Workshops

Pre-event Tutorial: Introduction to Python

Online Attendance Only

Faculty Supervisor: Donna French

Introduction to Python

Description: Interested in one of the OurCS@DFW Workshops, but don’t have any Python experience? Python is an easy language for anyone to learn even for coding beginners. Unlike some programming languages, Python's use is expanding and covers a range of programming needs, from basic to advanced. It is frequently used in data science and machine learning which makes it an excellent choice for those interested in those topics. Python is considered a general-purpose language and offers multiple uses in web, software, game development, and more. This tutorial takes place one week before the OurCS@DFW workshops. If you are interested in learning just enough Python to get you started on your own Python journey or to prepare you for one of the workshops, then this tutorial is for you.

Expected coding experience: Basic-level coding experience in some other language – no experience in Python itself is expected. This tutorial will be most beneficial to those with some type of programming background. This background does not need to be extensive – a high school level Java class for example would be sufficient. Due to the limited amount of time, the tutorial, as an example, will focus on how to implement a for loop in Python as opposed to what is a for loop.


Pre-event Tutorial: Introduction to Data Science

Online Attendance Only

Speaker: Sharma Chakravarthy and Chengkai Li

Introduction to Data Science

Description: Please join us for this 5-hour introductory tutorial. You will be exposed to the world of data science, learning why it is important to our world, what tasks are being tackled in data science, and the basic ideas and popular methodologies for such tasks. The tutorial will include real examples and hands-on experience. We will use the browser-based Google Collaboratory for part of the tutorial.

Expected coding experience: Students are expected to have basic Python coding experience. If not, please sign up for the OurCS@DFW pre-event tutorial Introduction to Python. Prior knowledge about machine learning is not expected. You are not expected to become fluent in data science after the tutorial. The goal of the tutorial is to get you started.


Workshop Projects

As part of the application for OurCS@DFW Workshops, students will select the top three projects they would like to work on. Each student will be placed in ONE project group by OurCS@DFW organizers. We will do our best to accommodate your preferences. Learn more about the projects we are offering below.

[CloudMining] Building a cloud-based, secure, data analytic web application with visualization

Faculty Supervisor: David Levine

In-person attendance only
Cloud Mining

Description: This workshop will assist you in creating your own cloud based web application where you will create and manage a database and allow users to do data exploration and mining through a browser. Results will be presented in both textual form and as graphics, such as pie charts and bar charts. We will present a step by step tutorial where you will build a functional web application on a cloud service provider. This workshop will be presented “cookbook” style, with no “theory”, and many examples. No prior web programming or database knowledge is required, but you should have some programming experience in any programming language and not be afraid to try out new things.

Expected coding experience: Basic-level coding experience required - mainly familiarity with conditional statements and loops and creating and managing data arrays. Codes for interfacing with the hardware will be provided.

[QVC] Query, Search, and Analysis of Video Contents

Faculty Supervisor: Sharma Chakravarthy

Hybrid (accept both in-person and online attendance)
QVC

Description: Currently, we are working on video content extraction and querying them for various types of analysis. Understanding videos is a labor-intensive process requiring human concentration and capital. Our research is trying to simplify this process by extracting video contents using ML tools and automate analysis by querying extracted data. Ubiquitous use of inexpensive devices begs for automated tools to tackle this problem of understanding videos. Think of a system where after Amazon delivers goods, you want to get an alert on your phone without watching the video, if someone has stolen or tampered with the item.

As part of this workshop, participants get a taste for various aspects of this problem from: i) state-of-the-art tools available for video processing (e.g., OpenCV, Pandas, . . .), ii) representation of video contents, and iii) how to use a homegrown system for querying these contents. This workshop will introduce baby steps towards the solution of this problem to curious participants to understand and appreciate the complexity of big data analysis problems. Pre-trained deep learning models for object detection (e.g., YOLO), will be developed using popular Python packages (e.g., PyTorch). MavVStream system developed at the IT Lab will be used for simple querying and compare the results with the ground truth. Participants will leave this workshop with a general understanding of the steps in automating video content extraction, querying and analysis. They will be exposed to cutting-edge technologies and solutions as well as hands-on experience in using multiple packages and systems synergistically.

Expected coding experience: Basic Java and Python knowledge.

[AirMon] Development of a Cloud-Based IoT System for Tap Water Quality Monitoring

Faculty Supervisor: Ming Li

Online attendance only
Development of a Cloud-Based IoT System for PM2.5 Air Quality Monitoring

Description: “Air Quality Index, today, in the Dallas/Fort-Worth Region is 52; There may be a moderate health concern for a very small number of people. People with respiratory problems should exercise caution.” -- How to get this information by your own developed IoT systems?

As part of this workshop, students will learn how to build their own IoT based Air Quality Monitoring System with the widely used ESP32 Microcontroller (MCU). Students will generate their own dataset that reflects the PM2.5 air quality of UTA (east) campus and also produce an air quality map for visualization. At the end of this workshop, students are expected to have the fundamental knowledge on how to create their own customized IoT systems and also be exposed to cloud computing technologies. This will enable them to be introduced to state-of-the-art research problems and solutions.

