Dr. Sujatha Moorthy | Artificial Intelligence | Most Cited Article Award
PHD at Sathyabama University, India
Β Dr. M. Sujatha is a seasoned professional with 22 years of experience, specializing in Wireless Sensor Networks and RF Antenna technology. Holding a Ph.D. from Sathyabama University, Chennai, her research focuses on developing and validating antenna models to enhance the efficiency of wireless sensor applications. As a Professor at KL University, Vijayawada, she has contributed significantly to academia, with numerous publications in reputable international journals. Driven by a passion for innovation, she is actively involved in cutting-edge projects, showcasing her expertise in machine learning, robotics, and high-resolution satellite remote sensing. A dedicated scholar, she continues to shape the future of technology.
Professional Profiles:
Education:
Ph.D., Sathyabama University, Chennai (July 2017) Faculty of Electronics Engineering, Highly Recommended M.E., Sathyabama University, Chennai (May 2006) Applied Electronics, I Class with Distinction B.E., Adhiparasakthi Engg. College, Madras University (May 1999) Electronics and Communication Engineering, I ClassΒ
Professional Experience:
Total 22 years of experience, with 16 years post M.E. Professor, KL University, Vijayawada, Andra Pradesh (December 2020-Till date) Professor, Saveetha School of Engineering, SIMATS (April 2019-December 2020) Professor, KL University, Vijayawada, Andra Pradesh (January 2017-March 2019) Associate Professor, Prathyusha Institute of Technology and Management (December 2003 β June 2016) Lecturer, Sri Ram Engineering College (June 2000-December 2003)
Professional Qualification:
FPGA Based Industrial Robotic Arm Controller, Design Engineering (Toronto), ISSN: 0011-9342 | Year 2022, Issue: 1, Pages: 2209 β 2215. Maze Solver Using Webots, Design Engineering (Toronto), ISSN: 0011-9342 Year 2022, Issue: 1, Pages: 2563 β 2568.
Research Focus:
Dr. M. Sujatha’s research spans varmetamaterialsious domains, primarily focusing on Wireless Sensor Networks (WSN), RF Antennas, and their applications in cutting-edge technologies. Her work includes the development of high-performance grouping schemes for WSN, innovative antenna designs inspired by metamaterials, and hardware design for biomedical video compression. Additionally, she explores AI-based traffic flow prediction models for connected and autonomous electric vehicles. Dr. Sujatha’s research extends to biometric voting systems, electronic voting machines, and the detection of fake news, showcasing a diverse expertise in wireless communication, IoT applications, and information security. Her multidisciplinary contributions demonstrate a holistic approach to technological advancements.
Peer Reviewer & Academic Engagements:
Dr. M. Sujatha, citation metrics and indices from Google Scholar are as follows:
Citations: 115 (All), 93 (Since 2018)
h-index: 6 (All), 6 (Since 2018)
i10-index: 4 (All), 3 (Since 2018)
Publications (TOP NOTES)
Grid Search for Predicting Coronary Heart Disease by Tuning Hyper-Parameters. cited by 11, publication date: 2022/4/20
Metamaterial Inspired Circular Antenna with DGS for Tetra Band Application, cited by 8, publication date: 2020/3/25
AI Based Traffic Flow Prediction Model for Connected and Autonomous Electric Vehicles, cited by 7, publication date: 2021/11.
AR-ESIHE and ARS-ESIHE-based image enhancement methods on 9oba pure and nano dispersed liquid crystalline compound, cited by 5, publication date: 2020/8
Design of Reconfigurable Integrated patch antenna in ISM band for IoT applications, cited by 5, publication date: 2020/7/23
Unconstrained Global Optimization Base Partial Transmit Sequence for OFDM PAPR Reduction, cited by 4, publication date: 2020/4/15.
Image enhancement using wavelet based image fusion and power law transform, cited by 2, publication date: 2020/5/15
Spectrum sensing based reconfigurable filter bank for multicarrier communication receiver, cited by 1 , publication date: 2020.
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