AATISH KAMBLE

Robotics Engineering graduate with a Master’s degree in Robotics and a strong foundation in autonomous systems, control, and machine learning. I have hands-on experience developing simulation-based robotic models, implementing closed-loop control frameworks, and building intelligent systems using Python, ROS, Gazebo, and C++. Through academic and practical projects, I have designed, integrated, and validated robotic solutions from concept to testing. I am seeking an initial engineering role where I can contribute to real-world robotics and automation systems while continuing to grow as a robotics professional.

Parkinsonian Tremor Modeling & CNN-Based Severity Classification

• Developed a neurorobotic simulation model to replicate Parkinsonian tremor dynamics.
• Implemented a Closed-Loop Deep Brain Stimulation (CL-DBS) control framework.
• Built a signal processing and feature extraction pipeline for tremor analysis.
• Designed and trained a CNN model for automated tremor severity classification.
• Integrated and validated the system within a robotic simulation environment (iCub, ROS).

Technologies: Python, TensorFlow, ROS, Gazebo, MATLAB

Wireless Tele-Operated Surveillance Robot

• Designed and developed a remotely operated mobile robot for hazardous environment surveillance.
• Integrated wireless communication systems for real-time video streaming and remote navigation.
• Implemented motor control logic and sensor integration for stable movement and obstacle awareness.
• Led end-to-end system integration including mechanical assembly, embedded programming, and electronics interfacing.
• Conducted performance testing and troubleshooting to improve stability and response time.

Technologies: Arduino, Embedded C/C++, Wireless Modules

Automated Conveyor-Based Product Sorting System

• Engineered an industrial automation prototype for automated weight detection and product counting.
• Integrated load cells and IR sensors for real-time classification and object detection.
• Developed microcontroller-based control logic for decision-making and actuation.
• Optimized system accuracy and processing efficiency through calibration and testing.
• Collaborated in system design, prototyping, and deployment phases.

Technologies: Arduino, Sensors & Actuators

Autonomous Obstacle-Avoiding Mobile Robot

• Built an autonomous robotic platform using ultrasonic sensors for real-time obstacle detection.
• Developed and implemented obstacle avoidance algorithms based on dynamic sensor inputs.
• Programmed motor control and sensor fusion logic using Arduino.
• Performed iterative hardware testing to improve navigation accuracy and stability.

Technologies: Arduino, Embedded Programming

• Machine Learning Certification – Internshala | 2023
  Supervised and unsupervised learning using Scikit-learn; implemented Linear Regression, Decision Trees, and K-Means clustering on real datasets.
• Core Python for Everyone – Udemy | 2023
  Python fundamentals, object-oriented programming, file handling, and debugging with hands-on coding exercises.

• Robotics and Emerging Technologies
• Problem-Solving Challenges
• Chess
• Reading Novels