Hello and Welcome!
I’m Jony Chen, an MS Mechanical Engineering graduate from Columbia University with a focus in Robotics and Controls. This site showcases my skills, experience, and projects. I’m always exploring new ideas, building impactful solutions, and looking for opportunities to grow. Thanks for stopping by!
Jony Chen
ROBOTICS & MACHINE LEARNING ENGINEER
Phone:
+1 (332)-288-8839
Email:
Address:
New York City, NY, United States
Date of Birth:
Oct. 9th, 1998
EXPERIENCE
2024-present
Data Science & Machine Learning Engineer
Python
Live Building Systems LLC
I am the first Data Science and Machine Learning Engineer at Live Building Systems, where I independently developed a machine learning model trained on millions of historical utility data points to detect water leaks. This solution automated a process that previously required extensive manual review, reducing workload by 30% and enabling efficient monitoring across seven thousand of buildings.
Feb. 2022-Aug. 2022
University of New South Wales (UNSW)
Undergraduate Student Researcher
Python, Abaqus
For my thesis, I developed a finite element model in Abaqus to simulate carbon fiber-reinforced laminates with curvilinear fibers. I implemented a custom Python-based iterative algorithm to align fiber paths with maximum principal stress, achieving a 76% improvement in damage initiation load over conventional designs. This work demonstrates my deep expertise in composite mechanics and integration of Python with Abaqus for advanced simulations.
June 2021-Aug. 2021
Mechanical Structure Engineer Intern
SolidWorks
Midea
At Midea, I designed and prototyped an innovative kitchen appliance capable of rapidly cooking and chilling by seamlessly integrating refrigeration and heating systems. Leveraging advanced mechanical design and CAD skills, I designed a reliable aluminum sleeve structure for contact cooling. This solution significantly enhanced thermal performance, reduced production risks, and achieved rapid cooling of 1L water from 95°C to 18°C within 25 minutes.
EDUCATION
2022-2024
Master of Science, Mechanical Engineering, Robotics
Columbia University
During my Master’s in Mechanical Engineering at Columbia University, I concentrated on Robotics and Control, and actively pursued relevant knowledge of AI and machine learning — a fusion that allowed me to explore the intersection of intelligent algorithms and physical systems. I immersed myself in courses like Robot Learning, Applied Robotics, Artificial Intelligence, and Applied Machine Learning, while applying this knowledge to hands-on projects ranging from Model Predictive Control, Motion Planning, to Behavioral Cloning and Deep Reinforcement Learning for robotic arms. These experiences sharpened both my theoretical foundations and my ability to design practical, data-driven systems that learn and adapt in real-world environments.​ Click to read more about the core courses I enjoyed the most at Columbia.
2017-2021
Bachelor of Engineering (Honours), Mechanical Engineering
University of New South Wales
(UNSW)
I earned my Bachelor of Engineering (Honours) in Mechanical Engineering from UNSW, where I built a strong foundation across Solid Mechanics, Engineering Mechanics, Control Systems, and Computational Methods. Through advanced courses like Finite Element Methods, Computational Fluid Dynamics, and Engineering Design, I developed a deep interest in simulation and design. The experience in Statistics and Programming laid the groundwork for my continued exploration of robotics, automation, and machine learning.
SKILLS
Python - Advanced
ROS2 - Advanced
SolidWorks - Proficient
Abaqus - Proficient
PyTorch - Advanced
Tensorflow - Proficient
SQL - Intermediate
Git - Proficient
EXPERTISE
Robotic Algorithms
With a strong foundation in mechanical engineering and a specialization in robotics, I’ve developed deep expertise in classical robotic algorithms including kinematics, dynamics, control, and motion planning.
Machine Learning
My expertise in machine learning lies in developing practical, data-driven solutions for real-world engineering problems. I've developed learning-based approaches to multiple robotics applications. I’ve also built supervised models for classification and regression tasks, with experience in preprocessing, feature engineering, and model evaluation.
Data Science
At Live Building Systems, I prepared and analyzed millions of utility readings to support infrastructure monitoring and resource optimization. With a strong grasp of statistics and domain understanding, I focus on turning raw data into reliable, decision-driving intelligence.