"Praxis tendatum docebit." [Practice will teach those who try.]
— Carl Friedrich Gauß
I am a Machine Learning Engineer at ServiceNow (MLE-II) with expertise in AI and deep learning. I graduated with MS-Research from IIIT Hyderabad, specializing in Geometric Deep Learning, Temporal Graph Neural Networks, and Large Language Models. My work spans across federated learning, adversarial robustness, and scalable AI architectures. Read more about my research journey...
Temporal Graph Learning, Spectral Methods, Knowledge Graphs
Fine-tuning, Optimization, Multi-modal Integration
Federated Learning, Adversarial Robustness, Scalable Architectures
Novel framework combining spectral graph transformers with neural ODEs for federated learning on non-IID graphs.
✓ TMLR 2025 (Accepted)Innovative adversarial attack framework for Continuous Time Dynamic Graphs with minimal resources.
✓ AAAI 2025 (Accepted)Abstention mechanisms in dynamic graph learning for improved prediction reliability.
arXiv 2025Abstention-based approach to reduce misclassification risk in Dynamic Graph Neural Networks.
ASONAM 2025Reliability-driven approach for Temporal Graph Neural Networks with confidence-based predictions.
TGL Workshop @ KDD 2025Combining LLMs with GNNs for enhanced reasoning over graph-structured data.
✓ TDL 2024