Overview Of Research Areas

Algorithms / Comp. Geometry / Comp. Topology

Artificial Intelligence / Machine Learning

Cross-Cutting Areas

Computer Architecture / VLSI

Centers and Groups: Utah Arch

Data Management

Centers and Groups: Data Management Research Center

High-Performance Computing

Human-Centered Computing

Networking / Operating Systems / Scalable Systems

Centers and Groups: Flux Research Group

Programming Languages / Software Engineering

Centers and Groups: PLUTah (Programming Languages at Utah), CTOP (Compilers To Optimize Performance), Flux Research Group

Robotics

Centers and Groups: Utah Robotics Center

Scientific Computing

Centers and Groups: Scientific Computing and Imaging Institute

Security / Privacy

Centers and Groups: Software Security Group

Visual Computing

Centers and Groups: Scientific Computing and Imaging Institute, Graphics Lab


Recent News

Research Areas

Recent Publications

  •  Measure-Theoretic Reeb Graphs and Reeb Spaces. Qingsong Wang, Guanquan Ma, Raghavendra Sridharamurthy, Bei Wang. International Symposium on Computational Geometry (SOCG), 2024.
  • Gallatin: A General-Purpose GPU Memory Manager Hunter McCoy, Prashant Pandey PPOPP 2024
  • Overlapping and Robust Edge-Colored Clustering in Hypergraphs. A. Crane, B. Lavallee, B. D. Sullivan, N. Veldt WSDM 2024
  • Algorithms for Covering Barrier Points by Mobile Sensors with Line Constraint. Princy Jain and Haitao Wang International Journal of Computational Geometry and Applications (IJCGA), 2024.
  • Tight Bounds for Volumetric Spanners and Applications. Sepideh Mahabadi, Ali Vakilian, Aditya Bhaskara Advances in Neural Information Processing Systems NeurIPS 2023
  • Interactive Visualization and Portable Image Blending of Massive Aerial Image Mosaics. Steve Petruzza, Brian Summa, Amy Gooch, Christine M Laney, Tristan Goulden, John Schreiner, Steven Callahan, Valerio Pascucci 2023 IEEE International Conference on Big Data
  • New Tools for Smoothed Analysis: Least Singular Value Bounds for Random Matrices with Dependent Entries. A. Bhaskara, E. Evert, V. Srinivas, A. Vijayaraghavan. ACM Symposium on Theory of Computing (STOC) 2024
  • Hypergraph Co-Optimal Transport: Metric and Categorical Properties. Samir Chowdhury, Tom Needham, Ethan Semrad, Bei Wang, Youjia Zhou. Journal of Applied and Computational Topology, 2023.
  •  Sketching Multidimensional Time Series for Fast Discord Mining. Chin-Chia Michael Yeh, Yan Zheng, Menghai Pan, Huiyuan Chen, Zhongfang Zhuang, Junpeng Wang, Liang Wang, Wei Zhang, Jeff M. Phillips, and Eamonn Keogh. IEEE International Conference on Big Data. December 2023.

Recent News

Selected Publications

2024
  • Promptly Predicting Structures: The Return of Inference. Maitrey Mehta, Valentina Pyatkin, Vivek Srikumar. ArXiv Preprint:2401.06877
  • Autonomous Assessment of Demonstration Sufficiency via Bayesian Inverse Reinforcement Learning. Tu Trinh, Haoyu Chen, Daniel S. Brown. HRI 2024
2023
  • Whispers of Doubt Amidst Echoes of Triumph in NLP Robustness. Ashim Gupta, Rishanth Rajendhran, Nathan Stringham, Vivek Srikumar, Ana Marasović. ArXiv Preprint:2311.09694
  • Quantifying Assistive Robustness Via the Natural-Adversarial Frontier Jerry Zhi-Yang He, Zackory Erickson, Daniel S. Brown, Anca D. Dragan. CoRL 2023
  • How Much Consistency Is Your Accuracy Worth?. Jacob K. Johnson and Ana Marasović. BlackboxNLP Workshop @ EMNLP 2023
  • On Evaluating Explanation Utility for Human-AI Decision-Making in NLP Fateme Hashemi Chaleshtori, Atreya Ghosal, and Ana Marasović. XAI in Action: Past, Present, and Future Applications @ NeurIPS 2023
  • SpotEM: Efficient Video Search for Episodic Memory. Santhosh K. Ramakrishnan, Ziad Al-Halah, Kristen Grauman. ICML 2023
  • Do Androids Laugh at Electric Sheep? Humor ''Understanding'' Benchmarks from The New Yorker Caption Contest Jack Hessel, Ana Marasovic, Jena D. Hwang, Lillian Lee, Jeff Da, Rowan Zellers, Robert Mankoff, and Yejin Choi. Best Paper Award at ACL 2023
  • Exploring Behavior Discovery Methods for Heterogeneous Swarms of Limited-Capability Robots. Connor Mattson, Jeremy C. Clark, Daniel S. Brown. MRS 2023
  • NaQ: Leveraging Narrations as Queries to Supervise Episodic Memory Santhosh K. Ramakrishnan, Ziad Al-Halah, Kristen Grauman. CVPR 2023
  • Don't Retrain, Just Rewrite: Countering Adversarial Perturbations by Rewriting Text. Ashim Gupta, Carter Blum, Temma Choji, Yingjie Fei, Shalin Shah, Alakananda Vempala, and Vivek Srikumar. ACL 2023

