We are excited to announce that we are offering a pilot workshop for our newly revamped DeapSECURE Deep Learning lesson (module 4). This workshop features both lecture-based and hands-on coding activities that utilize a high-performance computing (HPC) environment. The material includes an introduction to machine learning and deep learning, a case study that applies deep learning for cybersecurity (app classifier based on SherLock dataset), an overview of neural network concepts, model tuning using HPC, and further applications of deep learning in the real world.

Techniques taught in DeapSECURE workshops are foundational and transferable to other areas, including science, engineering, finance, linguistics, etc. (Why Cybersecurity?)

What You’ll Learn:

  • Basics of machine learning and deep learning
  • Building and tuning neural networks with Keras
  • Using ODU’s HPC system for model training
  • Visualizing and analyzing deep learning results
  • Real-world application: Mobile device cybersecurity

Workshop Audience

This training program is aimed at (1) students with interests in cutting-edge cybersecurity research, (2) those who need to use deep learning techniques for their research projects, and/or (3) those who want to learn how to harness the power of HPC through a realistic example.

Basic skill of writing computer programs is required to participate in this training. The specific language matters less; it is the programming skill that matters. Popular languages such as C, C++, Java, JavaScript, Python, R, and Matlab would be fine.

Schedule

This summer workshop will take place on August 11th from 1pm – 5pm and August 12th from 9am – 5pm at Old Dominion University (ODU) in Norfolk, VA, and will also be offered through Zoom.

Date & TimeLesson Episodes
August 11, 2025 | 1pm – 5pmIntroduction to Machine Learning & Deep Learning
Deep Learning to Identify Smartphone Applications
Overview of Deep Neural Network Concepts
Classifying Smartphone Apps with Keras
August 12, 2025 | 9am – 5pmTuning Neural Network Models for Better Accuracy
Effective Deep Learning Workflow on HPC
Post-Analysis for Modeling Tuning Experiments
Deep Learning in the Real World

Format

The workshop will be conducted in-person at Old Dominion University campus and virtually over Zoom. (Whenever possible, in-person participation is strongly encouraged.) It will consist of a mix of lectures / hands-on activities to introduce learners to basic concepts and practical skills in HPC, Machine Learning, and Neural Networks. Materials will be introduced at an introductory level. Hands-on activities will be carried out using common tools such as Python, Jupyter notebooks, UNIX shell, on ODU’s Wahab HPC. There will be teaching assistants to help the learners.

Rules & Requirements

  1. This is a pilot workshop of a new lesson; expect some rough edges as we will be teaching this lesson for the first time.
  2. We expect learners to engage seriously with the learning materials during the workshop, and will provide us honest feedback after the workshop, so we can improve the lesson.
  3. This is a hands-on training. You must bring and use your computer to connect to and perform exercises on ODU’s HPC cluster. If you are attending virtually, the same requirements apply.
  4. The two-day workshops build upon one another! If you sign up and are accepted, you must participate in both days.

Survey Disclosure

Assessments and participants’ feedback are an integral part of this NSF-funded training program; we require that all participants fill both the pre- and post-workshop surveys. By participating in this training, you agree to respond to our pre- and post-workshop surveys. Your responses will remain anonymous and confidential. We will use your collective responses and feedback to help us improve our lessons. Any published statistics will be reported in a manner that preserves the privacy of individual responses.

Sign-up

You can register for the workshop using the following informal preliminary sign-up sheet here. We may reach back to you to request for clarification/information regarding your registration, if necessary. You will be notified before the workshop starts whether you are accepted into the training program. The pre-workshop survey will be sent after admittance to the workshop is confirmed.

Have Questions?

If you have questions regarding this workshop, please send an email to t3ciders@gmail.com .

Acknowledgements

This training project is funded by the U.S. National Science Foundation CyberTraining grants #2320998 and #2320999.