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Ray Chen

1st-year PhD Student at Computer Science

University of Florida

About Me

I am a 1st-year Ph.D. student in Computer Science at the University of Florida, specializing in Human centered computing, especaily in interactive AI/ML and temporal-spatial data analysis. With a Master's in Electrical and Computer Engineering from the University of Washington and a Bachelor's in Physics and Astronomy from The Ohio State University, my expertise includes machine learning, data visualization, and human-centered AI. My research focuses on developing intuitive systems for actionable insights from complex data. I seek opportunities to collaborate on impactful interdisciplinary projects that address real-world challenges.

Research Interests

  • Human-Centered Computing

  • Interactive AI/ML

  • Fairness AI

  • Data Visualization

Education

  • Ph.D. in Computer Science (Expected graduation: 2028/05)

    University of Florida, Gainesville

  • MS in Electrical and Computer Engineering

    University of Washington, Seattle

  • BS in Physics and Astronomy

    The Ohio State Univeristy, Columbus

Academic Experience

Graduate Research Assistant

University of Florida

Aug 2024 – Present · Gainesville, FL

  • Leveraged interactive AI techniques to enhance model interpretability and improve detection accuracy.
  • Applied statistical and computational methods to analyze data trends, ensuring fairness and scalability of the developed solutions.
  • Contributed to the development of a framework for real-world applications in monitoring.
  • Advisor: Professor Christan Grant

Graduate Grader

University of Washington

Sep 2023 – Dec 2023 · Seattle, WA

  • Served as a grader for EE 215, evaluating homework assignments with consistency and accuracy.
  • Designed detailed grading rubrics to ensure fairness and clarity in evaluation.
  • Provided guidance and support by addressing student questions regarding homework assignments.
  • Answer the questions regraing to the homework assignmebntrs
  • Served courses: EE 215: Fundamentals of Electrical Engineering.

Undergraduate Teaching Assistant

The Ohio State University

Jan 2022 – May 2022 · Columbus, OH

  • Created and evaluated Python data analysis exercises for a class of 60 students, focusing on enhancing their data analysis and visualization skills in astronomy.
  • Attended assigned class and lab session to assist students in their development of basic skills in laboratories and lectures.
  • Graded assignments, hold office hours, and conducted review sessions to help students prepare for exams.
  • Coordinated the class schedule and resolved academic misconduct conflicts. Developed rubrics for NumPy assignments to ensure fair evaluation and grading consistency.
  • Served courses: Astronomy 1221: Astronomy Data Analysis and Visualization.

Undergraduate Research Assistant

The Ohio State University

June 2021 – May 2022 · Columbus, OH

  • The project is about the Pulsar Timing Analysis
  • Collaborated with a team to investigate pulsar timing and its application in detecting anomalies in pulsation periods caused by orbiting bodies.
  • Derived and implemented mathematical expressions for changes in radio pulse arrival times using orbital mechanics and pulsar timing models.
  • Designed and developed a Python-based computational notebook allowing users to simulate artificial pulse timing data for pulsar systems.
  • Incorporated instructional elements, background reading links, and visualization tools for educational purposes.
  • Advsior: Professor Donald Terndrup

Selected Projects

[Ongoing] Fair AI interface

Enable users to visualize the fairness of classifiers on video data in real-time by simultaneously adjusting various parameters.

'SettleIn' mobile app: Alleviating the challenges faced by young adults relocating to new areas.

We began with a thorough design research plan, conducted user research to understand needs, and performed a detailed task analysis to refine key functionalities. Insights from user research guided our initial sketches and storyboards, which were tested and iterated through paper prototyping. We then transitioned to digital prototypes to validate the user experience, culminating in a final presentation and poster showcasing the project's evolution.

Health monitoring system based on wireless perception

Developed non-contact wireless sensing technologies leveraging Wi-Fi and CSI analysis for behavior recognition and identity authentication. Designed algorithms for motion detection, noise reduction, and physiological signal monitoring using advanced techniques like Hampel filtering and SVM modeling. Contributed to a multi-signal sensing platform integrating UWB, Wi-Fi, and millimeter-wave signals for accurate indoor positioning and behavior monitoring.

Resulted in Patent CN116313093A, enabling applications in elderly fall detection, healthcare monitoring, and secure access systems.

Real-time Health Assessment and Early Warning Method Based on Perceptual Sampling Data

Developed intelligent wearable devices and wireless sensing systems for behavior correction and rehabilitation therapy, focusing on non-contact sensing, data transmission, and personalized health monitoring. Integrated edge-cloud computing for real-time data analysis, enabling precise monitoring of vital signs and behavior.

Resulted in Patent CN116386840A, with applications in rehabilitation for cerebral palsy patients, elderly care, and personalized healthcare systems.

Robotic Fuselage Inspection for Dents and Scratches sponsored by Airbus

The Robotic Fuselage Inspection project, sponsored by Airbus Robotics, aimed to automate and enhance the manual inspection of fuselage surfaces for defects like dents and scratches. Using a Fanuc CRX-20iA/L robotic arm, Intel RealSense camera, and a trained Inception V3 model (98.5% accuracy), the team captured and classified defect images, integrating the results into an AR application for precise defect visualization on 3D models. Simulated in ROBOGUIDE, the robotic arm's optimized scanning path enabled efficient panel coverage, while the AR app anchored and marked defect locations. This system significantly reduces inspection time, improving accuracy and scalability for future advancements.

Advisor: Professor Payman Arabshahi, Professor John Raiti

Industry Experience

Software Engineer Capstone Intern

Airbus Robotics(MTM Robotics)

Jan 2023 – Jun 2023 · Seattle, WA

Electrical Design Engineer Intern

State Grid NARI Group Corporation

May 2021 – Jul 2021 · Nanking, Jiangsu

Electrical Computer Engineer Intern

NR Electric Co., Ltd

May 2020 – Jul 2020 · Nanking, Jiangsu

Publications

External Service

Talks & Presentations

COMING SOON