Expected coding experience: Basic-level coding experience for C/C++ and Python and basic knowledge for CpE, e.g., having taken CSE 2440 Circuit Analysis.

[model-is-you] Thinking Declaratively in an Imperative World

Faculty Supervisor: Allison Sullivan

Thinking Declaratively in an Imperative World
In-person attendance only

Description: As software systems become ever more complex, subsequent failures are growing more costly. Software modeling can be leveraged to improve the quality and integrity of software systems. Models enable automated reasoning and correction of system designs before system construction, and automated testing and debugging of the implementation afterwards. However, software modeling languages are declarative in nature, not imperative. Where imperative languages such as Java or C++ use statements that define a sequence of operation, with, at most, changes to a program's state, declarative languages use statements that outline the facts of the solution space or operating behavior as a whole, without any notion of control flow. As such, becoming adept at declarative programming forms the first major obstacle towards reaping the benefits of software modeling. In this workshop, you will learn how to problem solve from a declarative perspective rather than an imperative one. Students will build their declarative problem-solving skills by exploring Baba-Is-You levels and then hone their skills solving logic problems in Z3, a SMT solver developed by Microsoft Research.

Expected coding experience: Beginner programmers (both high school and undergrad) are welcome. This workshop involves writing some small python programs; therefore, it is recommended that you have some prior experience with programming.

[SmartHome] Home Automation System Design

Faculty Supervisor: Habeeb Olufowobi

Hybrid (accept both in-person and online attendance)
Graphic Implying a smart, connected home

Description: The concept of home automation and control has evolved into incorporating the capabilities of the Internet of Things (IoT) to provide enhanced benefits for home management. Dubbed Smart Home, automation fuses several embedded sensors and devices enabled with connectivity that allows for communication with the environment and other devices. Automation and the IoT have become ubiquitous providing users with a convenient lifestyle and heightened security. The smart home automation intends to control many devices using different protocols, such as Wi-Fi, Bluetooth, ZigBee, for an enhanced way of life and safety, and has morphed into the smart city ecosystem that is an exciting research area aiming to provide improved city services and a higher quality of life.

In this workshop, we aim to develop a prototype home automation system capable of managing different devices in our home. Our prototype system will combine embedded system techniques with mobile applications and GSM technology for communication. Participants will develop a system that connects electrical appliances with wireless devices, such as Bluetooth, and can be controlled via a mobile application and gestures. Participants will also program a prototype system to control the appliances automatically based on the user's needs and extend it with preprogrammed schedules. At the end of the workshop, participants will gain an understanding and working knowledge of smart home applications controlled through their mobile devices and movements in the prototyped system environment, read connection diagrams and pin layouts, and develop app using MIT App Inventor.

Expected coding experience: Basic-level coding experience.

[Misinfodemic] Surveillance of Public Health Misinformation on Social Media

Faculty Supervisor: Chengkai Li

Hybrid (accept both in-person and online attendance)
Constructing Deep Learning Models for Detecting Check-Worthy Factual Claims

Description: The onslaught of health misinformation online poses a severe threat to the well-being of society as it hinders health outcomes and exacerbates public health crisis. In this workshop we will build machine learning models and visualization dashboard for the surveillance of public health related (mis)information on Twitter. The tool can help government agencies, researchers, and the public to better understand what misinformation is being spread and thus better tackle it. The project will use IDIR Lab's APIs (https://idir.uta.edu/claimbuster/api/) and will be integrated into the lab's current COVID-19 information dashboard https://idir.uta.edu/covid-19/ and ClaimPortal https://idir.uta.edu/claimportal/. Students in the workshop will work on an active research project that can have important societal impacts. They will study the concepts and technologies for various natural language processing tasks. They will learn to use various Python libraries in building machine learning and deep learning models as well as in visualizing information.

Expected coding experience: Basic coding experience in Python. Students without Python experience can attend, but please also sign up for the pre-event tutorials on Python and Data Science.

[VIRUS] How to Take Apart a Computer Virus

Faculty Supervisor: Sean Pierce & Carter Tiernan

Hybrid (accept both in-person and online attendance)
How to Take Apart a Computer Virus

Description: In this workshop you will disassemble, analyze, and combat a multi-layer cross platform malware sample. You will learn about modern threats and how to combat them.

Expected coding experience: Zero or almost no coding experience. However we will be looking at a lot of scripting level code. Familiarity with programming concepts such as if statements and loops especially in PowerShell/Bash/JavaScript is highly recommended.

