Offered Tutorials/Workshops

Offered Tutorials/Workshops

The following tutorials/workshops are offered for ACMSE 2026:


Architecting Reliable and Verifiable AI with Retrieval-Augmented Generation

Presenter: Vishwas Lele (WordX – USA)
Type of Event: Tutorial
Date: Thursday, April 23, 2026
Time: 09:30-11:30 (Central Time)
Duration: 2 hours
Room: Room 154

Abstract:
Retrieval-Augmented Generation (RAG) has emerged as a dominant architectural pattern for enterprise AI. However, transitioning from simple prompt-based applications to reliable, production-ready systems remains a significant engineering challenge. This session explores the design, implementation, and evaluation of RAG pipelines tailored for complex data environments and demanding commercial use cases. Participants will examine the architectural evolution of RAG, from Foundational and Naive approaches to optimized Advanced pipelines, composable Modular frameworks, and autonomous Agentic systems. The session shifts the focus from reactive, trial-and-error debugging to proactive pattern recognition by analyzing seven key structural failure modes in RAG systems—such as factually inconsistent hallucinations, missed top-ranked context, and incorrect specificity—and presenting research-backed strategies to mitigate them. By unpacking the seminal advances underlying semantic search and large-scale retrieval, this session equips attendees with essential research insights and practical guidance for building robust and trustworthy RAG systems.

Keywords:
Retrieval-Augmented Generation (RAG), Enterprise AI, Verifiable AI, AI Reliability, Semantic Search, Large Language Models (LLMs), Vector Databases, Dense Retrieval, Hybrid Search, Re-ranking, Agentic AI.

Covered Topics:
The covered topics include:

  • Evolution of RAG architectures: Foundational, Naive, Advanced, Modular, and Agentic systems
  • Design, implementation, and evaluation of production-ready RAG pipelines
  • Retrieval strategies: dense retrieval, hybrid search, and re-ranking techniques
  • Analysis of seven structural failure modes in RAG systems
  • Techniques to mitigate hallucinations, missed context, and specificity errors
  • Verification and evaluation strategies for reliable RAG systems
  • Transition from reactive debugging to proactive, pattern-driven system design
  • Foundations of semantic search and embedding-based retrieval
  • Scaling RAG systems for complex enterprise data environments

Prerequisites for Participants:
Basic understanding of ML and AI, familiarity with NLP (Natural Language Processing) concepts, working knowledge of LLMs, and programming experience (preferably in Python).


An Introduction to Embedded Systems Programming

Presenter: Jay Snellen (Jacksonville State University – USA)
Type of Event: Tutorial
Date: Thursday, April 23, 2026
Time: 14:00-17:15 (Central Time)
Duration: 3 hours
Room: Room 154

Abstract:
“Embedded systems” are small, highly efficient computers that are built into another device and are typically dedicated to controlling or monitoring the device. The operation of the embedded system is so tightly integrated with the device that, from the user’s point of view, the computer cannot be considered in isolation; the correct functioning of the embedded system is synonymous with the correct functioning of the device.

The design and programming of embedded systems is a fruitful area of exploration, for hobbyists and for students of Computer Science alike, but it also entails several unique challenges. Memory and processing power are often severely limited, and because embedded systems must provide uninterrupted long-term operation with little to no hands-on maintenance or intervention, correctness and predictability are essential. These challenges can add to one’s appreciation of the skills required, and acquiring those skills can also enlighten one’s exploration of more conventional computers. Since most computers in the world are embedded systems, relied upon by an increasing number of occupations, the exploration of embedded systems is also a worthwhile career investment. It is also an exciting and engaging way to learn about the fundamentals of computer architecture and good programming practices, while solving a range of interesting problems and working hands-on with an interesting range of platforms.

This tutorial introduces the fundamental concepts and ideals of embedded systems. After establishing the necessary background, it will proceed to introduce embedded systems programming through a variety of hands-on exercises with major embedded system platforms. It will begin with small-scale embedded systems based on microcontrollers, and their respective development tools. The microcontroller platforms introduced will be the MCS-51 family of microcontrollers, which have long been widely used in educational applications, as well as the Arduino, a popular family of consumer-oriented microcontroller kits. It will conclude with an introduction to single-board computers, with an emphasis on the Raspberry Pi.

Keywords:
Embedded Systems, C, Firmware, Microcontrollers, Single-Board Computers, MCS-51, 8051, AVR, Arduino, Raspberry Pi, Linux

Covered Topics:
The covered topics include:

  • The concepts and ideals of embedded systems
  • The role of cross-compilers, cross-assemblers, and linkers
  • Using Integrated Development Environments (IDEs) for embedded systems
  • The workflow of compiling and downloading firmware for embedded systems
  • Embedded systems monitoring and troubleshooting using in-circuit debugging
  • Communication for embedded systems, including serial and network communications

Prerequisites for Participants:
Ideally, the audience should have a basic knowledge of programming languages such as C and Python.


Broadening CI Workforce Development for Quantum-Based Machine Learning Research in Science and Engineering

Presenter: Dan Lo and Yong Shi (Kennesaw State University – USA)
Type of Event: Workshop
Date: Saturday, April 25, 2026
Time: 08:45-12:00 (Central Time)
Duration: 3 hours
Room: Room 154

Abstract:
Quantum computing and artificial intelligence are advancing rapidly, with the potential to transform science, engineering, and industry. However, preparing a workforce capable of integrating quantum principles with modern machine learning remains a major challenge. Existing educational resources often lack accessible, hands-on materials that connect abstract quantum concepts with practical algorithm development. As more science and engineering (S&E) fields adopt quantum machine learning (QML), there is a growing need for a unified, community-driven training program.

This workshop introduces our developed QML learning materials, providing participants with both foundational knowledge and hands-on experience. Learners can continue through self-paced modules on a free, open-source platform covering topics across computer science, civil and environmental engineering, industrial engineering, physics, and related fields. All materials are available at our project website.

Supported in part by the National Science Foundation, this project addresses workforce needs through scalable hands-on modules, diverse training events, sustainable curriculum integration, and an open educational resource repository, including a forthcoming book for long-term impact.

Keywords:
CI Contributors and CI Users, Open Source, Quantum Machine Learning (QML), Science and Engineering Research Fields, Curriculum Enhancement, Multi-faceted Training Events

Covered Topics:
The covered topics include:

  • Quantum Support Vector Machine
  • Quantum Neural Network

Prerequisites for Participants:
Basic Python programming skill.