Yashwant Gupta  is a Professor and Centre Director at the National Centre for Radio Astrophysics (NCRA), Pune, India.  NCRA is one of the national centres of the Tata Institute of Fundamental Research (TIFR).  Prof. Gupta’s research interests are in the broad area of radio astronomy, which special emphasis on the studies of pulsars...

This issue brings to you our interview with Dr. Abhishek Mahesh Appaji, an active IEEE Signal Processing Society (SPS) Young Professional. I am working as an Institutional Coordinator for R&D and Assistant Professor at B.M.S. College of Engineering, Bengaluru, India. I obtained my Bachelor of Engineering in Medical Electronics with University Rank from BMSCE, and a Masters of Engineering (M.E) in Bioinformatics from University Visvesvaraya College of Engineering, Bangalore.

Dr. Behnaz Ghoraani is an Associate Professor and the founder and director of the Biomedical Signal and Image Analysis lab at the Department of Computer & Electrical Engineering at Florida Atlantic University (FAU). Before joining FAU, she was an Assistant Professor at the Department of Biomedical Engineering at Rochester Institute of Technology (2012-2016).

The IEEE Signal Processing Society Delhi Chapter has been selected as the recipient of the 2020 Chapter of the Year Award! The Chapter of the Year Award will be presented at the ICASSP 2021 Awards Ceremony in Toronto, Canada. 

EEE Signal Processing Society Vice President-Education Shrikanth (Shri) S. Narayanan invites nominations for the positions of Chief Editor, Signal Processing Repository (SigPort) and Chief Editor, Resource Center for a 3-year term starting 1 January 2022. Nominations must be received no later than 5 April 2021.

With the explosive growth of data, it is a heavy burden for users to store the sheer amount of data locally. Therefore, more and more organizations and individuals would like to store their data in the cloud. However, the data stored in the cloud might be corrupted or lost due to the inevitable software bugs, hardware faults and human errors in the cloud. 

Monte Carlo (MC) methods are a set of fascinating computational techniques that have attracted ever-increasing attention in the last decades. They are based on the simulation of random samples that are used for diverse purposes, such as numerical integration or optimization.