CS4760 & CS5760 Scientists and App Ideas
Below is the list of scientists and their potential applications for collaborative CS4760 & CS5760 teams.
Briana Bettin – Assistant Professor, Computers & Cognitive and Learning Sciences
Contact Information
Email: bcbettin at mtu.edu
Phone:
Office: Rekhi 202
Computer Science Department
Michigan Technological University
App Idea: Programming Analogies
Learning programming can be a difficult task, especially with how novel computing concepts can seem when first explained. Analogies can help instructors better connect programming content with real world experiences to ground understanding for students, but creating good analogies can be a challenge depending on the needs and context. This app is intended to help instructional staff (teachers, teaching assistants, and professors) easily find structured analogies that may help them better explain programming concepts to their students, creating more options for understandable and accessible programming education. This app will require a unique visual display to help showcase the structured components of an analogy effectively, and a robust sort to allow instructors to search for analogies across concepts like programming topic and analogy domain (topic used in the analogy). With the ability to draw from a dataset of existing structured analogies, instructors will be able to easily search and view possible additions to their classroom. The ability to compare analogies, create new structured analogies to share, and to add notes about analogies (such as if they worked in a lecture) would further expand this tool’s value to instructors in not only finding analogies, but analyzing existing ones and working to create their own. This app will allow for further implementation of and research into programming analogies, and has the potential to move the field of computing education (and in turn, the courses your future colleagues may find themselves in) forward in new and exciting ways as a result.
Initial Meetings
First Team-Scientist Meeting: January 17, Tuesday, 1/17/2023, at 4 pm by Zoom
Second Team-Scientist Meeting: January 24, Tuesday, 1/24/2023, at 4 pm by Zoom
By Zoom
Issac Wedig – Kinesiologist
Contact Information
Email: ijwedig at mtu.edu
Phone:
Office:
Kinesiology and Integrative Physiology Department
Michigan Technological University
App Idea: BFR Exercise Trainer
Exercise with blood flow restriction (BFR) is emerging as an effective training option to increase muscle size and strength in healthy, clinical, and athletic populations. This modality involves exercising with a tourniquet (i.e., pressurized cuff or elastic band) applied to the upper portion of a limb, which serves to partially limit blood flow going to the working muscles (arterial) and returning to the heart (venous). The main advantages that BFR exercise has over traditional training are 1) increases in muscle size and strength can be achieved using low exercise intensities, and 2) these adaptations can be stimulated using both resistance (i.e., lifting light weights) and aerobic (i.e., walking) exercise. Accordingly, BFR offers an alternative option for improving muscle size and strength in populations such as the elderly and those with orthopedic limitations or various diseased states to whom higher intensity exercise may be difficult or contraindicated. Despite its growing use in sport and rehabilitation settings, implementation of BFR remains challenging for practitioners. There are no standardized protocols or guides available for conducting medical screening of potential candidates, selecting an appropriate training technology for performing BFR, or determining safe and effective tourniquet pressures to utilize. This app is intended to guide exercise professionals (i.e., physical therapists, personal trainers, coaches) through the steps of implementing BFR with their patients/clients. Specifically, the app will 1) conduct medical screening to determine the relative safety of performing BFR, 2) give recommendations for appropriate training technologies to utilize, and 3) determine the proper amount of tourniquet pressure to apply during exercise. An additional feature may include providing BFR exercise prescriptions for both resistance and aerobic exercise. Collectively, this app will help to enhance access to BFR and ensure that safe and effective practices are utilized in sport and rehabilitation settings.
Initial Meetings
First Team-Scientist Meeting: January 17, Tuesday, 1/17/2023, at 4 pm
Second Team-Scientist Meeting: January 24, Tuesday, 1/24/2023, at 4 pm
In-person at SDC 121-B in the multipurpose room
Sachin Fernandes – Cloudflare Developer
Contact Information
Email: fernandes.sachin at gmail.com
Phone:
Office:
Cloudflare
San Francisco, CA
App Idea: PG&E Energy Reducer
The UN recently announced that the world’s population surpassed 8 billion people and is not showing signs of slowing down. That’s a lot of people that consume energy and produce waste.
Most people are willing to cut down their energy and waste production but are unaware of how to do so.
The PG&E energy reducer app aims to analyze a user’s energy consumption and provide a way to visualize their usage and cut down on their waste.
The initial version of the app will focus on PG&E users. It will be designed to surface patterns and anomalies in a user’s energy usage and provide general guidance for energy reduction. Later versions of the app can provide the user specific guidance based on individual usage and learned AI/ML rules.
The app will provide exposure to libraries such as C3Js, service workers, web frameworks, authentication and interfacing with 3rd party APIs.
