Prof. Bruno Carpentieri  
University of Salerno, Italy

Speech Title: Understanding Data Compression: Acquired Knowledge and Practices
Abstract: Digital data compression has become a central topic in modern information technology. Without it, key innovations such as digital television, mobile communications, and broader digital data transmission would not be feasible. Compression is closely intertwined with clustering and learning, each representing dimensions of the same multifaceted problem. Interestingly, the insights gained from compression processes can inform both learning algorithms and clustering techniques. In this presentation, we will explore recent advancements in data compression and examine its deep connections with learning and clustering methodologies.

Biography: Bruno Carpentieri graduated in Computer Science at the University of Salerno, and then obtained the Master of Arts Degree and the Philosopy Doctorate Degree in Computer Science at the Brandeis University (Waltham, MA, USA).

Since 1991, he was first Researcher, then Associate Professor and finally Full Professor of Computer Science at the University of Salerno (Italy).

His research interests include data compression and information hiding.

He was Associate Editor of IEEE Trans magazine. on Image Processing and is still Associate Editor of the international journals Algorithms and Security and Communication Networks. He was also chair and organizer of various international conferences including the International Conference on Data Compression, Communication and Processing, co-chair of the International Conference on Compression and Complexity of Sequences, and, for many years, a member of the program committee of the IEEE Data Compression Conference.

He has been responsible for several European Commission contracts in the field of data compression (compression of digital images and videos).

He directs the Data Compression Laboratory at the Computer Science Department of the University of Salerno.

 

 

Assoc. Prof. Akbar Sheikh-Akbari  
Leeds Beckett University, UK

Biography: Akbar Sheikh-Akbari received the B.Sc. (Hons.), M.Sc. (Hons.), and Ph.D. degrees in electronic and electrical engineering. He is currently an Associate Professor (Reader) with the School of Built Environment, Engineering and Computing, Leeds Beckett University. After completing his Ph.D. at Strathclyde University, he joined Bristol University to work on an EPSRC project in stereo/multi-view video processing. He continued his career in the industry, working on real-time embedded video analytics systems. His main research interests include biometric identification techniques, color constancy techniques, image source camera identification, hyperspectral image processing, standard and non-standard image/video codecs, e.g., H.264 and HEVC, multiview image/video processing, image resolution enhancement methods, assisted living technologies, compressive sensing, camera tracking using retro-reflective materials, and signal processing.