Research Groups

Natural Language Processing

Website:  UtahNLP

PhD Students

Oliver Bentham, Michael Clemens, Joe Davison, Atreya Ghosal, Ashim Gupta, Fateme Hashemi Chaleshtori, Jacob Johnson, Mattia Medina Grespan, Maitrey Mehta, Nate Stringham, Zhichao Xu, Yuan Zhuang

Recent Graduates

Vivek Gupta (Postdoc at UPenn), Tianyu Jiang (Asst. Prof. at University of Cincinnati), Yichu Zhou (Yahoo Research), Tao Li (Google Research)


Research Projects

Recent News

  • Accepted paper: Security & Privacy 2024
  • Accepted paper: PLDI 2023
  • Accepted paper: DSN 2023
  • Accepted paper: IEEE Micro 2023

Recent Graduates

  • Surya Narayanan, May 2022, First employment: Imagination Technologies
  • Sumanth Gudaparthi, April 2022, First employment: AMD Research

Summer Internships


Research Projects

  • Democratizing data-driven systems: This project focuses on three key aspects of data system democratization: enhancing usability of data systems for non-experts and experts, providing explanation frameworks to enable understanding of system behavior, and achieving trust and fairness in machine learning.
  • Data structures for scalable computing: This project focuses on advancing the theory and practice of compact, dynamic, and scalable data structures to tackle the challenges of modern data analyses pipelines. We work on filters, hash tables, trees, succinct, and write-optimized data structures.
  • Large-scale indexing raw genomics data: This project focuses on building scalable data processing pipelines for quickly indexing and searching through tera-bytes of raw genomic, transcriptomic, and metagenomics data.
  • Efficient parallel graph processing: This project focuses on building highly parallel data structures and algorithms for efficiently processing static, streaming, and dynamic graphs. This project further explores using hardware accelerators such as GPUs for massively parallel processing of dynamic graphs.
  • Persistent Data Summaries: This project builds summaries for massive data arriving over time, which are small space, efficient to build and query, and amenable to data analysis. Moreover, they can be queried with respect to a time window for retrospective analysis.
  • Data Sketching:: We design and implement sketch data structures which are compressed representations of data with guaranteed trade-offs between the space and the accuracy of queries. Our group has designs sketches for quantiles, multi-dimensional data, frequent items, shape-fitting, trajectories data, and many more.
  • Spatial Exposome Data: CEDaR is be an open exposomic data resource that can be used by researchers across disciplines to increase understanding of the environment and health. Sources of environmental exposure data are sparse, inconsistent, and rarely linked to individuals, making research complicated and difficult. Through CEDaR, we provide a single platform containing cleaned and standardized environmental exposure measures that can be used independently or to create holistic measures of the exposome.
  • Data Systems on Modern Hardware: This project exploits modern compute hardware such as GPUs, FPGAs and storage hardware such as PMEMs, HBMs for accelerating data systems. Our group designs new algorithmic techniques to model the performance of new hardware and then analyzes data systems in the light of the new algorithmic models to accelerate them.
  • Extreme-Scale Data Management: DataSpaces is a programming system targeted at current large-scale systems and designed to support dynamic interaction and coordination patterns between scientific applications. DataSpaces essentially provides a semantically specialized shared-space abstraction using a set of staging nodes. This abstraction derives from the tuple-space model and can be associatively accessed by the interacting applications of a simulation workflow.

