I’m Andrés Cervera Rozo, a Robotics Engineer passionate about designing autonomous systems that bridge intelligent software and real-world hardware.
I earned my Bachelor’s in Mechanical Engineering with High Honours and Master of Engineering in Robotics from the University of Toronto. My work combines robotics, machine learning, data science, and electromechanical design to create intelligent machines capable of operating in complex environments. Read More
Robotics
Robotics
Developed a ROS2 autonomous navigation pipeline using Python, OpenCV, PyTorch, and LEDNet for real-time trail segmentation, combining YOLOv7, lidar, and camera fusion for pedestrian-aware robotic navigation.
Developed autonomous drone racing capabilities using Python, RRT*, and PyBullet, combining trajectory optimization, polynomial path fitting, and sim-to-real deployment on a Crazyflie quadrotor.
Analyzed petabytes of vehicle telemetry data using SQL and BigQuery to map global modem performance, integrating Mapbox visualizations to uncover geospatial trends in cellular connectivity.
Implemented deep learning-based semantic segmentation in PyTorch to classify outdoor trails, benchmarking multiple CNN architectures and optimizing LEDNet for accurate real-time robotic perception.
Built an AI financial advisor that screens 7,000 US stocks, reviews live brokerage holdings, and sends personalized HTML email digests and Telegram alerts using Claude, DeepSeek, and Gemini.
Designed an autonomous maze-navigation robot using Raspberry Pi and Arduino microcontrollers, integrating LiDAR, sensor fusion, and real-time communication via USB, I2C, and SPI protocols.
Projects spanning computer vision and robotic perception, combining deep learning and geometric methods for semantic understanding, 3D reconstruction, and visual navigation.
Projects in aerial robotics spanning UAV modeling, control systems, and autonomous flight planning, bridging simulation-based development with physical experimentation.
Exploring robotic localization through sensor fusion, SLAM, probabilistic filtering, and visual odometry to enable accurate state estimation in complex environments.
Exploring robotic motion planning through path generation, trajectory optimization, and autonomous navigation, balancing computational efficiency, safety, and optimality.
Projects spanning deep learning domains, from vision and language models to reinforcement learning, demonstrating how AI enables perception and control.
This section covers data science applications including large-scale data processing, geospatial analysis, and sensor analytics using SQL, Python, and cloud platforms.
Exploring embedded systems through hardware-software integration, featuring microcontrollers, real-time communication, sensors, and custom robotic prototypes.
Exploring hardware and power systems through battery testing, analog circuit design, PCB development, and instrumentation for high-performance systems.
Exploring mechanical design through CAD, simulation, and optimization using SolidWorks, ANSYS, and MATLAB, covering structures, mechanisms, and engineered systems.
Please feel free to reach out with any questions on my experience with these projects or to discuss a role that aligns with my past experiences.
