Representation Learning of Drug and Disease Terms for Drug Repositioning. - Sahil Manchanda; Ashish Anand (CYBCONF, 2017)

Learning Heuristics over Large Graphs via Deep Reinforcement Learning. - Sahil Manchanda; Akash Mittal; Anuj Dhawan; Sourav Medya; Sayan Ranu; Ambuj K. Singh (CoRR, 2019)

Domain Informed Neural Machine Translation: Developing Translation Services for Healthcare Enterprise. - Sahil Manchanda; Galina Grunin (EAMT, 2020)

GCOMB: Learning Budget-constrained Combinatorial Algorithms over Billion-sized Graphs. - Sahil Manchanda; Akash Mittal; Anuj Dhawan; Sourav Medya; Sayan Ranu; Ambuj K. Singh (NeurIPS, 2020)

SUPAID: A Rule mining based method for automatic rollout decision aid for supervisors in fleet management systems. - Sahil Manchanda; Arun Rajkumar; Simarjot Kaur; Narayanan Unny (CoRR, 2020)

Optum at MEDIQA 2021: Abstractive Summarization of Radiology Reports using simple BART Finetuning. - Ravi Kondadadi; Sahil Manchanda; Jason Ngo; Ronan McCormack (BioNLP@NAACL-HLT, 2021)

NeuroMLR: Robust & Reliable Route Recommendation on Road Networks. - Jayant Jain; Vrittika Bagadia; Sahil Manchanda; Sayan Ranu (NeurIPS, 2021)

TIGGER: Scalable Generative Modelling for Temporal Interaction Graphs. - Shubham Gupta; Sahil Manchanda; Srikanta Bedathur; Sayan Ranu (AAAI, 2022)

On the Generalization of Neural Combinatorial Optimization Heuristics. - Sahil Manchanda; Sofia Michel; Darko Drakulic; Jean-Marc Andreoli (ECML/PKDD (5), 2022)

Optum's Submission to WMT22 Biomedical Translation Tasks. - Sahil Manchanda; Saurabh Bhagwat (WMT, 2022)

Lifelong Learning for Neural powered Mixed Integer Programming. - Sahil Manchanda; Sayan Ranu (CoRR, 2022)

LIMIP: Lifelong Learning to Solve Mixed Integer Programs. - Sahil Manchanda; Sayan Ranu (AAAI, 2023)

StriderNet: A Graph Reinforcement Learning Approach to Optimize Atomic Structures on Rough Energy Landscapes. - Vaibhav Bihani; Sahil Manchanda; Srikanth Sastry; Sayan Ranu; N. M. Anoop Krishnan (ICML, 2023)

GRAFENNE: Learning on Graphs with Heterogeneous and Dynamic Feature Sets. - Shubham Gupta; Sahil Manchanda; Sayan Ranu; Srikanta J. Bedathur (ICML, 2023)

Generative Modeling of Labeled Graphs Under Data Scarcity. - Sahil Manchanda; Shubham Gupta; Sayan Ranu; Srikanta J. Bedathur (LoG, 2023)

GSHOT: Few-shot Generative Modeling of Labeled Graphs. - Sahil Manchanda; Shubham Gupta; Sayan Ranu; Srikanta Bedathur (CoRR, 2023)

Mirage: Model-agnostic Graph Distillation for Graph Classification. - Mridul Gupta; Sahil Manchanda; Hariprasad Kodamana; Sayan Ranu (ICLR, 2024)

NeuroCut: A Neural Approach for Robust Graph Partitioning. - Rishi Shah; Krishnanshu Jain; Sahil Manchanda; Sourav Medya; Sayan Ranu (KDD, 2024)

NeuroSteiner: A Graph Transformer for Wirelength Estimation. - Sahil Manchanda; Dana Kianfar; Markus Peschl; Romain Lepert; Michaël Defferrard (CoRR, 2024)

What is in a name? Mitigating Name Bias in Text Embedding Similarity via Anonymization. - Sahil Manchanda; Pannaga Shivaswamy (ACL (Findings), 2025)

What is in a name? Mitigating Name Bias in Text Embeddings via Anonymization. - Sahil Manchanda; Pannaga Shivaswamy (CoRR, 2025)