Jie Yu’s Personal Website on Github

Hello, my name is Jie and you can call me Jay. I am an experienced data scientist and machine learning engineer with backend software development experience and a diverse background in physics. My expertise spans natural language processing, computer vision, statistical analysis, and machine learning model development and deployment. With a deep curiosity for exploring the richness in data and the complexity of cutting-edge technologies, I thrive on tackling complex challenges.

With a passion for driving impactful solutions, I am constantly seeking opportunities to leverage my diverse skill set and experience to solve complex problems and contribute to innovative projects.

Skills

Machine Learning and Tools

My expertise consists of a wide array of machine learning frameworks and tools, including PyTorch, TensorFlow, SciKit-Learn, HuggingFace and Langchain. I’m proficient in developing and deploying robust machine learning models, leveraging the latest advancements in the field.

Natural Language Processing

My passion lies in natural language processing, with a focus on fine-tuning large language models for tasks such as text generation and sentiment analysis. I’m particularly enthusiastic about exploring performance metrics to assess these models’ efficacy, ultimately deriving valuable insights to drive impactful outcomes.

Computer Vision

In the realm of computer vision, I excel in adapting the innovative solutions, including Vision Transformer and CNN-based models, to address specific challenges in projects and tasks. From object tracking to 3D human reconstruction, I’m passionate about pushing the boundaries of visual intelligence.

Data Analysis

Drawing from my extensive experience in data analysis during my research in physics, I have developed a strong proficiency in extracting insights from dataset of any size. Whether it involves statistical inference, hypothesis testing, or exploratory data analysis, I am dedicated to uncovering the underlying patterns within complex data structures.

Experience

Amazon AWS - Software Developer Engineer

At Amazon AWS, I played a pivotal role in developing and deploying cutting-edge solutions to enhance the IoT Core Identity Service. From optimizing cache systems to integrating cloud infrastructure, I focused on driving efficiency and scalability.

SFL Scientific, a Deloitte Business - Data Scientist / Machine Learning Engineer

During my tenure at SFL Scientific, I spearheaded numerous projects spanning object tracking, 3D avatar generation, and language model fine-tuning. My contributions not only optimized performance but also drove significant business value for our clients.

MindMics Inc. - Data Scientist

At MindMics Inc., I leveraged my expertise in data cleaning, signal processing, and machine learning to enhance the reliability of biomedical device measurements. My work laid the groundwork for innovative solutions in healthcare analytics.

Academic Research

My academic background in high-energy physics has enabled me to contribute to pioneering research endeavors at institutions affiliated with the ATLAS Experiment at CERN. From developing pattern recognition algorithms to conducting particle physics simulations, my involvement spans from the discovery of the Standard Model Higgs Boson to the exploration of Beyond Standard Model Higgs Boson phenomena. These academic pursuits have not only honed my analytical mindset but also cultivated a robust problem-solving approach.

Education

I completed my Ph.D. in Physics through a Cotutelle program between the University of Paris-XI, France, and Nanjing University, China. This experience was pivotal in refining my research skills and maintaining a high standard of scientific inquiry. My academic journey began with a Bachelor of Science degree in Mechanical and Electrical Engineering from Shanghai University, laying the foundation for my interdisciplinary approach to coding and problem-solving.

Let’s Connect!

If you’re interested in collaborating on innovative projects or discussing the latest advancements in data science and machine learning, feel free to reach out. I’m always eager to engage with fellow enthusiasts and explore new opportunities for growth and collaboration.