Our stellar programs attract oustanding students from around the world who work closely with our faculty to advance state-of-the-art research in computing technologies. We attribute our success to a strong tradition of collaborative research, close working relationships with local industries, state-of-the-art facilities and a dedicated committment to student achievement.

We offer bachelor of science degrees in computer science (CS), computer engineering (CPE), and a master's degree in software engineering (MSE). Our MSE program is unique within the UW system and offers graduates very desiriable employment opportunities. We also offer a very popular dual-degree program that awards students a BS in Computer Science and a Master's in Software Engineering within a condensed time frame of only five years. If you have any questions please contact us at


Spring 2022: Lab Schedule
Spring 2022: MFT exam offered on Apr. 22nd and Apr. 29th

Deans Distinguished Fellow: Adam Grunwald

Adam Grunwald has received a Dean's Distinguished Fellowship to work with Dr. Elliott Forbes on heterogeneous multicore processor design over the summer months. His research topic is described in more detail below. Congratulations Adam!

This project revolves around single-ISA heterogeneous multicore processor design. Multicore systems have multiple processor cores, each of which can execute a program independent of the other cores. Most multicore processors have cores of the same architecture -- that is, their cores are homogeneous. Generally, the homogeneous cores have an architecture that performs adequately across the wide variety of programs. However, some programs have computational needs that are outliers. Heterogeneous multicore processors have cores with different architectures. Some of the heterogeneous cores may have architectures that perform adequately for most programs. But some of the heterogeneous cores can have architectures that are atypical, hopefully matching the computational needs of any outlier program behavior.

One of the challenges of heterogeneous processors is to determine on which core a given program should run. Ideally, this decision is made ahead of the execution of the program because a mismatch between a programs computational needs compared to the architecture ran lead to a lost performance opportunity. The goals of this project are to analyze the runtime behavior of processor benchmark programs to find their computational bottlenecks. This can be done through simulation. A processor simulator can be configured such that processor hardware resources are unrealistically large. Then each hardware resource type can be reduced, one-at-a-time. If the runtime performance doesn't change due to the reduction in a particular hardware resource, then that resource is not a bottleneck for the benchmark program. However, if the performance degrades as a result of reducing the hardware resource, then that resource is the bottleneck for that program. Understanding the computational bottlenecks of benchmark programs can then lead toward more accurate steering of programs to heterogeneous cores.

Project Highlight: Audio Canvas

Christian Strauss recently completed his MSE capstone project entitled Audio Canvas: An Audio Visualization Tool. The video below presents a brief summary of his work. This project created a web application to create visualizations of audio streams such that the visualizations support 3D objects, meshes, and 2D text and textures. Nice work Christian!

Professional Development Grant Award

Becky Yoshizumi, CS ADA, was recently awarded a University Staff Professional Development Grant from the University Staff Council. The grant is sponsoring a speaker related to understanding how generational differences affect student, staff and faculty perspectives on aspects of work and life. The Employment Enrichment Day Committee helped to organize the event and provides the details given below.

Ever wonder why Millennials and Gen Z colleagues/students often have a different perspective on things? Steve Bench, founder of Generational Consulting in Madison, has answers. Bench will present “Attracting Tomorrow’s Talent with Today’s Leaders” at 10 a.m. Wednesday, May 25, in 1309 Centennial Hall. The talk will be preceded by a reception to reconnect and network from 9-10 a.m. in Hall of Nations, Centennial Hall. The events are organized by the Employee Enrichment Committee.

The keynote will focus on talent attraction and workforce retention by building understanding of who we are, how we were raised, and how each generation views “work” as a part of their identity. Examples can also apply to working with students from different generations. Bench will provide an overview of talent attraction and retention strategies to overcome generational differences and attract Millennial and Gen Z employees and keep them from leaving. Adulthood has changed, and depending on life stages, some may prioritize lifestyle over career. Bench will provide tips on how to manage and motivate someone who may not be as committed to their job as in previous generations.

