Research Interests

His research interests lie in Data Science, Personalizations, Recommender Systems, Context-Awareness, Human Factors, Technology-Enhanced Learning, and so forth. It could be related to the following topics:

  • General Areas: Data Science, Machine Learning, Artificial Intelligence
  • Web & Learning Intelligence: Personalization, Recommender Systems, Learning Analytics
  • HCI and Users: User Modeling, Human Factors (trust, emotion, personality), Behavior Analysis
Grants
Projects & Supervisions

Below is a list of students or researchers under his supervision

  • List of PhD Students
    • Diego Sánchez-Moreno (Part-time PhD Student; University of Salamanca, Spain); Project: Music Recommender Systems
  • List of Master Students
    • Recommender Systems
      • Maria Delgado Franco, Mili Singh, Mayur Agnani; Project: Grey Sheep Users In RecSys
      • Tanaya Dave, Neha Mishra, Harshit Kumar; Project: Reciprocal Recommendations
      • Shephalika Shekhar; Project: Multi-Criteria Recommender System
      • Shravan Shankar Polisetty, Alisha Anna Jose; Project: Context-Aware Recommender System
      • Nastaran Ghane, Milad Sabouri; Project: Multi-Stakeholder Recommendations
      • Archana Subramaniyan; Project: Personality-Aware Recommendations
      • student pending; Project: Transparency and Fairness
    • Cybersecurity
      • Raquel Noblejas Sampedro, Sridhar Srinivasan, Kim Taehun; Project: Mobile Security
  • Students and Careers
    • Archana Subramaniyan, Zurich North America
    • Sridhar Srinivasan, DXC Technology
    • Shravan Shankar Polisetty, Google, Inc
    • Diego Sánchez-Moreno, Shotfarm, LLC
    • Mayur Agnani, MathWorks
Data Sets for Recommender Systems
Open Source Recommender Engines
  • Apache Mahout, Java-based library, especially for scalable data mining.
  • MyMediaLite, .Net-based library, specifically for recommender systems.
  • LensKit, Java-based recsys engine with classical recsys algorithms.
  • LibFM, a library for Factorization Machines
  • JavaFM, Java 8 Factorisation Machines Library
  • PITF, for tag recommendations
  • RankSys: Java 8 RecSys framework for novelty, diversity and much more
  • LibRec, Java-based library which implements the state-of-the-art recsys algorithms.
  • CARSKit, Java-based library for context-aware recommendations.