Research

Research Interests

Computer Vision, Machine (Deep) learning and Artificial Intelligence.

Current Research Focus

Probabilistic Graphical Models, tractable probabilistic modeling, integrating probabilistic graphical models and deep learning for computer vision tasks, neuro-symbolic AI.

Inference within Probabilistic Models
Neural Network-Based Inference for Probabilistic Graphical Models

  • Neural Network Approximators for Marginal MAP Inference (AAAI’24)

  • Learning to Solve the Constrained Most Probable Explanation Task (AISTATS’24)

Optimization based Inference Schemes for Graphical Models
  • Deep Dependency Networks and Advanced Inference Schemes for Multi-Label Classification (AISTATS’24)
Activity Recognition and Video Understanding

  • CaptainCook4D Dataset (DMLR’23)

  • Explainable Activity Recognition (TiiS’23)

  • Predictive Task Guidance in Augmented Reality (Poster at IEEE VR’24)

Multi-Label Classification
  • Kernelized Random Vector Functional Link Network (IJCNN’20)