Recent News

Publications

2024

  • WWW Tao Yang, Cuize Han, Chen Luo, Parth Gupta, Jeff M. Phillips, and Qingyao Ai: Mitigating Exploitation Bias in Learning to Rank with an Uncertainty-aware Empirical Bayes Approach.
  • SIGMOD Prashant Pandey, Martin Farach-Colton, Niv Dayan, Huanchen Zhang: Beyond Bloom: A Tutorial on Future Feature-Rich Filters.
  • FAST Yi Xu*, Henry Zhu*, Prashant Pandey, Alex Conway, Rob Johnson, Ramnatthan Alagappan, Aishwarya Ganesani: IONIA: High-Performance Replication for Modern Disk-based KV Stores.
  • PPOPP Hunter McCoy, Prashant Pandey: Gallatin: A General-Purpose GPU Memory Manager.
  • SIGCSE Anjali Singh, Anna Fariha, Christopher Brooks, Gustavo Soares, Austin Henley, Ashish Tiwari, Chethan M, Heeryung Choi, Sumit Gulwani: Investigating Student Mistakes in Introductory Data Science Programming.
  • EMNLP Soohyeong Kim, Whanhee Cho, Minji Kim, Yong Suk Choi: Bidirectional Masked Self-attention and N-gram Span Attention for Constituency Parsing.

 2023

  • IEEE BigData Chin-Chia Michael Yeh, Yan Zheng, Menghai Pan, Huiyuan Chen, Zhongfang Zhuang, Junpeng Wang, Liang Wang, Wei Zhang, Jeff M. Phillips, and Eamonn Keogh: Sketching Multidimensional Time Series for Fast Discord Mining.
  • SIGMOD Prashant Pandey, Michael A. Bender, Alex Conway, Martin Farach-Colton, William Kuszmaul, Guido Tagliavini, Rob Johnson: IcebergHT: High Performance Hash Tables Through Stability and Low Associativity.
  • VLDB Helen Xu, Amanda Li, Brian Wheatman, Manoj Marneni, Prashant Pandey: BP-tree: Overcoming the Point-Range Operation Tradeoff for In-Memory B-trees.
  • SIGMOD Bhavya Chopra, Anna Fariha, Sumit Gulwani, Austin Z. Henley, Daniel Perelman, Mohammad Raza, Sherry Shi, Danny Simmons, Ashish Tiwari: DemoCoWrangler: Recommender System for Data-Wrangling Scripts.
  • PPoPP Hunter McCoy, Steven Hofmeyr, Katherine Yelick, Prashant Pandey: High-Performance Filters for GPUs.
  • Knowledge and Information Systems Hasan Pourmahmood Aghababa, Jeff M. Phillips: An experimental study on classifying spatial trajectories.
  • IPDPS Süreyya Emre Kurt, Jinghua Yan, Aravind Sukumaran-Rajam, Prashant Pandey, P. Sadayappan: Communication Optimization for Distributed Execution of Graph Neural Networks.
  • APOCS Madhav Narayan Bhat, Paul Cesaretti, Mayank Goswami, Prashant Pandey: Distance and Time Sensitive Filters for Similarity Search in Trajectory Datasets.
  • ACDA Hunter McCoy, Steven Hofmeyr, Katherine Yelick, Prashant Pandey: Singleton Sieving: Overcoming the Memory/Speed Trade-Off in Exascale k-mer Analysis.
  • SIGCSE Rowan Hart, Brian Hays, Connor McMillin, El Kindi Rezig, Gustavo Rodriguez-Rivera, Jeffrey A. Turkstra: Eastwood-Tidy: C Linting for Automated Code Style Assessment in Programming Courses.

Research Areas

Recent News

  • Spring 24:  Paper Accepted at IEEE DySPAN 2024.
  • Fall 23: Sirus Shahini defended his PhD.
  • Fall 23: Paper Accepted at NSDI 2024!
  • Summer 23: Hao (Harry) Jiang defended his PhD.

