Yooseok Lim Hi! I am a Ph.D. student in the Department of Biomedical Engineering at the University of Massachusetts Amherst. I am advised by Prof. Hsiao-Chuan Liu. I am currently focused on advancing medical ultrasound technology with AI, specifically estimating mechanical and acoustic properties. My goal is to contribute to advances in medical technology and make a positive impact on the broader community. Email  /  GitHub  /  Google Scholar  /  CV

• 2026-06: 🎉 I was selected as a winner of the IEEE IUS 2026 QUASOS Challenge (a flagship ultrasonics conference).

• VLA-Based Autonomous Robotics for Medical Applications (Title Withheld for Blind Review)
  First author
• Assessing Senior Driver Safety through Trajectory-Level Inverse Reinforcement Learning: A Multidimensional Evaluation for Conditional Licensing
  Y. Lim, G. Shin, B. Jeon, H. Yang, M. Lim, J. Leigh
• Trustworthy ICU Care: Enhancing Clinical Safety via Out-of-Distribution Detection-Augmented Offline Reinforcement Learning
  Y. Lim, In-beom Park, S. Lee
• Generalizable Repetition Counting via Metric-Based Few-Shot Learning on Wearable Motion Signals
  Y. Lim, S. Lee
  arxiv

	Two-Stage Label-Efficient Deep Learning for Ultrasound Attenuation Estimation from RF Data Y. Lim, H. Liu IEEE International Ultrasonics Symposium, 2026 / accepted
	Large Language Model-augmented Offline Reinforcement Learning Framework for Sepsis Management in Critical Care Y. Lim, B. Jeon, S. Park, J. Lee, S. Choi, C. Jeong, H. Ryu, H. Lee, H. Yang npj Digital Medicine, 2026 url
	A Reinforcement Learning Framework for Personalized Anticoagulation Dosing in Critical Care: Integrating Batch-Constrained Policy Optimization and Off-Policy Evaluation Y. Lim, In-beom Park, S. Lee IEEE Access, 2025 url
	OMG-RL: Offline Model-based Guided Reward Learning for Heparin Treatment Y. Lim, S. Lee Biomedical Engineering Advances, 2025 url
	Mapping Interconnectivity of Digital Twin Healthcare Research Themes through Structural Topic Modeling E. Kim, Y. Lim Scientific Reports, 2025 url
	Multimodal sensor fusion models for real-time exercise repetition counting with IMU sensors and respiration data S. Lee, Y. Lim, k. Lim Information Fusion, 2024 url
	Machine learning-derived model for predicting poor post-treatment quality of life in Korean cancer survivors Y. Choe, S. Lee, Y. Lim, S. Kim Supportive Care in Cancer, 2024 url

Seoul National University Hospital , Rep. of Korea (Feb 2025 - Aug 2026)

Researcher
Prof. Hyun-Lim Yang and Prof. Byoungjun Jeon.

Chungnam National University , Rep. of Korea (Mar 2026 - Aug 2026)

Researcher

University of Massachusetts, Amherst (Sep 2026 - )

Ph.D. student in Biomedical Engineering

Soongsil University (Mar 2022 - Feb 2024)

M.S. in Industrial Engineering
Prof. Sujee Lee (currently at SKKU)

Soongsil University (Mar 2016 - Feb 2022)

B.S. in Industrial Engineering

Leave of absence for military service: April 2018 - Nov 2019

Driver Fitness Assessment System and Its Control Method. 2026

Exercised Data Processing Method and Electronic Device Performing the Same. 2024

Scholarships

BME Departmental Fellowship, University of Massachusetts, Amherst: Spring 2026 - 2027

Superior Acamedic Performance Scholarship, Soongsil University: Spring 2022 - Fall 2023

Awards

Winner, IEEE IUS 2026 QUASOS Challenge: Oct 2026

Gold Prize, Hyeongnam Science Award, Soongsil University: Dec 2021

	Development of an Intelligent (AI)-Based Assessment Algorithm for Evaluating Driving Fitness of High-Risk Drivers and Commercialization of a VR Driving Simulator Platform Korean National Police Agency 2026-05
	Development of an AI Model and Service Concept Based on Canine Activity Data Samsung Electronics 2023-09
	Development of a Course Recommendation System Based on Natural Language Data Soongsil University 2023-03
	Development of a Counting Algorithm Based on Human Activity Data Samsung Electronics 2022-09

	3D Medical Segmentation 2024-10 code This project implements 3D medical segmentation algorithms.
	Traffic Sign Detection 2022-03 code This project tackles traffic sign detection using multiple models across two datasets. It emphasizes cross-dataset evaluation to assess how well a model generalizes to different data distributions, addressing the challenge of distributional shifts.
	Autonomous Driving Temperature Measurement Robot 2022-01 code Development of an autonomous driving robot using computer vision, reinforcement learning, and edge computing technologies