GraphSig: A Scalable Approach to Mining Significant Subgraphs in Large Graph Databases. - Sayan Ranu; Ambuj K. Singh (ICDE, 2009)

Mining Statistically Significant Molecular Substructures for Efficient Molecular Classification. - Sayan Ranu; Ambuj K. Singh (J. Chem. Inf. Model., 2009)

Novel Method for Pharmacophore Analysis by Examining the Joint Pharmacophore Space. - Sayan Ranu; Ambuj K. Singh (J. Chem. Inf. Model., 2011)

Answering Top-k Queries Over a Mixture of Attractive and Repulsive Dimensions. - Sayan Ranu; Ambuj K. Singh (Proc. VLDB Endow., 2011)

Indexing and mining topological patterns for drug discovery. - Sayan Ranu; Ambuj K. Singh (EDBT, 2012)

Recommendations to boost content spread in social networks. - Vineet Chaoji; Sayan Ranu; Rajeev Rastogi; Rushi Bhatt (WWW, 2012)

Trajectory Analytics: Indexing, Mining, and Applications to Network Optimization. - Sayan Ranu; Aditya Telang; Vinay Kolar (COMAD, 2013)

Mining discriminative subgraphs from global-state networks. - Sayan Ranu; Minh X. Hoang; Ambuj K. Singh (KDD, 2013)

Entity Linking: Detecting Entities within Text. - Deepak P 001; Sayan Ranu (COMAD, 2014)

People in motion: Spatio-temporal analytics on Call Detail Records. - Vinay Kolar; Sayan Ranu; Anand Prabhu Subramanian; Yedendra Shrinivasan; Aditya Telang; Ravi Kokku; Sriram Raghavan (COMSNETS, 2014)

Inferring Uncertain Trajectories from Partial Observations. - Prithu Banerjee; Sayan Ranu; Sriram Raghavan (ICDM, 2014)

Answering top-k representative queries on graph databases. - Sayan Ranu; Minh X. Hoang; Ambuj K. Singh (SIGMOD Conference, 2014)

Applications of Top-k Representative Queries. - Sayan Ranu; Minh X. Hoang; Ambuj K. Singh (SWIM, 2014)

Entity Linking for Web Search Queries. - Deepak P 001; Sayan Ranu; Prithu Banerjee; Sameep Mehta (ECIR, 2015)

Indexing and matching trajectories under inconsistent sampling rates. - Sayan Ranu; Deepak P 001; Aditya D. Telang; Prasad Deshpande; Sriram Raghavan (ICDE, 2015)

Geo-Social Clustering of Places from Check-in Data. - Shivam Srivastava; Shiladitya Pande; Sayan Ranu (ICDM, 2015)

Trajectory aware macro-cell planning for mobile users. - Shubhadip Mitra; Sayan Ranu; Vinay Kolar; Aditya Telang; Arnab Bhattacharya 001; Ravi Kokku; Sriram Raghavan (INFOCOM, 2015)

COMMIT: A Scalable Approach to Mining Communication Motifs from Dynamic Networks. - Saket Gurukar; Sayan Ranu; Balaraman Ravindran (SIGMOD Conference, 2015)

A Scalable and Generic Framework to Mine Top-k Representative Subgraph Patterns. - Dheepikaa Natarajan; Sayan Ranu (ICDM, 2016)

MANTRA: A Scalable Approach to Mining Temporally Anomalous Sub-trajectories. - Prithu Banerjee; Pranali Yawalkar; Sayan Ranu (KDD, 2016)

Select, Link and Rank: Diversified Query Expansion and Entity Ranking Using Wikipedia. - Adit Krishnan; Deepak Padmanabhan 001; Sayan Ranu; Sameep Mehta (WISE (1), 2016)

Big-Graphs: Querying, Mining, and Beyond. - Arijit Khan 001; Sayan Ranu (Handbook of Big Data Technologies, 2017)

A weight-based map matching algorithm using minimum input variables for urban road networks. - Souvik Maity; Soumik Dalal; Sayan Ranu; Lelitha Vanajakshi (COMSNETS, 2017)

