Robotics and Automation Engineer
Building intelligent systems that bridge the gap between theory and application.
I build intelligent robotic systems that bridge the gap between simulation and reality. My work focuses on developing autonomous robots using reinforcement learning, advanced control systems, and physics-based simulation—then deploying them in real-world industrial environments.
Currently pursuing my Master's in Mechatronics, Robotics, and Automation Engineering at Arizona State University (GPA: 3.83/4.0), I specialize in:
MuJoCo-based locomotion, RL policy training (JAX/PyTorch), sim-to-real transfer
Model Predictive Control, inverse dynamics, torque control, Kalman filtering
PLC programming, SCADA, IIoT architectures (MQTT, OPC UA), warehouse robotics
Object detection, depth reconstruction, reinforcement learning for manipulation
Robotic Systems I & II, Mechatronic Systems, Experimental & Deployment of Robotic Systems, Industrial Internet of Things, Foldable Robotics, PLC Programming & Industrial Robotics
My approach combines rigorous physics simulation with practical deployment experience. Whether I'm training quadruped gaits in MuJoCo or integrating industrial robots on factory floors, I focus on building systems that work reliably in production. I'm passionate about making autonomous robotics accessible and practical for real-world applications.
I'm actively seeking opportunities in robotics R&D, industrial automation, and AI-driven manufacturing where I can contribute to building the next generation of intelligent robotic systems.
A cutting-edge robotic quadruped inspired by natural locomotion.
3rd place winning Honeywell x ASU hackathon project focused on passive geometry-driven automation for precision micro heat exchanger tube insertion.
Automated wafer handling system using Allen Bradley PLC, SCARA robots, and laser processing with coordinated motion control.
Physics-based 3D scene reconstruction using a robotic arm with an end-effector depth camera in MuJoCo.
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Optimized teach pendant programming for 6-object palletizing across 3x2 grid with dynamic position registers and ±2mm accuracy.
Bio-inspired four-bar linkage walking robot fabricated using foldable laminated structures and validated through MuJoCo physics-based simulation and hardware experiments.
Real-time wafer defect detection system using 5-layer IIoT architecture with edge ML achieving 94.5% accuracy and <50ms latency.
Hackathon-winning automation project for handling sequencing devices.
Voice-controlled integration of TurtleBot and MyCobot for intelligent mobile manipulation.
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Autonomous robotic arm using IK and CV to solve physical mazes.
Dynamic vision-based UAV landing system using real-time line tracking.
FarmPet: A cable-driven parallel robot designed for precision agriculture applications.
Smartphone sensor-based classification of human physical activities using ML.
Concentration in Systems Engineering
GPA: 3.83/4.0
GPA: 8.73/10.00
International Journal for Research in Applied Science & Engineering Technology (IJRASET)
February 2023
This paper presents the design and kinematic analysis of a novel cable-suspended parallel robot for agricultural applications. The proposed system offers high precision at low cost, making advanced farming techniques accessible to small-scale farmers.
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