Demo 5: Demo Season 2
The fifth demo in the second season of the series.
Posts by Collection
demos
Demo 1: Secure AI Prototype 20252025
A demo of secure AI systems.
Talk 1: PeymanNajafirad/_talks/2025-03-23-demo-1.md
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Interactive Data Visualization Demo
A demo showcasing real-time data visualization tools.
Demos
Demo 1: DigitalTwinUI
Explore the core principles and applications of AI agentic systems in the DigitalTwinUI.
Demo 2: Conceptual Guide: Multi Agent Architectures
A walkthrough of different multi-agent system designs and their use cases.
portfolio
Day One Hugging Face
Day One: Hugging Face, Vision Language Models and Event Instruct & Instruction Tuning
Instructor: Emet Bethany
Agentic Workshop Day 1
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
publications
Das, Arun, Jeffrey Mock, Yufei Huang, Edward Golob, and Peyman Najafirad. Interpretable self-supervised facial micro-expression learning to predict cognitive state and neurological disorders. In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, no. 1, pp. 818-826. 2021.
Bendre, Nihar, Kevin Desai, and Peyman Najafirad. Generalized zero-shot learning using multimodal variational auto-encoder with semantic concepts. In 2021 IEEE International Conference on Image Processing (ICIP), pp. 1284-1288. IEEE, 2021.
De La Torre Parra, Gonzalo, Luis Selvera, Joseph Khoury, Hector Irizarry, Elias Bou-Harb, and Paul Rad. Interpretable federated transformer log learning for cloud threat forensics. NDSS 22 (2022)
De La Torre Parra, Gonzalo, Luis Selvera, Joseph Khoury, Hector Irizarry, Elias Bou-Harb, and Paul Rad. Interpretable federated transformer log learning for cloud threat forensics. NDSS 22 (2022).
Silva, Samuel Henrique, Arun Das, Adel Aladdini, and Peyman Najafirad. Adaptive clustering of robust semantic representations for adversarial image purification on social networks. In Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 968-979. 2022.
Ebadi, Nima, Ruiqi Li, Arun Das, Arkajyoti Roy, Papanikolaou Nikos, and Peyman Najafirad. CBCT-guided adaptive radiotherapy using self-supervised sequential domain adaptation with uncertainty estimation. Medical Image Analysis 86 (2023): 102800.
Islam, Nafis Tanveer, Gonzalo De La Torre Parra, Dylan Manuel, Elias Bou-Harb, and Peyman Najafirad. An unbiased transformer source code learning with semantic vulnerability graph. In 2023 IEEE 8th European Symposium on Security and Privacy (EuroS&P), pp. 144-159. IEEE, 2023.
Islam, Nafis Tanveer, Gonzalo De La Torre Parra, Dylan Manuel, Elias Bou-Harb, and Peyman Najafirad. An unbiased transformer source code learning with semantic vulnerability graph. In 2023 IEEE 8th European Symposium on Security and Privacy (EuroS&P), pp. 144-159. IEEE, 2023.
Bethany, Mazal, Andrew Seong, Samuel Henrique Silva, Nicole Beebe, Nishant Vishwamitra, and Peyman Najafirad. “Towards targeted obfuscation of adversarial unsafe images using reconstruction and counterfactual super region attribution explainability.” In 32nd USENIX Security Symposium (USENIX Security 23), pp. 643-660. 2023.
Robinson, Caleb, Isaac Corley, Anthony Ortiz, Rahul Dodhia, Juan M. Lavista Ferres, and Peyman Najafirad. “Seeing the roads through the trees: A benchmark for modeling spatial dependencies with aerial imagery.” arXiv preprint arXiv:2401.06762 (2024).
Bethany, Mazal, Brandon Wherry, Emet Bethany, Nishant Vishwamitra, and Peyman Najafirad. Deciphering Textual Authenticity: A Generalized Strategy through the Lens of Large Language Semantics for Detecting Human vs. Machine-Generated Text. 33rd USENIX Security Symposium, 2024.
Bethany, Mazal, Brandon Wherry, Nishant Vishwamitra, and Peyman Najafirad. Image Safeguarding: Reasoning with Conditional Vision Language Model and Obfuscating Unsafe Content Counterfactually, 2024
Corley, Isaac, Caleb Robinson, Rahul Dodhia, Juan M. Lavista Ferres, and Peyman Najafirad. Revisiting pre-trained remote sensing model benchmarks: resizing and normalization matters. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 3162-3172. 2024.