Recent Publications

  • Where The Wild Things Are: Brute-Force SSH Attacks In The Wild And How To Stop Them. S. Kumar Singh, S. Gautam, C. Cartier, S. Patil, and R. Ricci in NSDI2024.
  • POWDER-RDZ: Prototyping a Radio Dynamic Zone using the POWDER platform. David Johnson, Dustin Maas, Serhat Tadik, Alex Orange, Leigh Stoller, Kirk Webb, M Basit Iqbal Awan, Jacob Bills, Miguel Gomez, Aarushi Sarbhai, Greg Durgin, Sneha Kasera, Neal Patwari, David Schurig, Jacobus Van der Merwe in IEEE DySPAN 2024.
  • An NSF REU Site Based on Trust and Reproducibility of Intelligent Computation: Experience Report. Mary Hall, Ganesh Gopalakrishnan, Eric Eide, Johanna Cohoon, Jeff M. Phillips, Mu Zhang, Shireen Y. Elhabian, Aditya Bhaskara, Harvey Dam, Artem Yadrov, Tushar Kataria, Amir Mohammad Tavakkoli, Sameeran Joshi, and Mokshagna Sai Teja Karanam in SC-W 2023.
  • OZTrust: An O-RAN Zero-Trust Security System. Hao (Harry) Jiang, Hyunseok Chang, Sarit Mukherjee, and Jacobus (Kobus) Van der Merwe in IEEE NFV-SDN 2023.
  • FlexRDZ: Autonomous Mobility Management for Radio Dynamic Zones. Aashish Gottipati and Jacobus (Kobus) Van der Merwe in FNWF 2023.
  • Generating Conforming Programs with Xsmith. William Gallard Hatch, Pierce Darragh, Sorawee Porncharoenwase, Guy Watson, and Eric Eide in GPCE 2023.
  • dNextG: A Zero-Trust Decentralized Mobile Network User Plane. Ryan West and Jacobus (Kobus) Van der Merwe in ACM Q2SWinet 2023.
  • Arvin: Greybox Fuzzing Using Approximate Dynamic CFG Analysis. Sirus Shahini, Mu Zhang, Mathias Payer, and Robert Ricci in AsiaCCS 2023.
  • Avoiding the Ordering Trap in Systems Performance Measurement. Dmitry Duplyakin, Nikhil Ramesh, Carina Imburgia, Hamza Fathallah Al Sheikh, Semil Jain, Prikshit Tekta, Aleksander Maricq, Gary Wong, and Robert Ricci in ATC 2023.
  • Adjacent Channel WiFi 5 Interference on DSRC Communication at 5.9GHz. Jacob Bills, Alex Orange, and Jacobus (Kobus) Van der Merwe in VTC2023-Spring 2023.
  • RESCue: A State-Disaggregated NFV System with Resilience, Elasticity, and State Consistency. Hao (Harry) Jiang, Hyunseok Chang, Sarit Mukherjee, and Jacobus (Kobus) Van der Merwe in NETSOFT 2023.

Research Projects

  • Designing a framework for efficient, scalable, and performance-portable tensor applications (Saday Sadayappan)
  • Developing effective performance models for compiler optimization by leveraging ML (Saday Sadayappan)
  • Constructing a synthesis-based superoptimizer for vector intrinsics in LLVM intermediate representation (John Regehr)
  • Better generative compiler fuzzing for loop optimizations in C++ and data-parallel languages (John Regehr)
  • Designing exploratory compiler infrastructure for automating high-performance code generation (Mary Hall)
  • Fully integrating data layout and data movement into compilers (Mary Hall)
  • Devising a programmable approach to neural network compression with emphasis on correctness (Ganesh)
  • Improving the performance and accuracy of numerical code on new platforms like GPUs, vector cores, and TPUs (Pavel Panchekha)
  • Scaling web browsers to large web pages (Pavel Panchekha)
  • Automatic synthesis of heterogeneous cache coherence protocols adhering to precise consistency models (Vijay Nagarajan)
  • Enhancing the engineering of 5G networks through domain-specific languages (Eric Eide)
  • Advancing the usability and effectiveness of compiler fuzzing through reusable tools for test-case generation. (Eric Eide)

