Theoretical Foundations

Researchers develop AI algorithm to analyze chest X-rays for COVID-19
Ju Sun is on a team that developed and validated an artificial intelligence algorithm that can evaluate chest X-rays to diagnose possible cases of COVID-19.

Fighting COVID-19 with deep graphs
The goal of the knowledge graph by Professor George Karypis is to narrow the list of drugs that could treat COVID-19.
Research in theoretical foundations formally defines both the types of problems that can be solved using a computer and the quality of their solutions. Computers are limited by space and time. The optimal solution to a computational problem often lies outside these limits, thus an approximate solution must be computed. Methods developed in this area define the plausibility of an optimal solution, the quality of the approximate solution, and the resources necessary to find each, thus leading the way to better utilization of a computer's resources or those of multiple computers in parallel. Specific research in this area encompasses a broad range of foundational topics in computer science including computational learning theory, complexity theory, algorithm and data structure design, parallel algorithms, geometric computing, cryptography, computational logic, programming languages theory, and matrix computations. Several group members are also engaged actively in leveraging their research into various application areas.
Faculty










Labs and selected projects
- Graph Partitioning George Karypis
- ITSOL: Iterative Solvers Package Yousef Saad
- Numerical Algorithms for Very Large, Sparse Dynamical Systems Daniel Boley and Yousef Saad
- pARMS: parallel Algebraic Recursive Multilevel Solvers Yousef Saad
- Research on Layered Manufacturing Ravi Janardan
- UMN Machine Learning Seminar Series
Related centers and programs
Latest research projects, publications, and talks

NCVX: A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning [preprint]
Posted November 27, 2021
Buyun Liang (M.S. student), Ju Sun (assistant professor)

Nonlinear Multi-Objective Flux Balance Analysis of the Warburg Effect [preprint]
Posted November 23, 2021
Yi Zhang, Daniel Boley (professor)

CTKG: A Knowledge Graph for Clinical Trials [preprint]
Posted November 9, 2021
Ziqi Chen, Bo Peng, Vassilis N. Ioannidis, Mufei Li, George Karypis (professor), Xia Ning (Ph.D. 2012)

Evaluating Scholarly Impact: Towards Content-Aware Bibliometrics [conference paper]
Posted November 7, 2021
Saurav Manchanda (Ph.D. student), George Karypis (professor)
Conference on Empirical Methods in Natural Language Processing (EMNLP)

Self-Validation: Early Stopping for Single-Instance Deep Generative Priors [preprint]
Posted October 23, 2021
Taihui Li (Ph.D. student), Zhong Zhuang, Hengyue Liang, Le Peng (Ph.D. student), Hengkang Wang (Ph.D. student), Ju Sun (assistant professor)

Meta-learning via Language Model In-context Tuning [preprint]
Posted October 15, 2021
Yanda Chen, Ruiqi Zhong, Sheng Zha, George Karypis (professor), He He

Kernelized Multitask Learning Method for Personalized Signaling Adverse Drug Reactions [journal]
Posted September 1, 2021
Fan Yang, Fuzhong Xue, Yanchun Zhang, George Karypis (professor)
IEEE Transactions on Knowledge and Data Engineering

Breaking Symmetries in Data-Driven Phase Retrieval [conference paper]
Posted July 19, 2021
Raunak Manekar (Ph.D. student), Kshitij Tayal (Ph.D. student), Zhong Zhuang, Chieh-Hsin Lai, Vipin Kumar (professor), Ju Sun (assistant professor)
Computational Optical Sensing and Imaging

Advancing Probabilistic Models for Approximate and Exact Inference [thesis]
Posted July 1, 2021
Robert Giaquinto (Ph.D. 2021)

Potential and limitations of radiomics in neuro-oncology [journal]
Posted June 11, 2021
Birra Taha, Daniel Boley (professor), Ju Sun (assistant professor), Clark Chen
Journal of Clinical Neuroscience
More About Research areas
- Architectures, Compiler Optimization, and Embedded Systems
- Bioinformatics and Computational Biology
- Data Mining, Databases, and Geographical Information Systems
- Graphics and Immersive Computing
- High Performance Computing
- Human Computer Interaction (HCI)
- Networks, Distributed Systems, and Security
- Robotics and Artificial Intelligence
- Software Engineering and Programming Languages