Bhawani Shankar Chowdhry

Work place: Department of Telecommunication Engineering, Mehran University of Engineering & Technology, Jamshoro, Sindh 76062, Pakistan



Research Interests: Theoretical Computer Science, Computer Networks, Computer Architecture and Organization, Computer systems and computational processes, Applied computer science, Computer Science & Information Technology


Bhawani Shankar Chowdhry - He is a renowned Scientist and ICT expert, Prof. BS Chowdhry is an Emeritus Professor and former Dean, Faculty of Electrical, Electronics, and Computer Engineering, Mehran UET Jamshoro. He has varied experience in diversified fields such as Electronics, Telecommunication, Microprocessor Technology, Internet o fThings, and Telemedicine, Wireless sensor network etc. After completing his first degree in an electronic engineering discipline in 1983, he did his PhD in Microprocessor Based Intelligent Instrumentation from the school of Electronics and Computer Science University of Southampton, UK in1990

Author Articles
Design of Microwave Pyramidal Absorber for Semi Anechoic Chamber in 1 GHz~20 GHz range

By Zahid Ali Badar Muneer Bhawani Shankar Chowdhry Shehroz Jehangir Ghulam Hyder

DOI:, Pub. Date: 8 Apr. 2020

In this paper, the design and development of wideband microwave pyramidal absorbers for semi anechoic chambers has been presented. This work is carried out with the goal of simulating and fabricating the microwave absorber using conventional and newest material such as polyurethane to save the budget cost with security and reliability. The simulation of absorber is performed via Computer Simulation Technology (CST) for the microwave frequencies 1 GHz to 20 GHz. The outcomes of simulation proved good absorbing efficiency and better RCS reduction compared to traditional microwave absorber. The reflection level is less than -30 to -10 dB over the desired frequency range of 1 GHz ~ 20 GHz.

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Off-line Sindhi Handwritten Character Identification

By Arsha Kumari Din Muhammad Sangrasi Sania Bhatti Bhawani Shankar Chowdhry Sapna Kumari

DOI:, Pub. Date: 8 Jun. 2019

Handwritten Identification is an ability of the computer to receive and translate the intelligible handwritten text into machine-editable text. It is classified into two types based on the way input is given namely: off-line and online. In Off-line handwritten recognition, the input is given in the form of the image while in online input is entered on a touch screen device. The research on off-line and online handwritten Sindhi character identification is on its very initial stage in comparison to other languages. Sindhi is one of the subcontinent's oldest languages with extensive literature and rich culture. Therefore, this paper aims to identify off-line Sindhi handwritten characters. In the proposed work, major steps involve in characters identification are training and testing of the system. Training is performed using a feed-forward neural network based on the efficient accelerative technique, the Back Propagation (BP) learning algorithm with momentum term and adaptive learning rate. The dataset of 304 Sindhi handwritten characters is collected from 16 different Sindhi writers, each with 19 characters. The novelty of proposed work is the comparison of the recognition rate for the single character, two characters and three characters at a time. Results showed that the recognition rate achieved for a single character is more than the recognition rate of multiple characters at a time.

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