[ThreatFinder] Threat Finder ft. Twitter: Visualizing a Real-Time Security Knowledge base Using Twitter Data

Faculty Supervisor: Shirin Nilizadeh

Hybrid (accept both in-person and online attendance)
Eyes that See Sounds Workshop

Description: Security threats such as online scams, malware and software vulnerabilities are always evolving to evade detection and do the majority of their damage during the early hours of their first appearance. In our work on "Evaluating the Effectiveness of Phishing Reports on Twitter,'' we found that information shared by security conscious users on Twitter to be a new and highly reliable source for identifying these threats, which also consistently outperform several prominent security tools and blocklists. Thus, in this workshop, we propose to implement a real-time visual dashboard which utilises security focused data shared on Twitter to identify new threats. Along the process of construction of this dashboard, students will learn about: (a) using Twitter data mining functionalities, including an extensive overview of Twitter’s Academic API, Twarc, Helium and several Python based data-science libraries, and then organizing this data using SQLite into a structured database, (b) The analysis and tracking of real-life security threats such as phishing attacks, malware and CVE (Common Vulnerabilities and Exposure) using VirusTotal, WHOIS, OpenPhish and PhishTank, (c) Building a real-time visualisation dashboard which marks security threats in real time throughout the globe using HoloViz, and (d) Getting introduced to basic statistical analysis approaches to compare the performance of security information shared on Twitter with reports by industry leading antivirus/anti-phishing tools.

Expected coding experience: No prior knowledge in computer security is required, though basic-level experience in Python is required, additionally some introductory knowledge database concepts would be helpful.

[CPS-Health] Building Cyber-Physical Systems for Healthcare

Faculty Supervisor: VP Nguyen

In-person Attendance Only
Building Cyber-Physical Systems for Healthcare

Description:Cyber-physical systems (CPSs) are transforming many parts of our life including homes, healthcare, cities, transportation, and others. CPS is the bridge between cyber and physical spaces, taking the most advanced technologies of both worlds and providing significant positive impacts on our everyday life. In this workshop, we will learn how to build a basic CPS system for a healthcare application. We will develop a close-loop sensing and intervention wrist-worn device that is able to capture multiple signals from the human body and provides just-in-time interventions. The developed CPS prototype will include a few main components such as sensing, intervention, computing, and wireless communication. In addition, you will also be introduced to some state-of-the-art wireless, mobile, and wearable systems developed by Wireless and Sensor Systems Lab (http://wsslab.org/) at UT Arlington for human health and environmental monitoring.

Expected coding experience: Basic-level coding experience, C/C++ and Python/Matlab

[Security-H] Stealing Secret Data from Computers Without a Network

Faculty Supervisor: Mohammad Atiqul Islam

In-person attendance only
Stealing Secret Data from Computers Without a Network

Description: Computers store many secret data such as passwords and encryption keys. Many bad actors try to steal this information for malicious purposes. To avoid such security threats, mission-critical computer systems use "air-gapping," which means no network connectivity to the outside world/internet. However, there are ways to get data out of computer systems even without a network. In this workshop, we will build such a system. We will utilize electromagnetic interference (EMI) from computer power supplies to steal secret passwords from a computer. We will use our power network to steal the data as even air-gapped systems need to be connected to power outlets. We will embed the stolen data in the victim computer's power consumption. We will sense the change in the victim's power using voltage measurement at a far-away power outlet. From the power change, we will extract the stolen data. The organizers will provide the hardware needed to collect data while the participants will build algorithms to extract secret information from the data.

Expected coding experience: Basic-level coding experience required - mainly familiarity with conditional statements and loops and creating and managing data arrays. Codes for interfacing with the hardware will be provided.

[Genome] Computational Approaches to Analyzing Infectious Disease

Faculty Supervisor: Jacob Luber

Computational Approaches to Analyzing Infectious Disease

Description:The societal changes from COVID-19 has sparked a renewed interest in computational approaches to analyzing infectious disease. In this workshop, we will learn about molecular biology, genetics, and then apply computational tools to understand the genomics of bacterial and viral genomes. In a hypothetical situation for the workshop, you are working as a computational biologist for the Center for Disease Control (CDC) on the infectious disease rapid response team. A new antibiotic resistant variant of the plague (caused by the Yersenia pestis bacteria and called the ”black death” during the middle ages) has been spreading rapidly in London and New York City. Your team has isolated the new variant from a patient and conducted short read genome sequencing on it. You will learn:

  • What a genome is
  • How we represent genomes based on string algorithms
  • How we sequence viral and bacterial samples
  • How to computationally “assemble” genomes from infectious diseases
  • How to analyze genomes

Expected coding experience: The only pre-req is that you bring a computer capable of accessing google colab.

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OurCS@DFW Workshops - hands-on projects for undergraduate and high-school students
February 18-20, 2022


Pre-event Tutorial: Introduction to Data Science
February 12, 2022


Pre-event Tutorial: Introduction to Python
January 28-29, 2022


Funding for the Event Provided By

IEEE
Lockheed Martin
Rotary

With Supoport From

C.A.R.I.D.A

TMAC

Of Interest

The Student Computing Research Festival (SCRF) is also happening at UTA. Learn more about it.


Computer Science and Engineering at UTA