Recent News

  • January 2024: Dr. Vsevolod Livinskii, advised by Prof. John Regehr, defended his Ph.D. thesis and joined NVIDIA.
  • January 2024: Dr. Ian Briggs, advised by Prof. Pavel Panchekha, defended his Ph.D. and joined AWS. 
  • January 2024: The MegaLibm project, led by Ian Briggs with help from Yash Lad and Prof. Pavel Panchekha, won a Distinguished Paper Award at POPL 2024.
  • October 2023: Prof. Eide presented the first paper about Xsmith (a library for compiler test-case generation) at the GPCE ‘23 conference.
  • August 2023: Profs. Vijay Nagarajan and Ben Greenman join the Kahlert School of Computing.
  • May 2023: Guy Watson defended his MS thesis entitled “Random Testing of WebAssembly Implementations Using Semantically Valid Programs.”
  • June 2023: Prof. Eide received the ACM SIGPLAN PLDI 2023 Distinguished Reviewer Award.
  • September 2022: Dr. Tharindu Rusira, advised by Prof. Mary Hall, defended his Ph.D. thesis and joined Samsung Semiconductor, Inc.
  • August 2022: Dr. Sureyya Emre Kurt, advised by Prof. Saday Sadayappan defended his Ph.D. thesis and joined Xantium.
  • May 2022: Dr. Tuowen Zhao, advised by Prof. Mary Hall, defended his Ph.D. thesis and joined Sambanova Systems.

Research Groups


Recent News

Research Areas

    Daniel S. Brown
  • Human Robot Interaction
  • Robot Learning
  • Swarm Robotics
  • AI Safety and Robustness
    Alan Kuntz
  • Autonomous Medical Robotics Systems and Learning:

Recent Publications

  • Exploring Behavior Discovery Methods for Heterogeneous Swarms of Limited-Capability Robots.Connor Mattson, Jeremy C. Clark, and Daniel S. Brown, 2023 International Symposium on Multi-Robot and Multi-Agent Systems (MRS) 
  • Quantifying Assistive Robustness Via the Natural-Adversarial Frontier. Jerry Zhi-Yang He, Daniel S Brown, Zackory Erickson, Anca Dragan. Conference on Robot Learning, pp. 1865-1886. PMLR, 2023.
  • Autonomous Medical Needle Steering In Vivo. Alan Kuntz, Maxwell Emerson, Tayfun Efe Ertop, Inbar Fried, Mengyu Fu, Janine Hoelscher, Margaret Rox, Jason Akulian, Erin A. Gillaspie, Yueh Z. Lee, Fabien Maldonado, Robert J. Webster III, and Ron Alterovitz. Science Robotics 2023
  • Safer Motion Planning of Steerable Needles via a Shaft-to-Tissue Force Model. Michael Bentley, Caleb Rucker, Chakravarthy Reddy, Oren Salzman, and Alan Kuntz. Journal of Medical Robotics Research 2023
  • Asymptotically Optimal Inspection Planning via Efficient Near-Optimal Search on Sampled Roadmaps. Mengyu Fu, Alan Kuntz, Oren Salzman, and Ron Alterovitz. The International Journal of Robotics Research (IJRR) 2023