Ebadi, Nima, Ruiqi Li, Arun Das, Arkajyoti Roy, Papanikolaou Nikos, and Peyman Najafirad. CBCT-guided adaptive radiotherapy using self-supervised sequential domain adaptation with uncertainty estimation. Medical Image Analysis 86 (2023): 102800.
Khoury, Joseph, Dorde Klisura, Hadi Zanddizari, Gonzalo De La Torre Parra, Peyman Najafirad, and Elias Bou-Harb. Jbeil: Temporal Graph-Based Inductive Learning to Infer Lateral Movement in Evolving Enterprise Networks. In 2024 IEEE Symposium on Security and Privacy (SP), pp. 9-9. IEEE Computer Society, 2023.
Wajid, Mohammad Saif, Hugo Terashima-Marin, Peyman Najafirad, Santiago Enrique Conant Pablos, and Mohd Anas Wajid. DTwin-TEC: An AI-based TEC District Digital Twin and Emulating Security Events by Leveraging Knowledge Graph. Journal of Open Innovation: Technology, Market, and Complexity (2024): 100297.
Islam, Nafis Tanveer, and Peyman Najafirad. Code Security Vulnerability Repair Using Reinforcement Learning with Large Language Models. Proceedings of the AAAI Conference on Artificial Intelligence Workshop, 2024.
Corley, Isaac, Jonathan Lwowski, and Peyman Najafirad. ZRG: A Dataset for Multimodal 3D Residential Rooftop Understanding. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp. 4635-4643. 2024.
talks
Talk 1: PeymanNajafirad/_talks/2024-06-09-talk-1.md
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Talk 2: PeymanNajafirad/_talks/2024-06-09-talk-2.md
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Talk 3: PeymanNajafirad/_talks/2024-06-09-talk-3.md
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Talk 4: PeymanNajafirad/_talks/2024-06-09-talk-4.md
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Talk 5: Talk Season 2 02/09/2025
This is a description of your talks Location: PeymanNajafirad/_talks/2025-01-01-talk-1.md
Workshop Talk
Presenters: Mazal Bethany, Emet Bethany, Mohammad Bahrami Karkevandi
We delivered a training workshop on multi-agent LLMs as part of international summer program at the School of Data Science (SDS) hosting 12 international students from June 24 to July 27 for the first annual SDS Summer Immersion Experience. The students, from two private Mexican universities- Tecnológico de Monterrey (TEC) and the Instituto Tecnológico Autónomo de México (ITAM)- spent a month in San Antonio assisting SDS core faculty with their research.
Day 1: High Performance Computing
This workshop covers the fundamentals of running jobs on UTSA’s ARC HPC systems that offer GPU computing capabilities to students. Attendees were introduced to networking, storage, job submission, and best practices for using common software with LLMs. With assistance from ARC’s administrative staff, students were given access to GPUs on ARC. During the workshop, attendees connected to ARC and ran commands to ensure everyone could access and use ARC. Utilizing GPU access, attendees participated in a hands-on assignment to fine-tune a small LLM, Microsoft Phi-2, on an instruction-based dataset.
Day 2: HuggingFace Workshop
This workshop covers leveraging the Hugging Face platform for machine learning tasks. Attendees learn the basics of getting started with Hugging Face, exploring the Model and Dataset Hub, and selecting appropriate models, particularly Large Language Models. The workshop includes fine-tuning techniques and provides code examples for loading models/datasets, creating training scripts, and utilizing other useful functions. Attendees also participate in a practical demonstration, creating a simple chatbot using an LLM (Llama3) from Hugging Face, complete with chat history functionality.
Talks & Presentation
- Information Coming Soon
teaching
2024-summer-teaching-2.md
ISCS 7053 Topics: LLM Agentic AI Systems, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Spring 2025.
CS 6263 Special Topics: NLP with Large Language Models, Graduate Course, Department of Computer Science, University of Texas at San Antonio, Spring 2024.
ISCS 7053 Topics: Adv. Secure AI/ML Research, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Fall 2023.
ISCS 7053 Topics: Adv. Secure AI/ML Research, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Fall 2022.
