Sahil Sidheekh
CS PhD Student | AI/ML Researcher
PhD Student
Department of Computer Science
📍 ECSS 3.214
Erik Jonsson School of Engineering
& Computer Science, UTD
About Me
Research Interests
Probabilistic Generative Models
Neuro-Symbolic AI
Tractable Inference
Trustworthy AI
Meta-learning
Recent News
View all →Our paper "Tractable Representation Learning with Probabilistic Circuits" has been accepted to TMLR!
Excited to announce that "Tractable Sharpness-Aware Learning of Probabilistic Circuits" has been accepted to AAAI 2026!
Excited to share that I'll be joining Altir as an AI Intern in Fall 2025! I'll be working on building the MVP for a knowledge-driven enterprise AI solution.
Our paper on Scalable Knowledge Graph Construction from Unstructured Text has been accepted to PAKDD 2025!
Two papers accepted to AAAI 2025! Our work on "A Unified Framework for Human-Allied Learning of Probabilistic Circuits" and "Human-in-the-loop or AI-in-the-loop? Automate or Collaborate?" explore fundamental questions in human-AI collaboration.
Featured Publications
View all →
Tractable Sharpness-Aware Learning of Probabilistic Circuits
AAAI '26H Suresh, Sahil Sidheekh, S Natarajan, NC Krishnan
Credibility-aware multi-modal fusion using probabilistic circuits
AISTATS '25Sahil Sidheekh, P Tenali, S Mathur, E Blasch, K Kersting, S Natarajan
A Unified Framework for Human-Allied Learning of Probabilistic Circuits
AAAI '25Athresh Karanam, Saurabh Mathur, Sahil Sidheekh, Sriraam Natarajan
Building Expressive and Tractable Probabilistic Generative Models: A Review
IJCAI '24Sahil Sidheekh, S Natarajan
Probabilistic Flow Circuits: Towards Unified Deep Models for Tractable Probabilistic Inference
UAI '23Sahil Sidheekh, K Kersting, S Natarajan