Recent Publications

2024
  • Joshua Dawson, Eden Fisher, and Jason Wiese. 2024. Hospital Employee Experiences Caring for Patients in Smart Patient Rooms. In Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI ’24), May 11–16, 2024, Honolulu, HI, USA. ACM, New York, NY, USA, 16 pages. https://doi.org/10.1145/3613904.3642201
  • Maxim Lisnic, Alexander Lex, Marina Kogan. ‘Yeah, this graph doesn't show that’: Analysis of Online Engagement with Misleading Data Visualizations. In Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI ’24), May 11–16, 2024, Honolulu, HI, USA. ACM, New York, NY, USA, 14 pages. https://doi.org/10.1145/3613904.3642448
  • Sadia O. Khan, Tania Ghafourian, and Sameer Patil. 2024. Targets of Weaponized Islamophobia: The Impact of Misinformation on the Online Practices of Muslims in the United States. Proc. ACM Hum.-Comput. Interact. 8, CSCW1, Article 126 (April 2024), 38 pages. https://doi.org/10.1145/3637403
  • Noelle Brown, Benjamin Xie, Ella Sarder, Casey Fiesler, and Eliane S. Wiese. 2024. Teaching Ethics in Computing: A Systematic Literature Review of ACM Computer Science Education Publications. ACM Trans. Comput. Educ. 24, 1, Article 6 (March 2024), 36 pages. https://doi.org/10.1145/3634685
2023
  • Joshua Dawson, K. Jens Phanich, and Jason Wiese. 2024. Reenvisioning Patient Education with Smart Hospital Patient Rooms. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 7, 4, Article 155 (December 2023), 23 pages. https://doi.org/10.1145/3631419
  • Joshua Dawson, Thomas Kauffman, and Jason Wiese. 2023. It Made Me Feel So Much More at Home Here: Patient Perspectives on Smart Home Technology Deployed at Scale in a Rehabilitation Hospital. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI '23). Association for Computing Machinery, New York, NY, USA, Article 344, 1–15. https://doi.org/10.1145/3544548.3580757
  • Johanna Cohoon, Kazi Sinthia Kabir, Tamanna Motahar, and Jason Wiese. 2023. Cultivating Altruism Around Computing Resources: Anticipation Work in a Scholarly Community. Proc. ACM Hum.-Comput. Interact. 7, CSCW2, Article 336 (October 2023), 22 pages. https://doi.org/10.1145/3610185
  • Kazi Sinthia Kabir and Jason Wiese. 2023. A Meta-Synthesis of the Barriers and Facilitators for Personal Informatics Systems. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 7, 3, Article 103 (September 2023), 35 pages. https://doi.org/10.1145/3610893
  • Jason Wiese, John R. Lund, and Kazi Sinthia Kabir. 2023. Adding Domain-Specific Features to a Text-Editor to Support Diverse, Real-World Approaches to Time Management Planning. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI '23). Association for Computing Machinery, New York, NY, USA, Article 856, 1–13. https://doi.org/10.1145/3544548.3581536
  • Tamanna Motahar, Noelle Brown, Eliane Stampfer Wiese, and Jason Wiese. 2023. Building “Design Empathy” for People with Disabilities: an Unsolved Challenge in HCI Education. In Proceedings of the 5th Annual Symposium on HCI Education (EduCHI '23). Association for Computing Machinery, New York, NY, USA, 68–71. https://doi.org/10.1145/3587399.3587409
  • Noelle Brown, Koriann South, Suresh Venkatasubramanian, and Eliane S. Wiese. 2023. Designing Ethically-Integrated Assignments: It’s Harder Than it Looks. In Proceedings of the 2023 ACM Conference on International Computing Education Research - Volume 1 (ICER '23), Vol. 1. Association for Computing Machinery, New York, NY, USA, 177–190. https://doi.org/10.1145/3568813.3600126
  • Noelle Brown, Nidhi Patel, Xavier Davis, and Eliane S. Wiese. 2023. Students’ Self-Evaluations of Contextual Inquiry Techniques. In Proceedings of the 5th Annual Symposium on HCI Education (EduCHI '23). Association for Computing Machinery, New York, NY, USA, 96–100. https://doi.org/10.1145/3587399.3587411
  • Derya Akbaba, Devin Lange, Michael Correll, Alexander Lex, and Miriah Meyer. 2023. Troubling Collaboration: Matters of Care for Visualization Design Study. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI '23). Association for Computing Machinery, New York, NY, USA, Article 812, 1–15. https://doi.org/10.1145/3544548.3581168
  • Maxim Lisnic, Cole Polychronis, Alexander Lex, and Marina Kogan. 2023. Misleading Beyond Visual Tricks: How People Actually Lie with Charts. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI '23). Association for Computing Machinery, New York, NY, USA, Article 817, 1–21. https://doi.org/10.1145/3544548.3580910
  • Nicole M Eklund, Jessey Ouillon, Vineet Pandey, Christopher D Stephen, Jeremy D Schmahmann, Jeremy Edgerton, Krzysztof Z Gajos, Anoopum S Gupta, Real-life ankle submovements and computer mouse use reflect patient-reported function in adult ataxias, Brain Communications, Volume 5, Issue 2, 2023, fcad064, https://doi.org/10.1093/braincomms/fcad064
  • Vineet Pandey, Nergis C. Khan, Anoopum S. Gupta, and Krzysztof Z. Gajos. 2023. Accuracy and Reliability of At-Home Quantification of Motor Impairments Using a Computer-Based Pointing Task with Children with Ataxia-Telangiectasia. ACM Trans. Access. Comput. 16, 1, Article 10 (March 2023), 25 pages. https://doi.org/10.1145/3581790

Research Projects

  • National Data Platform (NDP)
  • DataSpaces
  • R-Pulsar
  • Compilers for sparse tensor contractions
  • Sparse matrix/tensor algorithms on GPUs
  • Code generation and optimization for GPUs
  • Distributed training for NLP
  • Autotuning and fusion for AI compilers
  • Date layout transformations for sparse contractions.

