Research Areas – Kahlert School of Computing

Research Areas – Kahlert School of Computing
Overview
Algorithms / Comp. Geometry / Comp. Topology
Artificial Intelligence / Machine Learning
Computer Architecture / VLSI
Data Management
Networking / Operating Systems / Scalable Systems
Programming Languages / Software Engineering
Robotics
Human-Centered Computing
High-Performance Computing
Scientific Computing
Security / Privacy
Visual Computing
Overview Of Research Areas
Algorithms / Comp. Geometry / Comp. Topology
Approximation / Online Algorithms:
A. Bhaskara
J. Phillips
Algorithms & Data Structures:
H. Wang
Computational Geometry:
V. Pascucci
B. Wang Phillips
J. Phillips
H. Wang
Computational Topology:
V. Pascucci
B. Wang Phillips
Graph Algorithms:
A. Bhaskara
B. Sullivan
Artificial Intelligence / Machine Learning
Computer Vision:
Z. Al-Halah
K. Marino
Y. Jiang
ML and Data Analysis:
V. Pascucci
B. Wang Phillips
J. Phillips
ML Theory and Modeling:
A. Bhaskara
J. Phillips
S. Zhe
ML Security:
G. Tao
Natural Language Processing:
A. Marasovic
V. Srikumar
K. Marino
Scientific Machine Learning:
S. Zhe
M. Kirby
V. Shankar
Cross-Cutting Areas
ML and Systems:
R. Balasubramonian
G. Gopalakrishnan
P. Sadayappan
M. Zhang
Image Analysis and Computer Vision:
S. Elhabian
Y. Jiang
C. Johnson
S. Joshi
V. Pascucci
T. Tasdizen
R. Whitaker
Computer Architecture / VLSI
Accelerators and VLSI:
E. Brunvand
R. Balasubramonian
Cache Coherence and Memory Consistency:
V. Nagarajan
Correct-by-Construction Hardware Design:
V. Nagarajan
Memory Systems:
R. Balasubramonian
Centers and Groups:
Utah Arch
Data Management
Approximate Databases:
J. Phillips
Data Discovery and Data Quality:
A. Fariha
E.K. Rezig
Data Systems Usability and Debugging:
A. Fariha
E.K. Rezig
Databases for Emerging Hardware:
V. Nagarajan
Storage and Indexing:
J. Phillips
Extreme-Scale Data Management:
M. Parashar
Centers and Groups:
Data Management Research Center
High-Performance Computing
Accelerators and VLSI:
E. Brunvand
R. Balasubramonian
Compiler Optimization:
M. Hall
J. Regehr
P. Sadayappan
Large Scale Data Management:
M. Parashar
Scalable Machine Learning:
R. Balasubramonian
P. Sadayappan
V. Srikumar
High-Performance Scientific Computing:
M. Berzins
M. Hall
M. Kirby
V. Pascucci
R. Basu Roy,
P. Sadayappan
Scalable Systems:
E. Eide
R. Ricci
R. Basu Roy
K. Van der Merwe
Sustainable Systems:
R. Basu Roy
Human-Centered Computing
Computer Science Education:
E. Wiese
Security and Privacy:
S. Patil
Human-Computer Interaction:
Y. Jiang
M. Kogan
A. Lex
A. McNutt
V. Pandey
E. Wiese
J. Wiese
Social Computing:
M. Kogan
V. Pandey
Virtual Reality:
J. Hollerbach
Y. Jiang
Networking / Operating Systems / Scalable Systems
Networking:
E. Eide
S. Kasera
R. Ricci
R. Stutsman
K. Van der Merwe
Operating Systems:
A. Burtsev
R. Basu Roy
R. Stutsman
Scalable Systems:
E. Eide
R. Ricci
K. Van der Merwe
Storage Systems:
R. Stutsman
Federated Data Ecosystem:
M. Parashar
Centers and Groups:
Flux Research Group
Programming Languages / Software Engineering
Compilers and Performance Optimization:
M. Hall
J. Regehr
P. Sadayappan
Verification, Types, and Logic:
B. Greenman
G. Gopalakrishnan
P. Panchekha
J. Regehr
Testing and Fuzzing:
E. Eide
P. Panchekha
J. Regehr
Language Design & Implementation:
M. Flatt
B. Greenman
P. Panchekha
V. Nagarajan
Centers and Groups: PLUTah (Programming Languages at Utah),
CTOP (Compilers To Optimize Performance)
Flux Research Group
Robotics
Autonomous Systems and Learning:
D. Brown
T. Henderson
T. Hermans
A. Kuntz
, Weiyu Liu
Human/Medical Robotics:
D. Brown
J. Hollerbach
A. Kuntz
Centers and Groups:
Utah Robotics Center
Scientific Computing
Computational Inverse Problems:
C. Johnson
M. Kirby
Geometry and Mesh Generation:
V. Pascucci
V. Shankar
R. Whitaker
High-Performance Computing:
M. Berzins
M. Hall
C. Johnson
M. Kirby
V. Pascucci
P. Sadayappan
V. Shankar
M. Parashar
Modeling Methods and Frameworks:
M. Berzins
M. Kirby
V. Shankar
Centers and Groups:
Scientific Computing and Imaging Institute
Security / Privacy
Cryptography:
Pratik Soni
ML Security:
G. Tao
Mobile Security:
M. Zhang
Security/Safety of IoT and Cyber-Physical Systems: L. Garcia
Sociotechnical Aspects:
S. Patil
Systems Security:
R. Balasubramonian
E. Eide
S. Kasera
S. Nagy
R. Ricci
M. Zhang
J. Xu
Centers and Groups:
Software Security Group
Visual Computing
Computer Graphics:
E. Brunvand
, Y. Yang,
C. Yuksel
J. Lin
Computer Vision:
Z. Al-Halah
K. Marino
Image Analysis:
S. Elhabian
C. Johnson
S. Joshi
V. Pascucci
T. Tasdizen
R. Whitaker
Visualization:
C. Johnson
K. Isaacs
M. Kirby
A. Lex
A. McNutt
V. Pascucci
B. Wang Phillips
P. Rosen
Centers and Groups:
Scientific Computing and Imaging Institute
Graphics Lab
Algorithms / Comp. Geometry / Comp. Topology
Bhaskara Aditya
Pascucci Valerio
Phillips Jeff
Sullivan Blair
Wang Haitao
Wang Phillips Bei
Recent News
Jeff Phillips
co-PC Chair for
SoCG 2024
Blair Sullivan
is co-chair for
SIAM DM2024
Prof. Prashant Pandey won the
NSF CAREER Award (2024).
Hydra Prime
twinwidth solver by
Mizutani
, Dursteler, and
Sullivan
wins
2023 PACE Challenge
and Theory Award
Youjia Zhou
defended her PhD in Spring 2023 and joined Meta as a Research Scientist in Fall 2023.(Advisor:
Bei Wang Phillips
Lin Yan
defended her PhD in Spring 2022 and became an Assistant Professor at Iowa State University in Spring 2024. (Advisor:
Bei Wang Phillips
Tao Yang
(joining Amazon) and
Benwei Shi
(joining Meta) defended their PhDs in late Fall 2023. (Advisor:
Jeff Phillips
IcebergHT paper from SIGMOD 2023 featured in Quanta Magazine
Prashant Pandey
Research Areas
Approximation / Online Algorithms
A. Bhaskara
J. Phillips
Algorithms & Data Structures
P. Pandey
H. Wang
Computational Biology
P. Pandey
Computational Geometry
V. Pascucci
B. Wang Phillips
J. Phillips
H. Wang
Computational Topology and Topological Data Analysis
V. Pascucci
B. Wang Phillips
Graph Algorithms
A. Bhaskara
B. Sullivan
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.
Artificial Intelligence / Machine Learning
Al-Halah Ziad
Bhaskara Aditya
Brown Daniel
Marasovic Ana
Shankar Varun
Srikumar Vivek
Zhe Shandian
Recent News
Daniel Brown
received an NIH Trailblazer award.
Vivek Srikumar
is a Program Co-Chair for
ACL 2024
Zhenduo Wang
defended his Phd in Fall 2023 and joined Georgia Tech as a postdoc (Advisor:
Vivek Srikumar
).
Ana Marasovic
wins the Best Paper Award at
ACL 2023
Ashim Gupta
is awarded the
Bloomberg Data Science Ph.D. Fellowship
for the year 2023-24.
Vivek Gupta
defended his PhD in Spring 2023 and joined University of Pennsylvania as a postdoc (Advisor:
Vivek Srikumar
).
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)
Data Management
Website:
UtahDB Lab
Faculty:
Jeff M Phillips
Prashant Pandey
El Kindi Rezig
Anna Fariha
Computer Architecture / VLSI
Balasubramonian Rajeev
Brunvand Erik
Nagarajan Vijay
Research Projects
Accelerators and VLSI:
E. Brunvand
R. Balasubramonian
Cache Coherence and Memory Consistency:
V. Nagarajan
Correct-by-Construction Hardware Design:
V. Nagarajan
Memory Systems:
R. Balasubramonian
Hardware Security:
R. Balasubramonian
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
Shreyas Singh, 2024, AMD Research
Ananth Krishna Prasad
, 2022, Meta
Sarabjeet Singh
, 2022, NVIDIA
Utah Arch Lab
Faculty
Rajeev Balasubramonian
Erik Brunvand
Vijay Nagarajan
PhD Students
Ananth Krishna Prasad
Sarabjeet Singh
Lin Jia
Shreyas Singh
An Qi Zhang
Jarrett Minton
Soham Bagchi
Data Management
Fariha Anna
Parashar Manish
Phillips Jeff
Rezig El Kindi
Wang Phillips Bei
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
Prof. Prashant Pandey won the
NSF CAREER Award (2024)
IcebergHT paper from SIGMOD 2023 authored by Prof. Prashant Pandey featured in
Quanta Magazine
Prof. Prashant Pandey will lead a tutorial on Advanced Filter Data Structures at SIGMOD 2024.
