I am currently taking the Master of Science degree in Computer Science at the University of California San Diego. I got my bachelor degree at the National University of Singapore. I am interested in fields such as Artificial Intelligence, Computer Graphics and Games, Database Systems, and Software Engineering. I hope to further expand in these fields and I am looking forward to meeting some awesome people.

Project demos: YouTube.

• University of California San Diego Sep 2025 - May 2027 (Expected)
  • Master of Science in Computer Science
• National University of Singapore Aug 2021 - May 2025
  • Bachelor of Computing in Computer Science

• J. Chen, et al. Private Chat in a Public Space of Metaverse Systems, arXiv
• J. Chen, Memory Assisted LLM for Personalized Recommendation System, arXiv
• J. Chen, et al. Enhancing Breast Cancer Cryoablation Training via VR Simulation, Manuscript in preparation, 2026

• Anand Bhojan's Lab at NUS | Research Assistant | Singapore | Jan 2025 - Aug 2025

  • Developed a VR-based surgical training simulator for breast cryoablation using Unreal Engine, providing a repeatable interactive alternative to traditional lecture-based or physical phantom training.
  • Reduces costs potentially by ~$300+ per training for each trainee by replacing single-use phantom models.
  • Collaborated with the National University Hospital to examine its effectiveness with 21 medical student participants.
  • Implemented key features including an in-game tablet for surgery planning, ultrasound imaging for 2D cross-sectional views of the breast, cryoablation processes, and a procedural point system that tracks surgical accuracy.

• Johnson & Johnson (JNJ) | Machine Learning Engineer Intern, Enterprise Observability | Singapore | May 2024 - Nov 2024

  • Developed an end-to-end time series data forecasting & anomaly detection pipeline with cutting-edge deep learning models and algorithms, which is later deployed on JNJ’s Kubernetes GPU cluster after containerized as a Docker image.
  • Exposed the service as an internal Flask API integrated into the J&J Grafana dashboards and used by ~500 engineers for real-time monitoring. Enabled access to expected patterns, capacity trends, faster incident triage, and proactive scaling.
  • Built a scalable ETL pipeline to extract and transform metrics from VictoriaMetrics database into model-ready datasets.
  • Designed and implemented hierarchical forecasting models (single/multiple step prediction). Implemented and experimented with advanced models including TFT (Temporal Fusion Transformer), N-Beats, and N-HiTS with Pytorch framework.
  • Incorporated feature engineering to capture weekly patterns from timestamps, achieving an average estimation error within 3.3% for metrics with the scale of 100%.
  • Led a team of 5 interns to develop a GPT-based advisory chatbot for sales reps. Integrated domain-specific embeddings to enable context-aware recommendations, improving users’ ability to prepare client visits and data-driven product guidance.

• Hunan Kylinsec Technology Co., Ltd | Back-end Web Developer | Changsha, China | Jun 2022 - Jul 2022

  • Deployed Master-Slave control clusters for Kylinsec’s cloud operating system on internal servers. Containerized cloud runtime environments using Docker within a CI/CD pipeline (Jenkins & Grails).
  • Fixed a CPU core allocation bug in the Zombie Cloud module that caused orphaned processes to consume compute resources, restoring up to 2% cluster capacity through optimizing scheduler and query logic with SQL queries.

• Memory Assisted LLM Recommendation System | Jun 2024 - Dec 2024

  • Developed an LLM-based recommendation system with ‘memory’ to research better recommendation precision with personalized history. Consolidated and analyzed user history with LLM before conducting recommendation tasks.
  • Extracted memory from each user preference data/watching history. Applied memory to predict ratings for unseen preferences, sorting memory by genre similarity.
  • Conducted extensive experiments on movie rating prediction tasks with MovieLens 100K Dataset. Improved memory efficiency and identified movie correlations by integrating external knowledge (e.g. IMDB rating, Director, Stars, etc).

• Private VR Chat Channels User Experiences in Casual Social | Aug 2023 - May 2024

  • Researched related voice control in the VR metaverse to improve user experiences.
  • Built simulators to model user scenarios and quantify user experiences. Formulated and tested four research questions to enhance user experience through private chat channels in social virtual reality.
  • Analyzed APIs of major VR platforms to design and test a private communication channel packet for enhanced user privacy.

• PPP Loan Risk Prediction with Spark | Mar 2024 - Apr 2024

  • Built a Spark-based ML pipeline on Databricks to process large-scale PPP loan data, including class rebalancing, missing-value imputation, feature selection, and train/test split preparation for loan status prediction.
  • Trained and evaluated a Random Forest classifier using PySpark ML with scalable feature engineering and preprocessing, enabling binary prediction of full repayment versus charge-off on real-world loan records.

• Photo De-hazing Using Machine Learning Techniques | May 2023 - Jul 2023

  • Implemented a photo de-hazing AI model to gain proficiency in image processing through machine learning.
  • Learned image processing acceleration through GPU and Cuda technology.

• TeamBuilder | Team Leader | National University of Singapore | Feb 2023 - Apr 2023

  • Developed a desktop application facilitating student contact management and multidisciplinary team formation based on diverse criteria.
  • Completed a 7k Loc brownfield project named TeamBuilder with three undergrads based on the project AddressBook Level-3 for a software development module at NUS.
  • Developed features to facilitate team management by users, and updated the GUI through SceneBuilder to display a team list created by users.
  • Organized weekly scrum meetings, assigning tasks for documentation, UI development, and testing.
  • Released project on Github

• Space-Lin | Individual Developer | National University of Singapore | Jan 2023 - Feb 2023

  • Carried out a 1.6k Loc greenfield project named Space-Lin for a software development module at NUS.
  • Designed and implemented task-tracking features, incorporating I/O redirection techniques for text UI testing.
  • Integrated Gradle in the project and added JUnit tests, studied GitHub-related techniques such as Markdown.
  • Developed a desktop application using JavaFX and SceneBuilder. Enhanced user experiences through refined GUI design.
  • Released project on Github

• Programming Language: Python, Java, Vim, Git, C++, C, C#, SQL, JavaScript
• Framework: PyTorch, PyTorch Forecasting, TensorFlow, Keras, Scikit-learn, CUDA, Spark, Hadoop, Flask, Unity, Unreal Engine, OpenGL, ROS2, Grails, JUnit5, JavaFX, VictoriaMetrics, Prometheus, Kubernetes, Docker, Jenkins, Grafana, PostgreSQL, Databricks

• 2025 Certificate of Distinction in the Computer Graphics and Games Focus Area
• 2025 Certificate of Merit in the Database Systems Focus Area
• 2025 The 26th STePS NUS School of Computing Term Project Showcase, Third Prize
• 2024 The 25th STePS NUS School of Computing Term Project Showcase, Best Project Award-Platinum
• 2024 National University of Singapore, Dean’s List