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Yuwen Chen,
PhD at Duke

PhD in Electical and Computer Engineering

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Hi, my name is Yuwen Chen. I am an incoming PhD student at Duke University majoring in ECE. I received my ECE MS degree at Carnegie Mellon University. Prior to CMU, I finished my first master at Imperial College London and bachelor at University of Nottingham. Currently, I am focusing on research at the intersection of machine learning and medical imaging.

Research Interests

I am interested in the intersection area of machine learning and healthcare with the purpose of developing more accurate and robust clinical system. Basically, it can be divided into three aspects, which are computer vision, time-series data analytics and comprehensive model development. 

1. Computer vision: Images are one of the common types of data in medical diagnosis (e.g. MRI and CT). Therefore, computer vision plays an important role in multiple medical applications with the goal of assisting traditional diagnosis for better decision making. 

2. Time-series data analytics: Due to the rapid renewal of medical system, machine learning models based on prior data might suffer a large degradation as a result of data distribution changing and data population changing. Thus, it is crucial to acknowledge people when the degradation might happen and propose proper imputation methods to overcome these decays. 

3. Comprehensive model development: Facilitated by advanced medical devices, new types of data are keeping emerging. Exploring hidden features and thus, building up innovative machine learning models allow people to maximize the value of data. For example, establishing a machine learning system with dPCR data to help developing better multiplex assays for pathogen detection 


Helen, Z.*, Yuwen, C.* and Zachary, L., Model Evaluation in Medical Datasets Over Time, accepted by Conference on Health, Inference, and Learning (CHIL) 2023

Luca, M., Yuwen, C., et al, Smart-Plexer: a Breakthrough Workflow for Hybrid Development of Multiplex PCR Assays, Preprinted on Research Square 2022 (Presented at European Congress of Clinical Microbiology and Infectious Disease 2022)

Yuwen Chen, Blockchain in Enterprise: An Innovative Management Scheme Utilizing Smart Contract, Published in ICITM (IEEE International Conference on Industrial Technology and Management) 2020


Research projects

Recognizing transitional vertebra

Advisor: Professor Zachary C. Lipton (CMU)                                                 Aug. 2022 - present

  • Identified public spinal images to evaluate optional computer vision architectures

  • Established computer vision framework to recognize lumbar transitional vertebrae

  • Developed techniques to overcome imbalance labels

  • Increased model transparency for clinical validation

  • Co-led the project and updated progress with collaborators (Allegheny Health Network)

Exploring Potential Benefits by Rewinding to Plateau in General ML Model Training

Advisor: Professor Zachary C. Lipton (CMU)                                                 May. 2022 - present

  • Proposed the rewinding mechanism in general ML model training

  • Performed experiments to show the model improvement by rewinding to plateau during training

  • Incorporated beam search with rewinding mechanism to pursue further improvements

Investigating the Degradation of Real-World ML Healthcare Models Over Time

Advisor: Professor Zachary C. Lipton (CMU)                                                 Dec. 2021 - present

  • Identified multiple tabular medical datasets containing temporal information as test bed

  • Evaluated model performance over time in terms of different model classes and training regimes

  • Explored how data distribution shift over time affects the robustness of deployed models

  • Developed Python package (EMDOT) to facilitate community for machine learning in healthcare

Intelligent Algorithms for DNA Detection

Advisor: Dr. Jesus Rodriguez Manzano (Imperial College London)               Jan. 2021 - Aug. 2021

  • Processed data and successfully extracted features to translate from singleplex dPCR assays to multiplex

  • Designed ML-based algorithms to automatically develop multiplex dPCR assays. Reached 91% and 100% accuracy at well-level and sample-level on clinical samples, respectively

  • Completed high quality thesis (first class) and paper ready for submission

Graduation Project: Image Processing of Motorway CCTV Cameras

Advisor: Dr. David Ed Morris (University of Nottingham)                            Oct. 2019 - Jun. 2020

  • Implemented Hash algorithm using OpenCV function to calculate similarity between images and perform classifications

  • Analyzed offsets between images for alignment utilizing cross-correlation (Final mark in UK scale: 80/100)

GUI Development Used for Unconstructed Transmission Line Modelling Feedback

Advisor: Professor Phil Sewell                                                                   Jun. 2019 – Aug. 2019

  • Created file reader and a visual feedback system for significant data using Qt creator.

  • Added check functions, history browsing and dynamic tab widget to make user-friendly interface

  • Integrated with UI designed by other group members to build a commercial-level platform

Development of Blockchain System for Business Applications

Advisor: Professor David Siu-Yeung Cho (University of Nottingham)          Jun. 2018 - Aug. 2019

  • Utilized Remix and Solidity language to construct intelligent transaction system (smart contract) for car insurance system and entered final competition in 4th Maker Contests of Yinzhou Ningbo (top 15%)

  • Improved the security of the contract by adding safe math library, time control and authority control

  • Developed a local web interface using JavaScript and C language to make system more user-friendly


University of Nottingham (Sep 2016 - July 2020)

Title: Bachelor of Engineering (2 + 2) in Electrical and Electronic Engineering

GPA: 3.90/4.00


Imperial College London (Sep 2020 - Sep 2021)

Title: Master of Science in Electrical and Electronic Engineering

Track: Communications and Signal Processing

GPA: 3.82/4.00

Carnegie Mellon University (Sep 2021 - May 2023)

Title: Master of Science in Electrical and Computer Engineering

GPA: 3.96/4.00

 Social Activities



I successfully joined in campus badminton team in the University of Nottingham. I won the first prize in male doubles in Ningbo Badminton Competition in April 2017 and got the fourth prize in mixed doubles in Zhejiang Badminton Competition in May 2017.


With the strong skills in badminton, under the recommendation of the campus team, I became the badminton coach teaching primary school students in Ningbo voluntarily.


I became a member in the basketball team when I was in the University of Nottingham, Ningbo, China.

 Social Activities



During my time in the University of Nottingham, I became the director of International Department in SESA (Science & Engineering student association).


I participated in a volunteer program in Bali Island, teaching primary school students about English and math.


It is an unforgettable experience to join a group project at UNNC. We developed both hardware and software for automatic vehicles.

Social Activities


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