• M. Smith, L. Zhao, J. Cordova, X.-F. Jiang, and M. Ebrahimi, "Machine Learning-based Energy-efficient Workload Management for Data Centers". 2024 IEEE Consumer Communications & Networking Conference (IEEE CCNC 2024), Las Vegas, NV, USA, 2024. (In press)
  • M. Smith, L. Zhao, J. Cordova, X.-F. Jiang, and M. Ebrahimi, "Energy-efficient GPU-intensive Workload Scheduling for Data Centers". 2023 Symposium for Undergraduate Research in Data Science, Systems, and Security (REU Symposium 2023), Special Session at the 22nd International Conference on Machine Learning and Applications (ICMLA 2023), Jacksonville, Florida, 2023. (In Press)
  • Mohammad Zarak Shah Ji, and Mahdi Ebrahimi, "Predictive Modeling of Diabetes Onset and Survival Analysis," in Proc. of the the 21st International Conference on Scientific Computing (CSC), Las Vegas, Nevada, USA, 2023.
  • Mahdi Ebrahimi, Seyed Ziae Mousavi Mojab, and Najmeh Najmi, "CDAP: A Cultural Algorithm for Data Placement in Big Data Workflows," in Proc. of the the 2022 International Conference on Computational Science and Computational Intelligence (CSCI), pp. 629-634, Las Vegas, Nevada, USA, 2022. Download
  • Kyle Astudillo, Mahdi Ebrahimi, and Adam Kaplan, "Multi-user Searchable Attribute Based Encryption for Outsourced Big Data," in Proc. of the the 2022 International Conference on Computational Science and Computational Intelligence (CSCI), pp. 708-713, Las Vegas, Nevada, USA, 2022. Download
  • Elham Jahanpeikar, and Mahdi Ebrahimi, "Accuracy Analysis of Supervised and Unsupervised Techniques on Breast Cancer Datasets," in Proc. of the the 2022 International Conference on Computational Science and Computational Intelligence (CSCI), pp. 356-361, Las Vegas, Nevada, USA, 2022. Download
  • Seyed Ziae Mousavi Mojab, Mahdi Ebrahimi, Shiyong Lu, and Robert Reynolds, "iCATS: Big Data Workflow Scheduling in the Cloud Using Cultural Algorithms," in Proc. of the Fifth IEEE International Conference On Big Data Service And Applications (BigDataService), pp. 99-106, Newark, California, USA, 2019. Download
  • Darrell M. Wilson, Patrick Nelson, David Scheinker, Susan Pietropaolo, Maria Acevedo-Calado, Mahdi Ebrahimi, Andrea Steck, Jessica L. Dunne, Carla Greenbaum, and Massimo Pietropaolo, "898-P: CGM Metrics Identify Dysglycemic States in Subjects with Normal OGTT from the TrialNet Pathway to Prevention Study," Diabetes 1 June 2019.
  • Mahdi Ebrahimi, Aravind Mohan, and Shiyong Lu, "Scheduling Big Data Workflows in the Cloud under Deadline Constraints," in Proc. of the IEEE International Conference on Big Data Computing Service and Applications (BigDataService), pp. 33-40, Bamberg, Germany, 2018. Download
  • Aravind Mohan, Mahdi Ebrahimi, Shiyong Lu, and Alexander Kotov, "Scheduling Big Data Workflows in the Cloud under Budget Constraints," in Proc. of the IEEE Scalable Cloud Data Management Workshop, in conjunction with the IEEE Conference on Big Data, pp. 2775-2784, Washington DC, USA, 2016. Download
  • Aravind Mohan, Mahdi Ebrahimi, Shiyong Lu, and Alexander Kotov, "A NoSQL Data Model for Scalable Big Data Workflow Execution," in Proc. of the IEEE International Congress on Big Data, pp. 52-59, San Francisco, California, USA, 2016. Download
  • Mahdi Ebrahimi, Aravind Mohan, Andrey Kashlev, Shiyong Lu, and Robert Reynolds, "Task and Data Allocation Strategies for Big Data Workflows," in Proc. of the International Journal of Big Data (IJBD), pp. 28-42, 2(2), 2015. Download
  • Mahdi Ebrahimi, Aravind Mohan, Shiyong Lu, and Robert Reynolds, "TPS: A Task Placement Strategy for Big Data Workflows," in Proc. of the 2015 IEEE International Conference on Big Data (BigData), pp. 523-530, Santa Clara, CA, USA, 2015. Download
  • Mahdi Ebrahimi, Aravind Mohan, Shiyong Lu, Andrey Kashlev, "BDAP: A Big Data Placement Strategy for Cloud-based Scientific Workflows," in Proc. of the IEEE International Conference on Big Data Computing Service and Applications (BigDataService), pp. 105-114, San Francisco, California, USA, 2015. Download
  • Aravind Mohan, Mahdi Ebrahimi, Shiyong Lu, "A Folksonomy-Based Social Recommendation System for Scientific Workflow Reuse," in Proc. of the IEEE International Conference on Services Computing (SCC), pp. 704-711, New York, USA, 2015. Download
Ph.D. Dissertation:
  • Mahdi Ebrahimi, "Data Placement and Task Mapping Optimization for Big Data Workflows in the Cloud" (2017). Wayne State University Dissertations. 1799. Download
Presentation:
  • Mahdi Ebrahimi, Seyed Ziae Mousavi, Aravind Mohan, Shiyong Lu, and Robert Reynolds, "CATS: Scheduling Big Data Workflows in the Cloud Using Cultural Algorithms". 4th Big Data & Business Analytics Symposium @ WSU, Detroit, 2017.
  • Saeid Mofrad, Mahdi Ebrahimi, Fengwei Zhang, and Shiyong Lu, "Securing Big Data Workflows in the Cloud via Intel Software Guard Extensions". 4th Big Data & Business Analytics Symposium @ WSU, Detroit, 2017.
  • Mahdi Ebrahimi, Aravind Mohan, and Shiyong Lu, "An Efficient Big Data Placement Strategy in Cloud-based Big Data Workflows". 7th MidWest Graduate Research Symposium @ University of Toledo, Toledo, 2016.
  • Mahdi Ebrahimi, Aravind Mohan, Andrey Kashlev, Shiyong Lu and Robert Reynolds, "An efficient task and data placement strategy for running cloud-based big data workflows". 2nd SOCIETY 2030 @ University of Michigan, Ann Arbor, 2016.
  • Aravind Mohan, Mahdi Ebrahimi, and Shiyong Lu, "A NoSQL Data Model for Running Big Data Workflows in the Cloud". 7th MidWest Graduate Research Symposium @ University of Toledo, Toledo, 2016.
  • Mahdi Ebrahimi, Aravind Mohan, Andrey Kashlev, Shiyong Lu, and Robert Reynolds, "An efficient task and data placement strategy for running cloud-based big data workflows". 3rd Big Data & Business Analytics Symposium @ WSU, Detroit, 2016.
  • Aravind Mohan, Mahdi Ebrahimi, and Shiyong Lu, "A Big Data Platform for running workflows in the Cloud." 3rd Big Data & Business Analytics Symposium @ WSU, Detroit, 2016.