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Publications

Jahnavi Methukumalli, Shivani Sharma, Aditi Prasad, Manasvi Aggarwal, Rupam Kumawat, Suhas Powar, Yatin Katyal, and Sahil Manchanda “𝗥𝗼𝗯𝘂𝘀𝘁 𝗮𝗻𝗱 𝗦𝗰𝗮𝗹𝗮𝗯𝗹𝗲 𝗠𝗲𝗿𝗰𝗵𝗮𝗻𝘁 𝗙𝗿𝗮𝘂𝗱 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 𝘃𝗶𝗮 𝗦𝘂𝗿𝗿𝗼𝗴𝗮𝘁𝗲-𝗚𝘂𝗶𝗱𝗲𝗱 𝗡𝗲𝗶𝗴𝗵𝗯𝗼𝗿 𝗦𝗲𝗹𝗲𝗰𝘁𝗶𝗼𝗻”, CIKM 2026 Applied Research - Full Paper

Saurav Sudevan, Harsh Pal, Yatin Katyal, and Sahil Manchanda “Uncovering Currency Bias and Syntax Gap in Text-embedding model”, Findings of ACL 2026, ACL Findings 2026

Sahil Manchanda and Pannaga Shivaswamy, “What is in a name? Mitigating Name Bias in Text Embeddings via Anonymization”, ACL Findings 2025

Sahil Manchanda, Dana Kianfar, Markus Peschl, Romain Lepert, Michaël Defferrard, “NeuroSteiner: A Graph Transformer for Wirelength Estimation”, in AAAI, 2025 Workshop of AI to accelerate Science.

Rishi Rajesh Shah*, Krishnanshu Jain*, Sahil Manchanda*, Sourav Medya and Sayan Ranu, “NeuroCut: A Neural Approach for Robust Graph Partitioning”, in KDD, 2024.(*Joint authorship) “Video”

Mridul Gupta*, Sahil Manchanda*, Hariprasad Kodamana and Sayan Ranu, “Mirage: Model-agnostic Graph Distillation for Graph Classification”, in ICLR, 2024.(*Joint authorship)

Sahil Manchanda*, Shubham Gupta*, Sayan Ranu and Srikanta Bedathur “Generative Modeling of Labeled Graphs under Data Scarcity” in LOG 2023. (*Joint authorship)

Shubham Gupta*, Sahil Manchanda*, Sayan Ranu and Srikanta Bedathur “GRAFENNE: Continual learning on Graphs with Heterogeneous and Dynamic Feature Sets” in ICML 2023. (*Joint authorship)

Vaibhav Bihani, Sahil Manchanda, Srikant Sastry, Sayan Ranu and Anoop Krishnan “StriderNet: A Graph Reinforcement Learning Approach to Optimize Atomic Structures on Rough Energy Landscapes” ICML 2023.

Sahil Manchanda and Sayan Ranu “Lifelong Learning to solve Mixed Integer Programs”. in AAAI 2023.

Sahil Manchanda, Sofia Michel, Darko Drakulic, Jean-Marc Andreoli “On the Generalization of Neural Combinatorial Optimization Heuristics” , ECML-PKDD 2022.

Shubham Gupta, Sahil Manchanda, Srikanta Bedathur and Sayan Ranu, “TIGGER: Scalable Generative Modelling for Temporal Interaction Graphs”, in AAAI 2022

Jayant Jain, Vrittika Bagadia, Sahil Manchanda and Sayan Ranu, “NeuroMLR: Robust & Reliable Route Recommendation on Road Networks” , in NeurIPS, 2021.

Sahil Manchanda, Akash Mittal, Anuj Dhawan, Sourav Medya, Sayan Ranu, and Ambuj Singh “GCOMB: Learning Budget-constrained Combinatorial Algorithms over Billion-sized Graphs”, in NeurIPS, 2020.

Sahil Manchanda and Ashish Anand “Representation Learning of Drug and Disease Terms for Drug Repositioning” - 3rd IEEE International Conference on Cybernetics, 2017.

Patent

1. Trained Pattern Analyzer for Rollout Decisions” USPTO.
   Inventors: Sahil Manchanda, Arun Rajkumar, Simarjot Kaur and Narayanan Unny.
   Status : Granted 2022: USPTO