CS 6243 Machine Learning, Graduate Course, Department of Computer Science, University of Texas at San Antonio, Fall 2022.
CS 4843 Cloud Computing, Undergraduate Course, Department of Computer Science, University of Texas at San Antonio, Spring 2022.
CS 5573 Cloud Computing, Graduate Course, Department of Computer Science, University of Texas at San Antonio, Spring 2022.
CS 3793 Artificial Intelligence, Undergraduate Course, Department of Computer Science, University of Texas at San Antonio, Fall 2021.
CS 5233 Artificial Intelligence, Graduate Course, Department of Computer Science, University of Texas at San Antonio, Fall 2021.
ISCS 7033 Topics: AI/ML Research, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Fall 2021.
CS 1714 Computer Programming II, Undergraduate Course, Department of Computer Science, University of Texas at San Antonio, Spring 2021.
ISCS 7033 Topics: AI/ML Research, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Fall 2020.
ISCS 7033 Topics: AI/ML Research, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Spring 2020.
ISCS 7033 Topics: AI/ML Research, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Fall 2019.
ISCS 7033 Topics: AI/ML Research, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Spring 2019.
ISCS 6733 Big Data Technology, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Spring 2019.
ISCS 6733 Big Data Technology, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Fall 2018.
ISCS 6733 Big Data Technology, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Spring 2018.
ISCS 6733 Big Data Technology, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Fall 2017.
ECE 6973 Special Topic: Machine Learning/BigData, Graduate Course, Department of Electrical and Computer Engineering, University of Texas at San Antonio, Fall 2017.
ECE 6973 Special Topic: Machine Learning/BigData, Graduate Course, Department of Electrical and Computer Engineering, University of Texas at San Antonio, Spring 2017.
ECE 6973 Special Topic: Machine Learning/BigData, Graduate Course, Department of Electrical and Computer Engineering, University of Texas at San Antonio, Fall 2016.
Courses Taught
ISCS 7053 Topics: LLM Agentic AI Systems, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Spring 2025.
CS 6263 Special Topics: NLP with Large Language Models, Graduate Course, Department of Computer Science, University of Texas at San Antonio, Spring 2024.
ISCS 7053 Topics: Adv. Secure AI/ML Research, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Fall 2023.
ISCS 7053 Topics: Adv. Secure AI/ML Research, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Fall 2022.
CS 6243 Machine Learning, Graduate Course, Department of Computer Science, University of Texas at San Antonio, Fall 2022.
CS 4843 Cloud Computing, Undergraduate Course, Department of Computer Science, University of Texas at San Antonio, Spring 2022.
CS 5573 Cloud Computing, Graduate Course, Department of Computer Science, University of Texas at San Antonio, Spring 2022.
CS 3793 Artificial Intelligence, Undergraduate Course, Department of Computer Science, University of Texas at San Antonio, Fall 2021.
CS 5233 Artificial Intelligence, Graduate Course, Department of Computer Science, University of Texas at San Antonio, Fall 2021.
ISCS 7033 Topics: AI/ML Research, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Fall 2021.
CS 1714 Computer Programming II, Undergraduate Course, Department of Computer Science, University of Texas at San Antonio, Spring 2021.
ISCS 7033 Topics: AI/ML Research, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Fall 2020.
ISCS 7033 Topics: AI/ML Research, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Spring 2020.
ISCS 7033 Topics: AI/ML Research, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Fall 2019.
ISCS 7033 Topics: AI/ML Research, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Spring 2019.
ISCS 6733 Big Data Technology, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Spring 2019.
ISCS 6733 Big Data Technology, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Fall 2018.
ISCS 6733 Big Data Technology, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Spring 2018.
ISCS 6733 Big Data Technology, Graduate Course, Department of Information Systems and Cyber Security, University of Texas at San Antonio, Fall 2017.
ECE 6973 Special Topic: Machine Learning/BigData, Graduate Course, Department of Electrical and Computer Engineering, University of Texas at San Antonio, Fall 2017.
ECE 6973 Special Topic: Machine Learning/BigData, Graduate Course, Department of Electrical and Computer Engineering, University of Texas at San Antonio, Spring 2017.
ECE 6973 Special Topic: Machine Learning/BigData, Graduate Course, Department of Electrical and Computer Engineering, University of Texas at San Antonio, Fall 2016.