Hello!

I'm Jigme.

A Robotics & AI Engineer passionate about machine learning and autonomous systems — specializing in crafting intelligent solutions that bridge technology and real-world applications.

Available for work
Robotics Engineer & AI Developer
Jigme Tsering

I'm Jigme Tsering—a robotics and AI developer with roots in Tibet and currently building my career in Toronto. My journey spans from the Himalayan region to the tech landscape of Canada, bringing unique perspectives to solving complex problems in autonomous systems and machine learning.

My passion lies in developing intelligent systems using Machine Learning to building and training neural networks. I thrive at the intersection of technical precision and creative problem-solving, creating solutions that bridge cutting-edge research with real-world applications.

Beyond code and algorithms, I'm a lifelong FC Barcelona supporter who's marveled at their tiki-taka philosophy and Messi's magic for over 15 years. When I'm not analyzing data, you'll find me on the football field or tennis court. Through my camera lens, I capture the unsimulated beauty of the real world.

Technical Skills

  • Python & Machine Learning
  • Robotics & Autonomous Systems
  • Computer Vision
  • Data Analytics

Tools & Technologies

  • TensorFlow & PyTorch
  • ROS
  • OpenCV
  • SQL

Improved 3D object detection by combining camera images and LiDAR point clouds. Extensive testing using detectors like Cascade RCNN and Voxel-RCNN on the KITTI dataset.

3D Object Detection
Python Computer Vision PyTorch

Analyzed public sentiment toward Ukraine in the Russia-Ukraine war using social media posts. Implemented multiple ML models including Logistic Regression, SVM, Random Forest, and XGBoost.

Sentiment Analysis Results
Machine Learning NLP Python

Implemented PPO, SAC, DQN, and DDPG algorithms for autonomous navigation in corridor environments using quadcopters. Environments created with Unreal Engine and Microsoft AirSim.

Reinforcement Learning Robotics Path Planning

A real-time theft detection system that uses Vision-Language Models (VLMs) and Large Language Models (LLMs) to analyze CCTV footage and identify suspicious behaviors in retail environments. The system goes beyond traditional object detection by understanding contextual human behavior and generating actionable alerts through semantic reasoning.

theft flow chart
Generative AI VLM LLM

Interested in collaborating or discussing technology? I'm always up for meaningful conversations about the future of technology and innovation.

Email [jigtse4@gmail.com]
Location Available remotely & locally
Status Available for work