Prof. Prashant Pandey won the
2023 IEEE-CS TCHPC Early Career Researchers Award for Excellence in High Performance Computing
Prof. Jeff M. Phillips received an
NSF Award
on Integrating and Learning on Spatial Data via Multi-Agent Simulation.
Prof. Anna Fariha was recognized as one of the
distinguished PC members
at SIGMOD 2023.
Workshop proposal led by Prof. El Kindi Rezig has been accepted to VLDB 2023. The workshop (
Poly
) focuses on recent advances in polystore and data lake management systems. The workshop will take place on September 1st, 2023 at VLDB in Vancouver, Canada.
Prof. Pandey organized a
Workshop on Filter Data Structures
at SPAA 2023 part of FCRC 2023.
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 Group
Website:
UtahDB Lab
Faculty:
Jeff M Phillips
Prashant Pandey
El Kindi Rezig
Anna Fariha
Manish Parashar
PhD student:
Meysam Alishahi
Arman Ashkari
Yuvaraj Chesetti
Whanhee Cho
Mingxuan Han
Shiyi He
Peter Jacobs
Hunter McCoy
Mir Mahathir Mohammad
Foad Namjoo
Hasan Pourmahmood
Bo Zhang
Networking / Operating Systems / Scalable Systems
Burtsev Anton
Eide Eric
Kasera Sneha
Parashar Manish
Ricci Robert
Stutsman Ryan
Van der Merwe Kobus
Research Areas
LTE/5G Mobile Networking, Wireless Security, Spectrum Sharing, Wireless Testbeds:
Kobus Van der Merwe,
Sneha Kasera
Systems (Networking, Scalable Systems); Security / Privacy (Systems Security):
Eric Eide
Sneha Kasera
Robert Ricci
Anton Burtsev
Operating Systems:
Anton Burtsev
Ryan Stutsman
Storage Systems:
Prashant Pandey
Ryan Stutsman
Federated Data Ecosystem:
Manish Parashar
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
NSDI
2024.
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.
Programming Languages / Software Engineering
Eide Eric
Flatt Matthew
Gopalakrishnan Ganesh
Greenman Ben
Hall Mary
Nagarajan Vijay
Panchekha Pavel
Regehr John
Sadayappan Saday
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
Flux Research Group
[Co-directors:
Eric Eide, Robert Ricci, and Jacobus Van der Merwe]
Compilers To Optimize Performance (CTOP)
[PI: Mary Hall]
PLUtah: Programming Languages at Utah
Robotics
Brown Daniel
Henderson Tom
Hermans Tucker
Recent News
Dr. Daniel Brown
received an NIH Trailblazer award in collaboration with Dr.. Haohan Zhang to develop intelligent and adaptive control of a powered neck exoskeleton!
Dr. Brown's work
Autonomous Assessment of Demonstration Sufficiency via Bayesian Inverse Reinforcement Learning
was accepted to HRI 2024
Papers from
Dr. Alan Kuntz
's group, "
Efficient and Accurate Mapping of Subsurface Anatomy via Online Trajectory Optimization for Robot Assisted Surgery
" and "
DefGoalNet: Contextual Goal Learning from Demonstrations For Deformable Object Manipulation
", have been accepted to the International Conference on Robotics and Automation (ICRA) 2024.
Dr. Alan Kuntz
's recent Science Robotics paper, "
Autonomous medical needle steering in vivo
" has been written about in multiple international media outlets, including
Forbes
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
Human-Centered Computing
Kogan Marina
Pandey Vineet
Patil Sameer
Wiese Eliane
Wiese Jason
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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,
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.
Research Labs
Code in Context Lab
Personal Data and Empowerment Lab (PeDEL)
Visualization Design Lab
*New* Research Lab
High-Performance Computing
Berzins Martin
Hall Mary
Parashar Manish
Pascucci Valerio
Sadayappan Saday
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.
