Journals

• H. Homayouni, T. Kantilal Gada, H. Shirazi, S. Mehrotra, S. Ghosh, I. Ray, 2024. “Anomaly Detection in Time Series Data: A Comparative Evaluation of Methods”, submitted to ACM JDIQ.
• H. Homayouni, I. Ray, S. Ghosh, S. Gondalia, M. Kahn, 2021. “Anomaly Detection in COVID-19 Time-Series Data”, SN Computer Science, 2(4), pp.1-17.
• H. Homayouni, S. Ghosh, I. Ray, M. G. Kahn, 2021. “ADQuaTe2: A Data Quality Test Approach for Fault Detection and Explanation in Big Data”, submitted to The ACM Journal of Data and Information Quality.
• M.R. Keyvanpour, H. Homayouni, 2014. “Automatic Test Case Generation for Modern Web Applications Using Population-based Automatic Fuzzy Neural Network”, International Journal of Information and Communication Technology Research, Volume 6, No.2, pp. 29–40.
• M.R. Keyvanpour, H. Homayouni, and S. Zolfaghari, 2014. “Population-based Automatic Fuzzy Neural Network for Online, Knowledge-based Learning”, The Modares Journal of Electrical Engineering, Volume 14, Issue 3.
• M.R. Keyvanpour, H. Homayouni, and H. Shirazi, 2013. “A Classification Framework for Automatic Test Case Generation Techniques for web applications” International Journal of Information Processing and Management (IJIPM), volume 4, Issue 3.
• M.R. Keyvanpour, H. Homayouni and H. Shirazi, 2012. “Automatic Software Test Case Generation: An Analytical Classification Framework.” International Journal of Software Engineering and Its Applications, volume 6, No.4.
• M.R. Keyvanpour, H. Homayouni, and H. Shirazi, 2011. “Automatic Software Test Case Generation.” Journal of Software Engineering, Volume 5, Issue 3.

Book Chapter

• H. Homayouni, S. Ghosh, I. Ray, 2018. “Data Warehouse Testing”. Advances In Computers, Volume 112.

Conferences

• D. Rozenshteyn , H. Homayouni, 2024. “Gender Gap and Impact in Cardiovascular Research”, submitted as a full paper to the IEEE Healthcom.
• H. Homayouni, S. N. Dabhi, S. T. Nguyen, P. P. Badlania, M. Hashemib, H. Shirazi, 2024. “Towards Comprehensive Functional Testing in ETL Processes: A Classification Framework and Empirical Validation on a Real-World Data Warehouse”, 24th IEEE International Conference on Software Quality, Reliability, and Security (QRS).
• A. Jnaini, H. Shirazi, H. Homayouni, 2024. “Synergy of GPT-3 Summarization and Vision-Encoder-Decoder for Chest X-ray Captioning”,  IEEE Canadian Conference on Electrical and Computer Engineering (CCECE).
• H. Homayouni, M. Pourebadi, H. Shirazi, 2024. ”Poster: Federated Multimodal Medical Data Generation”, in the Network and Distributed System Security Symposium (NDSS).
• E. Navaro, H. Homayouni, 2023. “Topic Modeling in Cardiovascular Research Publications”, KDD-UC.
• S. Kaur, S. Justme, H. Homayouni 2023. “High-Resolution COVID-19 X-Ray Generator”, ACM HIKM, pp. 151–159
• G. Maurina, H. Homayouni, I. Ray, S. Ghosh, G. P. Duggan, 2022.“A Methodology for Energy Usage Prediction in Unforeseen Circumstances”, IEEE CogMI, pp. 91-100
• J. Cuomo, H. Homayouni, I. Ray, S. Ghosh, 2021. “Detecting Temporal Dependencies in Data”, British International Conference on Databases
• H. Homayouni, S. Ghosh, I. Ray, S. Gondalia, J. Duggan, M. Kahn, 2020. “An Autocorrelation-based LSTM-Autoencoder for Anomaly Detection on Time-Series Data”, IEEE Big Data at the Special Session: Machine Learning on Big Data, pp. 5068-5077
• Homayouni, S. Ghosh, I. Ray, M. Kahn, 2019. “An Interactive Data Quality Test Approach for Constraint Discovery and Fault Detection”, IEEE Big Data, pp. 200–205.
• H. Homayouni, S. Ghosh, I. Ray, 2019. “ADQuaTe: An Automated Data Quality Test Approach for Constraint Discovery and Fault Detection”, In IEEE 20th International Conference on Information Reuse and Integration for Data Science.
• H. Homayouni, 2018. “Testing Extract-Transform-Load Process in Data Warehouse Systems”. In Doctoral Symposium section of the 29th IEEE International Symposium on Software Reliability Engineering, Memphis, USA.
• H. Homayouni, S. Ghosh, I. Ray, 2018. “An Approach for Testing the Extract-Transform-Load Process in Data Warehouse Systems”. In 22nd International Database Engineering & Applications Symposium,  Villa San Giovanni, Italy, pp. 236–245. (Presentation file)

Presentations

• H. Homayouni, M. Porebadi, H. Shirazi, “Poster: Federated Multimodal Medical Data Generation”, 2024. Network and Distributed System Security (NDSS) (NDSS), San Diego
• H. Homayouni. “Generative Models for Synthetic Data Generation“, 2023. IEEE CIS Summer School, SMNIT Jaipur, India.
• H. Homayouni. “Synthetic COVID-19 Data Generation“, 2023. Computational Science Research Center (CSRC), San Diego State University.
• H. Homayouni. “Anomaly Detection and Explanation in Big Data”, 2021. Computational Science Research Center (CSRC), San Diego State University.
• H. Homayouni, S. Ghosh, I. Ray, 2020. “Anomaly Detection and Explanation in Big Data”, Rising Stars, UC Berkeley.
• H. Homayouni, S. Ghosh, I. Ray, 2020. “IDEAL: Interactive Detection and Explanation of Anomalies using Autocorrelation-based LSTM-Autoencoder for Time-Series Data”, virtual poster presentation at Rocky Mountain Advanced Computing Consortium (RMACC).
• H. Homayouni, S. Ghosh, I. Ray, 2019. “ADQuaTe: An Automated Interactive Data Quality Test Approach”, poster presentations at Graduate Show Case, Colorado State University, USA.
• H. Homayouni, S. Ghosh, I. Ray, 2019. “ADQuaTe: An Automated Interactive Data Quality Test Approach”, poster presentations at Grace Hopper Celebration of Women in Computing, USA
• H. Homayouni, S. Ghosh, I. Ray, 2019. “ADQuaTe: An Automated Interactive Data Quality Test Approach”, poster presentations at Tapia Celebration of Diversity in Computing, Sandiego, USA
• H. Homayouni, S. Ghosh, I. Ray, 2019. “ADQuaTe: An Automated Data Quality Test Approach for Constraint Discovery and Fault Detection”, poster presentation at Rocky Mountain Advanced Computing Consortium (RMACC).
• H. Homayouni, S. Ghosh, I. Ray, 2018. “Using Autoencoder to Generate Data Quality Tests”, paper presentation at Rocky Mountain Celebration of Women in Computing (RMCWIC), Denver, USA, November 2 – 3.
• H. Homayouni, S. Ghosh, 2016. “A study of Evosuite as an automatic test case generation approach to kill first order mutants”, paper presentation at Rocky Mountain Celebration of Women in Computing (RMCWIC), Salt Lake City, USA, September 22 – 23.