ACM TELO Article

Dr. David Mathias has had an article accepted for publication in the highly regarded ACM Transactions on Evolutionary Learning and Optimization journal. The paper is co-authored by Dr. Annie Wu of the University of Central Florida and Daniel Dang, a student at Whitman College. The articles abstract is given below.

In this work, we investigate the application of a multi-objective genetic algorithm to the problem of task allocation in a self-organizing, decentralized, threshold-based swarm. We use a multi-objective genetic algorithm to evolve response thresholds for a simulated swarm engaged in dynamic task allocation problems: two-dimensional and three-dimensional collective tracking.  We show that evolved thresholds not only outperform uniformly distributed thresholds and dynamic thresholds but achieve nearly optimal performance on a variety of tracking problem instances (target paths).  More importantly, we demonstrate that thresholds evolved for some problem instances generalize to all other problem instances, eliminating the need to evolve new thresholds for each problem instance to be solved.  We analyze the properties that allow these paths to serve as universal training instances and show that they are quite natural.

After a priori evolution, the response thresholds in our system are static.  The problem instances solved by the swarms are highly dynamic, with schedules of task demands that change over time with significant differences in rate and magnitude of change. That the swarm is able to achieve nearly optimal results refutes the common assumption that a swarm must be dynamic to perform well in a dynamic environment.

MICS 2022 Best Student Paper Award

Two MSE students working under the supervision of Dr. Mao Zheng (Computer Science) and Dr. Song Chen (Mathematics) received the MICS 2022 Best Student Paper award for their paper entitled "A Detection Tool for Traffic Objects". Congratulations on this outstanding work. An abstract of their paper is given below.

This manuscript describes the design and development of a software detection tool for traffic objects. It is a web-based system with a built-in machine learning model. The system allows users to upload images and videos and then detects traffic objects, such as cars, trucks, traffic lights, pedestrians, and bikers. Our machine learning model, using the YOLOv3 algorithm, will process images and videos and return results with the category and location of all detected objects. The results will be stored in the history, and users can then manage the information from there. Most of our data for training the YOLOv3 model came from the Udacity Self Driving Car Dataset. We tried the YOLOv3 model with different backbones such as, Darknet, Mobilenet and Efficientnet. The best combination of both accuracy and speed was obtained using darknet-53, so this network was chosen as our backbone.

The technologies used in this project are HTML, CSS and JavaScript on the frontend, and Python, TensorFlow and Django on the backend. We used MySQL as the database and deployed the project in a Linux Server.

To further improve our model’s mAP, we could use a larger dataset scale. However, it will require a longer training process and higher computing power. This manuscript also describes future work on how to incorporate our model as part of a road monitoring and/or self-driving system

Deans Distinguished Fellow: Walter Leifeld

Walter Leifeld has received a Dean's Distinguished Fellowship to work with Dr. David Mathias on swarm intelligence research over the summer months. His research topic is described in more detail below. Congratulations Walter!

An artificial swarm consists of a large number of simple agents that must solve a problem, typically through iterative performance of some number of tasks.  Because assignment of tasks to agents by a central authority introduces points of failure, swarms are typically decentralized. This means that each agent must determine independently which tasks to perform and when. This problem, known as decentralized task allocation is difficult, and becomes more so when the task requirements are dynamic, but is critical to effective swarm performance.  In the problem domains studied, swarm performance increases when trained using a genetic algorithm, with the tradeoff of high training time.  Universal training instances have been found within these domains, allowing a swarm trained on one task set to perform well on most others.  This avoids costly training time.  This research will develop a generalized model that can represent the task allocation requirements of a wide range of applications and explore universal training instances within this model. This will increase our understanding of solving complex problems dependent on large numbers of tasks and the general properties of universal training instances, independent of any one problem domain.

2022 IEEE AP-S/URSI Conference Publications

Several research articles by Dr. Dipankar Mitra have been accepted for conference public in IEEE AP-S/URSI 2022 the flagship conference dealing with antennas and propagation. One of those papers is the result of collaboration between Mayo Clinic, South Dakota School of Mines and UWL. This work is entitled On the Dielectric Characterization of Biological Samples for Microwave Imaging Reconstruction. See the abstract below.

