Doctoral Student Research

Machine learning is the sub-field of AI concerned with learning models from data. Once learned, these models can be use to label future data, make predictions about the future, aid in decision making, or explain the past. At Rice, we cover multiple sub-fields of machine learning, including deep learning.

Computational biology and bioinformatics research in the Department of Computer Science spans biological systems from individual genes, proteins, and cells, to networks of interacting molecules, to species and microbial communities. The research projects include protein structure prediction, protein binding and interaction networks, comparative genomics, microbial forensics, and phylogenomics. Research projects are conducted on a wide array of biological systems and species, including, but not limited to, cancer, neurodegenerative diseases (Alzheimer’s, Parkinson’s, etc.), microbiomes, and eukaryotic species. 

Research into programming languages, HPC & formal methods includes new language abstractions for principled programming, compiler construction and optimization, software technology for parallel computing, compilers and architectures for low-power and inexact computing, formal reasoning about program correctness, and computer-assisted programming.

The demands on modern computing systems are increasingly complex, from small embedded systems to phones to laptops to servers in the datacenter. Research into the design and implementation of efficient hardware and software systems will enable next generation systems to support an expanding array of services and applications.

In the field of Robotics and Artificial Intelligence (AI), doctoral student researchers develop intelligent robotic agents to solve problems in manufacturing, clinical healthcare, transportation, search and rescue, and most importantly, agents that will improve the quality of life by assisting in daily activities such as wellness needs and education.

Quantum computing has emerged as an alternative computational model. Realizing the practical acceleration using a Noisy Intermediate-Scale Quantum computer is one of the most important problems of our century. While prototypes are being built now, moving computations to a fully-functional fault-tolerant quantum computer still faces many technical hurdles.

Comp 600 is a weekly seminar for graduate students to practice presenting their research and communicating the impact of their work clearly. The program also exposes doctoral students to the breadth of the department's research. All CS PhD students in residence at Rice are expected to enroll each semester and to present every four semesters. Learn more about the ACTIVATE Engineering Program's outcomes.

The following two videos represent doctoral student research presentations.