Recent News

Recent Papers


Research Areas

Research Groups

PhD Students

Selected Publications

2024

  • M. Berzins. “COMPUTATIONAL ERROR ESTIMATION FOR THE MATERIAL POINT METHOD IN 1D AND 2D,” In VIII International Conference on Particle-Based Methods, PARTICLES 2023, 2024.
  • William Black, David Neilsen, Hari Sundar, Eric Hirschmann, Yosef Zlochower, Milinda Fernando, “Refining Refinement in Binary Black Hole Simulations”, Bulletin of the American Physical Society
  • Shikai Fang, Madison Cooley, Da Long, Shibo Li, Robert M. Kirby, Shandian Zhe, “Solving High Frequency and Multi-Scale PDEs with Gaussian Processes”, The 12th International Conference on Learning Representations (ICRL 2024), Vienna, Austria, May 7-11, 2024.
  • Shibo Li, Xin Yu, Wei W. Xing, Robert M. Kirby, Akil Narayan and Shandian Zhe, “Multi-Resolution Active Learning of Fourier Neural Operators”, The 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), Valencia, Space, May 2-4, 2024.
  • Da Long, Wei W. Xing, Aditi S. Krishnapriyan, Robert M. Kirby, Shandian Zhe and Michael W. Mahoney, “Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels”, The 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), Valencia, Space, May 2-4, 2024.

2023

  • Wu, X., Balaprakash, P., Kruse, M., Koo, J., Videau, B., Hovland, P.D., Taylor, V.E., Geltz, B., Jana, S., & Hall, M.W. (2023). ytopt: Autotuning Scientific Applications for Energy Efficiency at Large Scales. ArXiv, abs/2303.16245.
  • T. M. Athawale, C.R. Johnson, S. Sane,, D. Pugmire. “Fiber Uncertainty Visualization for Bivariate Data With Parametric and Nonparametric Noise Models,” In IEEE Transactions on Visualization and Computer Graphics, Vol. 29, No. 1, IEEE, pp. 613-23. 2023.
  • Han D. Tran, Siddharth Saurav, P. Sadayappan, Sandip Mazumder, and Hari Sundar. 2023. Scalable parallelization for the solution of phonon Boltzmann Transport Equation. In Proceedings of the 37th International Conference on Supercomputing (ICS ’23).
  • MGM: A meshfree geometric multilevel method for systems arising from elliptic equations on point cloud surfaces. Grady B Wright, Andrew Jones, Varun Shankar. SIAM Journal on Scientific Computing, 2023.
  • Locally Adaptive and Differentiable Regression. Mingxuan Han, Varun Shankar, Jeff M Phillips, Chenglong Ye. Journal of Machine Learning for Modeling and Computing, 2023.
  • Hongsup Oh, Roman Amici, Geoffrey Bomarito, Shandian Zhe, Robert M. Kirby and Jacob Hochhalter, “Inherently Interpretable Machine Learning Solutions to Differential Equations”, Engineering with Computers, https://doi.org/10.1007/s00366-023-01915-7, 2023.
  • Khemraj Shukla, Vivek Oommen, Ahmad Peyvan, Michael Penwarden, Nicholas Plewacki, Luis Bravo, Anindya Ghoshal, Robert M. Kirby and George Em Karniadakis, “Deep neural operators as accurate surrogates for shape optimization”, Engineering Application of Artificial Intelligence, Volume 129, pages 107615, 2023.
  • Bo Zhang, Philip E. Davis, Nicolas Morales, Zhao Zhang, Keita Teranishi, and Manish Parashar. “Optimizing Data Movement for GPU-Based In-Situ Workflow Using GPUDirect RDMA.” In European Conference on Parallel Processing, pp. 323-338. Cham: Springer Nature Switzerland, 2023.

2022

  • Accelerated Training of Physics-Informed Neural Networks (PINNs) using Meshless Discretizations. Ramansh Sharma, Varun Shankar. Advances in Neural Information Processing Systems, 2022.
  • Bo Zhang, Pradeep Subedi, Philip E. Davis, Francesco Rizzi, Keita Teranishi, and Manish Parashar. “Assembling Portable In-Situ Workflow from Heterogeneous Components using Data Reorganization.” In 2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid), pp. 41-50. IEEE, 2022.

