The Cyber-Physical Systems Integration Lab, under the direction of Professor Lui Sha, is currently seeking undergraduate and master students with diverse backgrounds and skillsets to assist in two projects in healthcare.

Project 1
Interpretable Medical AI: this project aims to find the harmony between AI and established medical knowledge. We will explore technologies to systematically embed human body hierarchy and medical logic in machine learning models, and therefore obtain interpretability, accuracy, as well as training efficiency.

Tasks include but are not limited to-
1. Medical dataset setup and time series data preprocessing.
2. Evaluating models such as probabilistic graphical models and time series models.
3. Understanding medical knowledge and formalizing it in AI models.

Project 2Clinical Decision Support System (CDSS): this project computerized clinical best practice guidelines into interactive software that can provide situation-specific guidance to healthcare providers during acute care.

Tasks include but are not limited to-
1. Clinical guideline knowledge base representation and implementation.
2. Graphical user interface implementation and frontend-backend communication.
3. Clinical evaluation result analysis.

Applicants are expected to have experience in any or all of the following:
• Strong programming skills in Python, and machine learning tools such as PyTorch, pandas, and sklearn.
• Working knowledge in probabilistic and statistical theory.
• Working knowledge in formal methods and program verification.
• Programming skills in full-stack software development, familiarity with React.
• Self-motivated, interest in medical knowledge, self-learning capabilities and a positive and respectful attitude.

Desired qualifications
• Experienced in the above topics
• Interested in doing research
• Self-motivated
• Ability and willingness to learn
• A positive and respectful attitude

Anyone interested in learning from these projects are encouraged to apply. All applicants must have a minimum GPA of 3.0, be able to commit to at least two semesters, and work at least 10 - 12 hours per week.

For those who are interested, please apply by emailing Shuang Song (shuangs3@illinois.edu) your resume, official or unofficial transcript, together with a short paragraph explaining how your past course or research experiences could help you succeed in our project.