Himaja Reddy

Developed a machine learning-based system for detecting and classifying ECG heartbeats using the MIT-BIH Arrhythmia Database. Applied ECG pre-processing and Butterworth band-pass filtering, extracted 19 heartbeat-level features, and trained a Random Forest classifier to classify beats into five arrhythmia categories. Achieved 99.15% accuracy with an overall F1-score of 0.94 and developed a web interface for ECG feature upload, visualization, and heartbeat prediction.

• Designed and simulated a 77 GHz compact 1×4 corporate-fed microstrip patch antenna array for 6G-enabled automotive radar using Ansys HFSS. • Developed a symmetric corporate feed network with quarter-wave impedance transformers and inset-fed patches to achieve efficient impedance matching and equal power distribution. • Performed parametric optimization of element spacing and substrate dimensions to enhance antenna performance, achieving optimal resonance at 77 GHz. • Achieved S11 = –30.87 dB, VSWR = 1.06, and a peak gain of 12.56 dB, meeting the design requirements for high-performance millimeter-wave radar applications. • Designed the antenna on Rogers RO3003 substrate and evaluated its suitability for 6G Integrated Sensing and Communication (ISAC) and autonomous vehicle radar.

Developed a prototype trolley that can be controlled through a mobile application via Bluetooth. • Enabled directional movement (forward, backward, left, right) • Integrated ultrasonic sensor for obstacle detection within 15 cm • Implemented using Arduino, Bluetooth module, motor driver, and battery power supply