Research Areas

Selected Publications

  • Hyena: Balancing Packing, Reuse, and Rotations for Encrypted Inference. (S&P 2024) Sarabjeet Singh, Shreyas Singh, Sumanth Gudaparthi, Xiong Fan, Rajeev Balasubramonian
  • Foundations of Adaptor Signatures. (EUROCRYPT 2024) Paul Gerhart, Dominique Schroder, Pratik Soni, Sri AravindaKrishnan Thyagarajan
  • Targets of Weaponized Islamophobia: The Impact of Misinformation on the Online Practices of Muslims in the United States. (Proc. ACM Hum.-Comput. Interact. 8, CSCW1, Article 126 (April 2024), 38 pages.) Sadia O. Khan, Tania Ghafourian, and Sameer Patil.
  • VetEOS: Statically Vetting EOSIO Contracts for the “Groundhog Day” Vulnerabilities(NDSS’24) Levi Taiji Li, Ningyu He, Haoyu Wang, Mu Zhang
  • Profile-guided System Optimizations for Accelerated Greybox Fuzzing (CCS 2023) Yunhang Zhang, Chengbin Pang, Stefan Nagy, Xun Chen, Jun Xu.
  • SysPart: Automated Temporal System Call Filtering for Binaries (CCS 2023) Vidya Lakshmi Rajagopalan, Konstantinos Kleftogiorgos, Enes Göktaş, Jun Xu, Georgios Portokalidis
  • Automated Generation of Security-Centric Descriptions for Smart Contract Bytecode (ISSTA'23) Yu Pan, Zhichao Xu, Levi Taiji Li, Yunhe Yang, Mu Zhang
  • No Linux, No Problem: Fast and Correct Windows Binary Fuzzing via Target-embedded Snapshotting (USENIX'23) Leo Stone, Rishi Ranjan, Stefan Nagy, and Matthew Hicks.
  • AEM: Facilitating Cross-Version Exploitability Assessment of Linux Kernel Vulnerabilities (S&P 2023) Zheyue Jiang, Yuan Zhang, Jun Xu, Xinqian Sun, Zhuang Liu, Min Yang
  • Arvin: Greybox Fuzzing Using Approximate Dynamic CFG Analysis (AsiaCCS 2023) Sirus Shahini, Mu Zhang, Mathias Payer, Robert Ricci
  • Distributed-Prover Interactive Proofs (TCC 2023) Sourav Das, Rex Fernando, Ilan Komargodsky, Elaine Shi, Pratik Soni
  • Non-Interactive Anonymous Router with Quasi-Linear Router Computation (TCC 2023) Rex Fernando, Elaine Shi, Pratik Soni, Nikhil Vanjani, Brent Waters

Utah Software Security Group

Our group of faculty and students conducts cutting-edge research to proactively strengthen software defenses, uncover security vulnerabilities at scale, and enhance program analysis toward efficient,effective, and practical cybersecurity.

We routinely publish our work in security and software engineering venues (e.g., IEEE S&P, USENIX Security, ACM CCS, NDSS, ICSE, and ASE). To learn more about our projects, check out our Research page, and feel free to get in touch with our Faculty.


Recent Publications

  • Design Concerns for Integrated Scripting and Interactive Visualization in Notebook Environments, C. Scully-Allison et al.
  • Loon: Using Exemplars to Visualize Large-Scale Microscopy Data, Devin Lange, Eddie Polanco, Robert Judson-Torres, Thomas Zangle, Alexander Lex  IEEE Transactions on Visualization and Computer Graphics
  • A Qualitative Analysis of Common Practices in Annotations: A Taxonomy and Design Space. Rahman, Md Dilshadur, et al.
  • Misleading Beyond Visual Tricks: How People Actually Lie with Charts. Maxim Lisnic, Cole Polychronis, Alexander Lex, and Marina Kogan. 2023.
  • DeepSSM: A blueprint for image-to-shape deep learning models, Riddhish Bhalodia, Shireen Elhabian, Jadie Adams, Wenzheng Tao, Ladislav Kavan, Ross Whitaker
  • Super Fast Strand-Based Hair Rendering with Hair Meshes. Gaurav Bhokare, Eisen Montalvo, Elie Diaz, Mitchell Allen, and Cem Yuksel. 2023.
  • Here’s what you need to know about my data: Exploring Expert Knowledge’s Role in Data Analysis. Lin, Haihan, et al.