Spring 2024 CSCI special topics courses

CSCI 5980/8980 

Machine Learning for Healthcare: Concepts and Applications

Meeting Time: 1:00PM - 2:15PM MW
Instructor: Yogatheesan Varatharajah
Course Description: Machine Learning is transforming healthcare. This course will introduce students to a range of healthcare problems that can be tackled using machine learning, different health data modalities, relevant machine learning paradigms, and the unique challenges presented by healthcare applications. Applications we will cover include risk stratification, disease progression modeling, precision medicine, diagnosis, prognosis, subtype discovery, and improving clinical workflows. We will also cover research topics such as explainability, causality, trust, robustness, and fairness.

Registration Prerequisites: CSCI 5521 or equivalent.

CSCI 5980/8980 

Software Foundations

Meeting Time: 04:00 PM‑05:15 PM MW
Instructor: Gopalan Nadathur
Course Description: Mathematical techniques for specifying and reasoning about properties of software and tools for applying these techniques in practical ways will be studied. Towards this end, five interrelated conceptual threads will be exposed:

  • The use of logic for making and justifying precise claims about programs
  • The use of proof assistants for constructing rigorous arguments that verify such claims
  • The use of functional programming as a bridge between programming and logic
  • The use of types as a means for stating deep properties of programs and type checking for ensuring such properties hold.

The focus will be on practical aspects: the course will be oriented around a hands-on use of a proof assistant, Coq, to construct actual programs and to state and prove properties about them.

Registration Prerequisites: CSci 5106 and CSci 4011 strongly encouraged, adequate mathematical maturity essential.

CSCI 5980/8980 

Programming Language Theory

Meeting Time: 04:00 PM‑05:15 PM TTh
Instructor: Favonia
Course Description: This course will teach students a rigorous way to present and analyze programming languages. We will cover: 

  • Operational semantics, a uniform framework for describing a wide range of programming features (such as recursion, references, and polymorphism). 
  • Logical relations, a powerful technique for establishing the compositionality of the semantics and highly non-trivial results about programming languages. 
  • Other theoretical frameworks and tools for analyzing programming languages. 

The instructor intends to work closely with each student to collect feedback on the course structure and learning materials.

Registration Prerequisites: CSCI 4011 and CSCI 5106.

CSCI 8980

Visualization in Human-AI Interactions: Interpretability and Beyond

Meeting Time: 4:00 PM-5:15 PM MW
Instructor: Qianwen Wang
Course Description: The question this course seeks to answer is: how can we build AI systems that human will use and interact with in real-world scenarios? This is a seminar style course consisting of lectures, paper presentation, and interactive discussion of the selected papers. Students will also work on a group project where they propose a research idea, survey related studies, and present initial results.

This course will discuss machine learning algorithms and Visualization techniques for facilitating human-AI interactions, especially the integration of these elements into AI systems and the methodology for their evaluation. Readings for the course cover papers from the top venues of AI, Visualization, and HCI, topics including AI explainability, reliability, and Human-AI collaboration.

This course is designed for PhD students, Masters students, and advanced undergraduates who want to dig into research. 

Registration Prerequisites: Please fill out this Google form to apply for a permission number.

Students are expected to have a solid foundation in either machine learning, data visualization, or HCI. Having expertise in all would be perfect! However, a robust interest and eagerness to delve into these subjects can be equally valuable, even though it means you need to learn basic concepts in visualization and machine learning independently.

Although the class is primarily intended for PhD students, motivated juniors/seniors and MS 
Students who are interested in this topic are welcome to apply, ensuring they detail their qualifications for the course.

CSCI 8980

Current Research in Virtual and Augmented Reality

Meeting Time: 02:30 PM‑03:45 PM MW
Instructor: Victoria Interrante
Course Description: In this course we will read and discuss key recent and historical research papers in the field of virtual and augmented reality.  Students will identify a topic of particular personal interest and will either conduct a formal literature review on that topic or implement a project that contributes new knowledge to the current understanding on that topic.

Registration Prerequisites: CSCI 5619 or graduate student status.