of still and moving images (video) in information systems. Compression techniques, JPEG, MPEG-1, 2, 4, 7 standards.
      Courses Portal Link: Multimedia Data Management
    • AIS 414: Machine Vision
      Description
      Basic principles and methodology of machine vision with emphasis on algorithms and applications of machine vision. Image formation, mathematical, geometric, colour, frequentist, discrete models. Basic image processing techniques (filtering, enhancement, normalization). Edge detection, first and second derivative operators. Image segmentation, methods for segmenting or enhancing regions and edges, thresholding techniques. Advanced segmentation techniques (merging and splitting regions and edges, relaxed ordering, Hough technique). Techniques for processing binary images, distance transforms, morphological operators, and region labeling. Analysis, representation, and recognition of images. Representation of edges and regions, representation and recognition of shapes, representation and recognition of structural content. Texture analysis and recognition, structural and statistical methods. Dynamic vision, estimation of motion, optical flow, and trajectory.
      Courses Portal Link: Machine Vision
    • COMP 211: Data Structures and Algorithms
      Description
      Abstract Data Types, implementation in Java, algorithm complexity, performance analysis of algorithms. Sorting in main and external memory, sorting algorithms: bubble sort, exchange sort, insertion sort, selection sort, quick sort, merge sort, k-way merge sort, radix sort. Stacks, queues, linked lists. Implementation of one-dimensional arrays and dynamic memory allocation. Trees, tree traversal, binary search trees, operations research in binary trees (search, insert, delete data). Implementation using arrays and dynamic memory allocation. Applications, Huffman codes. Graphs, graph traversal. Operations on graphs (search, insertion, deletion). Implementation of graphs and applications (minimum spanning tree, shortest path). Searching in main or external memory. Sequential search (binary search, interpolation search, self-adjusting search), Indexed sequential search, ISAM. Performance analysis of search. Hierarchical search trees, trees in main memory (binary search trees, AVL trees, optimal trees, splay trees), analysis of performance. Trees on the secondary memory (multi-way search trees, B-trees, B +-trees), VSAM. Tries, digital search trees, text tries, Patricia tries, Ziv-Lembel coding. Searching in text (KMP, BMH algorithms). Non-hierarchical search, hashing in the main memory, collision resolution, open addressing, separate chaining. Complexity of search. Hashing in external memory (dynamic hashing, extendible hashing, linear hashing). Performance analysis of search.
      Courses Portal Link: Data Structures and Algorithms

    Postgraduate Courses

    • AIS 603: Multimedia Data Management
      Description
      Processing, archiving, and searching multimedia information including documents, one-dimensional signals, still and moving images (video) in information systems and the Internet. Classic models of information retrieval (binary, relational, probabilistic), information clustering and clustering algorithms (partitional, hierarchical, hybrid algorithms), clustering applications grouping in document collections. Visualization of one-dimensional signals and images in multimedia systems. Feature extraction (color, texture, shape, and spatial relationships) from images. Retrieval methods for onedimensional signals and images. Indexing techniques in information systems for documents and multimedia information (inverted files, k-d rees, grid files, R-trees). Design of information systems on the Internet, management and analysis of information on the Internet (PageRank and HITS methods). Basic processing techniques and analysis of still and moving images (video) in information systems. Compression techniques, JPEG, MPEG-1, 2, 4, 7 standards. Video segmentation into shots, shot aggregates.
      Courses Portal Link: Multimedia Data Management
    • COMP 607: Machine Vision
      Description
      Basic principles and methodology of machine vision with emphasis on algorithms and applications of machine vision. Image formation, mathematical, geometric, colour, frequentist, discrete models. Basic image processing techniques (filtering, enhancement, normalization). Edge detection, first and second derivative operators. Image segmentation, methods for segmenting or enhancing regions and edges, thresholding techniques. Advanced segmentation techniques (merging and splitting regions and edges, relaxed ordering, Hough technique). Techniques for processing binary images, distance transforms, morphological operators, and region labeling. Analysis, representation, and recognition of images. Representation of edges and regions, representation and recognition of shapes, representation and recognition of structural content. Texture analysis and recognition, structural and statistical methods. Dynamic vision, estimation of motion, optical flow, and trajectory.
      Courses Portal Link: Machine Vision

Supervision

Publications

Funding

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