Students

PhD

  1. George Stone (expected Fall 2023)
  2. Prabin Lamichhane (expected Fall 2022)
  3. Jeffrey Graves (expected Fall 2022)
  4. Sheikh Rabiul Islam, “DOMAIN KNOWLEDGE AIDED EXPLAINABLE ARTIFICIAL INTELLIGENCE”, Spring 2020. Currently an Assistant Professor position at University of Hartford, Connecticut.
  5. Ramesh Paudel, “EFFICIENT GRAPH KNOWLEDGE DISCOVERY ON GRAPH STREAMS WITH CONCEPT DRIFT”, Spring 2020. Currently a Post-Doc at George Washington University, Washington, D.C.
  6. Sirisha Velampalli (Jawaharlal Nehru Technological University), “Novel Graph Based Approaches for Finding Interesting Substructures in Heterogeneous Networks”. Spring 2018. Currently a Currently a Machine Learning Research Engineer at DataOrb AI.
  7. Lenin Mookiah, “Personalized Context Mining of News Streams Using Graph-Based Approaches”, Summer 2017. Currently a Machine Learning and Software Engineer for eBay (California).

 Masters

  1. Matthew Brotherton, Fall 2023.
  2. Allison (Baylee) Jones, Spring 2022.
  3. Prajjwal Kandal, “NODE SIMILARITY FOR ANOMALY DETECTION IN ATTRIBUTED GRAPHS”, Spring 2019.
  4. Niraj Rajbhandari, “GRAPH SAMPLING TO DETECT ANOMALIES IN LARGE GRAPHS AND DYNAMIC GRAPH STREAMS”, Spring 2018.
  5. Sheikh Rabiul Islam, “AN EFFICIENT TECHNIQUE FOR MINING BAD CREDIT ACCOUNTS FROM BOTH OLAP AND OLTP”, Spring 2018.
  6. Raduanul Islam, “Canonical labelling to Improve Compression Approach to Graph Matching”, Spring 2017.
  7. Rupak Dhunaga, “Real-Time Visualization of Graph Streams”, Spring 2016.
  8. Jamie Terral, “Exploring Regular Expression-Based Variable-Width Intelligent Part Number Component Translation for Purposes of Engineering Design Knowledge Transfer and Manufacturing Execution Automation”, Spring 2016.
  9. Alan McCormick, “Detecting Fraud in Online Classified Ads”, May 2014.
  10. Ramesh Paudel, “Linkcube: A Tool for Anomaly Detection in Social Networks Using GBAD”, May 2014.
  11. Jeffrey Graves, “Source Code Plagiarism Detection Using a Graph Based Approach”, July 2011.