17 Jul 2019

Tel-U Organized STACOS Summer School 2019

BANDUNG, Telkom University – School of Electrical Engineering, Telkom University (FTE Tel-U) in collaboration with IEEE Signal Processing Society (SPS) Indonesia Chapter held a Summer School that took place from 15 – 20 July 2019 at El Royale Hotel Bandung.

Entitled Statistical Signal Processing and Compressive Sensing for Inference Problems (STACOS), this second event organized by FTE Telkom University will provide an understanding of the basics of statistical signal processing, machine learning and sensing/compression for inference problems, such as detection, estimation, and classification.

Dr. Fiky Suratman as chairman of the program explained that this activity was held to provide management and development of signals in statistical terms.

“The participants will recognize where the statistical processing is, so the material will be about Advanced Machine Learning, Sparse Sampling, and Compressive Sensing.”

Fiky added that this activity was attended by 19 participants from lecturers, students and professionals from several universities in Indonesia.

“Participants from summer school are diverse because our own targets range from students, Researchers from universities, besides R & D institutes, doctors, to practitioners from the industry,” he said.

Teachers in this 2019 Summer School are:

Dr. Sundeep Prabhakar Chepuri, Indian Institute of Science (IISc), India. Presenting the material about Sparse Sampling for Statistical and Graph Signal Processing

Dr.-Ing. Fiky Y. Suratman from Telkom University Indonesia. Presenting material about Fundamentals of Statistical Signal Processing: Detection and Estimation Theory material

Prof. Andriyan B. Suksmono, Ph.D., Bandung Institute of Technology (ITB), Indonesia & Dr. Koredianto Usman, Telkom University, Indonesia. Presenting material about Theory and Applications of Spectrum Sensing material.

Dr. Suryo Adhi Wibowo, Telkom University, Indonesia. Presenting material about Supporting 5G era material using Artificial Intelligence.