News

  • Sep-21: Preprint introduced by Import AI! — Self-supervised Representation Learning for Reliable Robotic Monitoring of Fruit Anomalies.

  • Jul-21: New paper accepted to ECMR2021! — Adaptive Selection of Informative Path Planning Strategies via Reinforcement Learning.

  • Jun-21: Best Paper Award received at SWARM2021 for the presented paper! — Beyond Tracking: Using Deep Learning to Discover Novel Interactions in Biological Swarms.

  • Mar-21: New paper accepted to SWARM2021! — Beyond Tracking: Using Deep Learning to Discover Novel Interactions in Biological Swarms.

  • Nov-20: New paper accepted to IAAI2021! — Identification of Abnormal States in Videos of Ants Undergoing Social Phase Change.

  • Nov-20: PhD dissertation defended successfully! — Deep Learning Approaches for Inferring Collective Macrostates from Individual Observations in Natural and Artificial Multi-Agent Systems Under Realistic Constraints.

  • Oct-20: New position started as a Postdoctoral Research Associate at University of Lincoln in UK!

  • Aug-20: New paper accepted to MFI2020! — Automatic Discovery of Motion Patterns that Improve Learning Rate in Communication-Limited Multi-Robot Systems.

  • Jun-20: New paper accepted to ACSOS2020! — How Far Should IWatch? Quantifying the Effect of Various Observational Capabilities on Long-range Situational Awareness in Multi-robot Teams.

  • May-20: Engineering Graduate Fellowship awarded from ASU Ira A. Fulton Schools of Engineering!

  • Apr-20: Completion Fellowship awarded from ASU Graduate College for supporting the successful completion of my PhD dissertation!

  • Mar-20: Doctoral Fellowship awarded from ASU School of Computing, Informatics, and Decision Systems Engineering!

  • Feb-20: Invitation to Collective Information Processing Workshop in Berlin, Germany on March 4-6th, 2020 to talk about “Automated Local Behavior Learning for Social Temperature Prediction without Individual Ant Tracking”!

  • Jan-20: New paper accepted to ICRA2020! — Learning Local Behavioral Sequences to Better Infer Non-local Properties in Real Multi-robot Systems.