Initial Meetings
First Team-Scientist Meeting: January 18, Wednesday, 1/18/2023, at 4 pm EST (1 pm PST)
Second Team-Scientist Meeting: January 25, Wednesday, 1/25/2023, at 4 pm EST (1 pm PST)
By Zoom
Jesse Alger & Mary Ellen Miller – Environmental Engineers
Contact Information
Email: Jesse Alger: jlalger at mtu.edu, Mary Ellen Miller: memiller at mtu.edu
Phone:
Office:
Department of Civil, Environmental, and Geospatial Engineering
Michigan Technological University
App Idea: Urban Green Infrastructure and Flood Risk
Green stormwater infrastructure practices are a viable and beneficial alternative to gray stormwater infrastructure. Green stormwater infrastructure relies on vegetation, soil and natural systems to manage stormwater runoff by slowing down and allowing stormwater to infiltrate into the soil where it can be used by vegetation. Slowing down and reducing stormwater runoff can help prevent urban flooding and reduce the quantity of runoff that reaches sewers and water bodies. Water quality is also improved as plants and soil filter nutrients and contaminants. Understanding how placement and type of green stormwater infrastructure can affect urban hydrological processes is important for stormwater management and urban flood risk mitigation. Mapping both green stormwater infrastructure and flooding is an important step to understanding the dynamics of urban hydrology but is often difficult due to a lack of data on where green stormwater infrastructure is located throughout urban areas and what areas are most prone to flooding.
The development of this census application will help to educate the public about the importance and benefits of urban green stormwater infrastructure as well as provide invaluable information on the location of green infrastructure and areas that are prone to flooding. Users will use the app to learn, locate and classify urban green infrastructure. Having users upload photos of green infrastructure and flooding will help scientists and managers locate problematic flood zones and improve public safety.
Initial Meetings
First Team-Scientist Meeting: January 17, Tuesday, 1/17/2023, at 4 pm
Second Team-Scientist Meeting: January 25, Tuesday, 1/25/2023, at 4 pm
By Zoom.
Leo Ureel – Assistant Professor, Computer Science
Contact Information
Email: ureel at mtu.edu
Office Phone: (906) 487-1816
Office: Rekhi Hall 209
Computer Science Department
Michigan Technological University
App Idea: Antipattern Coder
One way to identify problematic code (termed “Antipatterns”) is to scan the source code using regular expressions that match on the bad code. Currently, these regular expressions are developed by computer scientists and stored in a database (see examples at https://webta-dev.cs.mtu.edu/PatternDB/ User your MTU account to login.) The problem with this method is that regular expressions somewhat esoteric and are not well known, even among practicing programmers. You will develop a database system for storing antipattern definitions that has a front-end which includes a new way of describing problematic code while maintaining regular expressions as the underlying representation. This will make it easier for us to put tools into the hands of general practitioners. This is a UX (User eXperience) challenge and an area of active Human Factors research.
Initial Meetings
First Team-Scientist Meeting: January 17, Tuesday, 1/17/2023, at 4 pm
Second Team-Scientist Meeting: January 25, Tuesday, 1/25/2023, at 4 pm
By Zoom.
Bill Siever – Principle Lecturer
Contact Information
Email: bsiever at wustl.edu
Phone/Text: (573) 364-8890
Office:
https://cse.wustl.edu/faculty/Pages/Bill-Siever.aspx
Computer Science
Washington University in St. Louis
App Idea: Micro:bit Bluetooth
The micro:bit is a kid-friendly computing platform that’s used for both computing education and STEM/Maker activities. Its data logging feature, described at https://microbit.org/get-started/user-guide/data-logging/, is particularly beneficial for science activities. With the data logger, it only takes a few minutes to setup the micro:bit to collect and store data from sensors. By default, the data logger saves all data to the micro:bit’s flash memory. In order to view the data from flash, the micro:bit has to be connected to a computer, which may disrupt the data collection process. The goal of this project is to use create an app that uses the micro:bit’s bluetooth support to wirelessly view and collect data, even while collecting data live. The app will run in a Chromium-based browser (e.g., Chrome or Edge), which has WebBluetooth support. Libraries will be provided to deal with the bluetooth connections and collection of data. Also each team member will receive a micro:bit for development. The focus of the project will be on a user interface that will allow users to select at least one micro:bit (preferably support for several simultaneous micro:bits), to retrieve collected data, and to visualize the data. All data is like a time series and will need to be displayed in a graph, which may be dynamically updated as data streams in. Depending on the quantity of data, users may need to pan or zoom the graph and enable/disable views of separate time series. In addition, users should have the ability to interact with a few features of the provided library to erase the micro:bit’s log or download CSV files of the data.
Initial Meetings
First Team-Scientist Meeting: January 17, Tuesday, 1/17/2023, at 4 pm EST (3 pm CST)
Second Team-Scientist Meeting: January 24, Tuesday, 1/24/2023, at 4 pm EST (3 pm CST)
By Zoom
Kaitlyn Roose – Director of Esports
Contact Information
Email: kmroose at mtu.edu
Phone/Text: (906) 487-1224
Office:
https://www.michigantechhuskies.com/sports/esports/coaches/Roose-Kaitlyn
Esports
Michigan Technology University
App Idea: Esports SSBU Stats App
A mobile and desktop web app for recording the stats of ePlayers during a tournament. During or after a game, players or statisticians record the stats in the apps. The statistician and ePlayers can view individual ePlayer stats.The statistician can download a CSV to perform more advanced statistical analysis. Admin manages user accounts.
App challenges are responsive UI because the app must run on both mobile and desktop platforms, and Spring Security for authentication and authorization.
Initial Meetings
First Team-Scientist Meeting: January 17, Tuesday, 1/17/2023, at 4:30 pm
Second Team-Scientist Meeting: January 24, Tuesday, 1/24/2023, at 4:30 pm
In-person at SDC 266