Muhammad Hammad Sarwar

PROFESSIONAL PROFILE Electrical Engineering undergraduate with a minor in AI, specializing in the intersection of nonlinear control, deep learning, and computer vision. Proven researcher at DRONEXAS Lab developing BiLSTM-enhanced control frameworks, complemented by practical experience in object tracking and classical CV techniques. Proficient in MATLAB/Simulink and Python, offering a strong ability to bridge theoretical modeling with visual perception for autonomous systems EDUCATION Electrical Engineering SEECS , Islamabad , 3.51 (2026) INTERNSHIP EXPERIENCE DRONEXAS Lab 03-Feb-2025 - 05-Sep-2025 During my tenure at the DRONEXAS Lab, SEECS, I have gained extensive hands-on experience in control systems and robotics. As a Control and Robotics Intern, I led the end-to-end assembly and validation of drone systems, implementing PID controls and Kalman filters to ensure stability and precise state estimation. My work extended to designing custom tethered drone solutions, which included 3D-printing mechanical components and integrating communication systems for public demonstration. Promoting to a Research Intern role, I shifted focus to advanced biomedical applications, developing nonlinear control strategies (SMC and TSMC) in MATLAB/Simulink for prosthetic joint regulation. I further innovated in this space by proposing a BiLSTM-assisted control framework that significantly improved predictive accuracy for gait references, a contribution currently under peer review FINAL YEAR PROJECT BiLSTM-Enhanced Nonlinear Control for Prosthetic Knee Joints in Gait and Health Applications, This project focuses on the precise regulation of prosthetic knee and hip joints by integrating nonlinear control theory with deep learning. I developed and simulated Sliding Mode Control (SMC) and Terminal SMC strategies in MATLAB Simulink, successfully improving transient performance for prosthetic actuation. To enhance system intelligence, I engineered a BiLSTM-assisted framework to predict control inputs from gait references, achieving high predictive accuracy with $R^2$ values of 0.95 for the hip and 0.88 for the knee. This research culminated in a manuscript titled "BiLSTM-Enhanced Nonlinear Control for Prosthetic Knee Joints in Gait and Health Applications," which is currently under peer review. TECHNICAL EXPERTISE Control, Communication, Signal Processing and Artificial Intelligence related skills • Control Systems: PID, Sliding Mode Control (SMC), Terminal SMC, State-Space Modeling, Kalman Filtering • Signal Processing: FFT, Spectral Analysis, MFCCs, Feature Extraction, Time/Frequency-Domain Analysis • Communication Systems: Digital Modulation (BPSK, QPSK, QAM), BER Analysis, AWGN Channel Modeling ...

Electrical Engineering undergraduate with a minor in AI, specializing in the intersection of nonlinear control, deep learning, and computer vision. Proven researcher at DRONEXAS Lab developing BiLSTM-enhanced control frameworks, complemented by practical experience in object tracking and classical CV techniques. Proficient in MATLAB/Simulink and Python, offering a strong ability to bridge theoretical modeling with visual perception for autonomous systems