An application of engineered materials to control electromagnetic waves and shield devices to maintain antenna parameters in a highly scattering multiple-antenna environment is shown. In a multiple-antenna environment, where each antenna operates at different frequencies, the scattering effects can be significantly reduced by enclosing an individual antenna with an engineered electromagnetic structure operating at a wavelength higher than the source. Numerical simulations are performed in COMSOL Multiphysics to demonstrate the success of the proposed shielding technique involving two 2D line-dipole antennas and a cylindrical enclosure of engineered EM materials at microwave frequencies.

ICMHI 2022 Conference Publication

CS faculty member Dr. Kasi Periyasamy, MSE student Athira Kaivelikkal, and Dr. Venkateswaran Iyer of Allina Health authored a paper that they will present at the 2022 International Conference on Medical and Health Informatics. The paper is entitled "A Mobile Application for Chronic Kidney Disease (CKD) Diagnosis" and the abstract is given below.

Chronic Kidney Disease (CKD) is a condition where kidneys partially work in filtering waste products from blood. In most cases, CKD patients do not experience any symptoms in the early stages. This makes early detection of CKD much harder. The result is starting treatment at a later stage which not only complicates the health condition of the patient, but it also increases the healthcare cost for the patient. This paper describes a mobile application the authors have developed which can be used by any healthcare practitioner. In addition to detecting the presence and the stage of CKD, the application also lets the user find out two risk factors associated with CKD patients, namely Anemia and Mineral Bone Disease (MBD). After detecting either or both of these risk factors, the tool recommends initial treatment plans for the same based on guidelines provided the National Kidney Foundation (NKF) in the United States.

Dr. Petullo: Faculty Development Grant

Dr. Mike Petullo was awarded a UWL Faculty Development Grant to work on expanding an online learning environment known as Aquinas. An abstract describing his work can be found below. Aquinas is open source software. The canonical Aquinas deployment is and more information about the project itself is available at

The project will refine a tool named Aquinas that uses an interactive, online learning environment to deliver content for computer science and cybersecurity courses at UW–L. Aquinas applies an everything-as-code approach to teaching the practice of programming and exploit development using hands-on exercises. Teachers define exercises using a machine-readable format, and Aquinas processes these definitions to setup artifacts such as instructions, grading scripts, and network targets. Students submit solutions using Git and benefit from immediate grading. This project will modify Aquinas along several dimensions elicited through student surveys, and it will prepare Aquinas for further deployment in support of teaching efforts at middle schools, high schools, and other universities.

Wisconsin Space Grant Award

The Wisconsin Space Grant Consortium has awarded the 2021-2022 Early-Stage Investigator award to Dr. Dipankar Mitra. Dr. Mitra will use the grant to perform theoretical work that will eventually enable satellite links using steerable phased array antenna systems. The full project abstract is included below. Congratulations Dr. Mitra!

NASA’s Space Technology Mission Directorate (STMD) commences its new era of space exploration at the Moon by focusing on advancing technologies and testing new capabilities, which is crucial for crewed mission in Mars. In that effort, it is of great importance to the NASA’s exploration program to have capability of testing a variety of technologies for future flight application. This leads to the requirement of an alternative solution for Internet of Things (IoT) technologies, which aims to provide a universal connectivity. The satellite based IoT technology can be an excellent candidate in this regard. In this research, we aim to address the theory and practicality of achieving a bidirectional connectivity between the remote assets and Low Earth Orbit (LEO) satellites. The proposed research project aims to facilitate a ubiquitous IoT connectivity using a smart electronically steerable phased array antenna system for satellite earth terminals. To implement such a highly efficient antenna system, the preliminary requirement would be to compute the satellite link budget for the proposed scheme. The link budget would essentially help determine the required gain of the antenna system and hence enable the design and fabrication of the single element antenna.