Research Labs
Scientific Computing and Imaging Institute
Compilers To Optimize Performance (CTOP)
[PI: Mary Hall]
Recent News
November 2023:
Manish Parashar Receives the 2023 Sidney Fernbach Memorial Award
August 2023:
Bo Zhang & Manish Parashar's paper
"Optimizing Data Movement for GPU-Based In-Situ Workflow Using GPUDirect RDMA."
in Euro-Par 2023 was nominated as a
Best Paper Candidate
June 2023:
Manish Parashar Receives the 2023 Achievement Award in High Performance Distributed Computing
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.
Recent Papers
Exploring Data Layout for Sparse Tensor Times Dense Matrix on GPUs
Khalid Ahmad, Cris Cecka, Michael Garland, Mary Hall
ACM Transactions on Architecture and Code Optimization (TACO) 2023
Optimizing Data Movement for GPU-Based In-Situ Workflow Using GPUDirect RDMA
B Zhang, PE Davis, N Morales, Z Zhang, K Teranishi, M Parashar
European Conference on Parallel Processing (Euro-Par 2023) -
Best Paper Candidate
Performance-Portable Tensor Transpositions in MLIR
Mahesh L, M Ravishankar, M Hall, P Sadayappan
2023 International Workshop on Languages and Compilers for Parallel Computing (LCPC) -
Best Paper Candidate
Communication Optimization for Distributed Execution of Graph Neural Networks
SE Kurt, J Yan, A Sukumaran-Rajam, P Pandey, P Sadayappan
2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
Efficiently Learning Locality Optimizations by Decomposing Transformation Domains
Tharindu R Patabandi, Mary Hall
2023 ACM SIGPLAN International Conference on Compiler Construction (CC)
Effective Performance Modeling and Domain-Specific Compiler Optimization of CNNs for GPUs
Y Xu, Q Yuan, EC Barton, R Li, P Sadayappan, A Sukumaran-Rajam
International Conference on Parallel Architectures and Compilation Techniques (PACT 2022)
Assembling Portable In-Situ Workflow from Heterogeneous Components using Data Reorganization
B Zhang, P Subedi, PE Davis, F Rizzi, K Teranishi, M Parashar
2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid)
High-Performance Architecture Aware Sparse Convolutional Neural Networks for GPUs
L Xiang, P Sadayappan, A Sukumaran-Rajam
International Conference on Parallel Architectures and Compilation Techniques (PACT 2022)
Sparsity-aware tensor decomposition
SE Kurt, S Raje, A Sukumaran-Rajam, P Sadayappan
2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
Scientific Computing
Berzins Martin
Hall Mary
Johnson Christopher
Kirby Mike
Parashar Manish
Pascucci Valerio
Sadayappan Saday
Shankar Varun
Research Areas
Computational Inverse Problems:
C. Johnson
M. Kirby
H. Sundar
Geometry and Mesh Generation:
V. Pascucci
V. Shankar
High-Performance Computing:
M. Berzins
M. Hall
C. Johnson
M. Kirby
V. Pascucci
P. Sadayappan
V. Shankar
H. Sundar
M. Parashar
Modeling Methods and Frameworks:
M. Berzins
M. Kirby
V. Shankar
H. Sundar
Extreme-Scale Data Management:
M. Parashar
Research Groups
Scientific Computing and Imaging Institute
PhD Students
Alberto Cattaneo
Bo Zhang
Budvin Edippuliarachchi
David van Komen
Gaurav Dhir
Han Duc Tran
LeAnn Lindsey
Matthew Lowery
Milena Belianovich
Ramansh Sharma
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.
Security / Privacy
Balasubramonian Rajeev
Eide Eric
Garcia Luis
Kasera Sneha
Nagy Stefan
Patil Sameer
Ricci Robert
Soni Pratik
Xu Jun
Zhang Mu
Research Areas
Cryptography
Pratik Soni
Mobile Security
M. Zhang
Security/Safety of IoT and Cyber-Physical Systems
L. Garcia
Sociotechnical Aspects
S. Patil
Systems Security
R. Balasubramonian
E. Eide
S. Kasera
S. Nagy
R. Ricci
M. Zhang
J. Xu
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
Visual Computing
Al-Halah Ziad
Brunvand Erik
Elhabian Shireen
Isaacs Kate
Johnson Christopher
Kirby Mike
McNutt Andrew
Pascucci Valerio
Rosen Paul
Wang Phillips Bei
Yang Yin
Yuksel Cem
Research Areas
Visualization:
Kate Isaacs
Christopher Johnson
Mike Kirby
Alexander Lex
Andrew Mcnutt
Valerio Pascucci
Paul Rosen
Bei Wang Phillips
Computer Vision:
Ziad Al-Halah
Shireen Elhabian
Ross Whitaker
Computer Graphics:
Eric Brunvand
Cem Yuksel
Yin Yang
Research Groups
Visualization Design Lab
CEDMAV
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.