NetClus: A Scalable Framework for Locating Top-K Sites for Placement of Trajectory-Aware Services. - Shubhadip Mitra; Priya Saraf; Richa Sharma; Arnab Bhattacharya 001; Sayan Ranu; Harsh Bhandari (ICDE, 2017)

Debunking the Myths of Influence Maximization: An In-Depth Benchmarking Study. - Akhil Arora 001; Sainyam Galhotra; Sayan Ranu (SIGMOD Conference, 2017)

Predicting novel metabolic pathways through subgraph mining. - Aravind Sankar; Sayan Ranu; Karthik Raman 002 (Bioinform., 2017)

SkyGraph: Retrieving Regions of Interest using Skyline Subgraph Queries. - Shiladitya Pande; Sayan Ranu; Arnab Bhattacharya 001 (Proc. VLDB Endow., 2017)

Mining bus stops from raw GPS data of bus trajectories. - Nandani Garg; Gitakrishnan Ramadurai; Sayan Ranu (COMSNETS, 2018)

Route Recommendations for Idle Taxi Drivers: Find Me the Shortest Route to a Customer! - Nandani Garg; Sayan Ranu (KDD, 2018)

Identifying User Intent and Context in Graph Queries. - Jithin Vachery; Akhil Arora 001; Sayan Ranu; Arnab Bhattacharya 001 (CoRR, 2018)

Resling: a scalable and generic framework to mine top-k representative subgraph patterns. - Dheepikaa Natarajan; Sayan Ranu (Knowl. Inf. Syst., 2018)

Noticeable Network Delay Minimization via Node Upgrades. - Sourav Medya; Jithin Vachery; Sayan Ranu; Ambuj K. Singh (Proc. VLDB Endow., 2018)

Leveraging semantic resources in diversified query expansion. - Adit Krishnan; Deepak P 001; Sayan Ranu; Sameep Mehta (World Wide Web, 2018)

NetClus: A Scalable Framework to Mine Top-K Locations for Placement of Trajectory-Aware Services. - Shubhadip Mitra; Priya Saraf; Richa Sharma; Arnab Bhattacharya 001; Sayan Ranu (COMAD/CODS, 2019)

Influence Maximization Revisited: The State of the Art and the Gaps that Remain. - Akhil Arora 001; Sainyam Galhotra; Sayan Ranu (EDBT, 2019)

Route Recommendations on Road Networks for Arbitrary User Preference Functions. - Pranali Yawalkar; Sayan Ranu (ICDE, 2019)

Efficiently Answering Regular Simple Path Queries on Large Labeled Networks. - Sarisht Wadhwa; Anagh Prasad; Sayan Ranu; Amitabha Bagchi; Srikanta Bedathur (SIGMOD Conference, 2019)

RAQ: Relationship-Aware Graph Querying in Large Networks. - Jithin Vachery; Akhil Arora 001; Sayan Ranu; Arnab Bhattacharya 001 (WWW, 2019)

Beyond Shortest Paths: Route Recommendations for Ride-sharing. - Chak Fai Yuen; Abhishek Pratap Singh; Sagar Goyal; Sayan Ranu; Amitabha Bagchi (WWW, 2019)

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

RISC: Rapid Inverted-Index Based Search of Chemical Fingerprints. - Jithin Vachery; Sayan Ranu (J. Chem. Inf. Model., 2019)

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)

GraphGen: A Scalable Approach to Domain-agnostic Labeled Graph Generation. - Nikhil Goyal; Harsh Vardhan Jain; Sayan Ranu (WWW, 2020)

GraphReach: Locality-Aware Graph Neural Networks using Reachability Estimations. - Sunil Nishad; Shubhangi Agarwal 001; Arnab Bhattacharya 001; Sayan Ranu (CoRR, 2020)

Mining Top-k Pairs of Correlated Subgraphs in a Large Network. - Arneish Prateek; Arijit Khan 001; Akshit Goyal; Sayan Ranu (Proc. VLDB Endow., 2020)

A Group-to-Group Version of Random Walk Betweenness Centrality. - Iqra Altaf Gillani; Amitabha Bagchi; Sayan Ranu (COMAD/CODS, 2021)

Batching and Matching for Food Delivery in Dynamic Road Networks. - Manas Joshi; Arshdeep Singh; Sayan Ranu; Amitabha Bagchi; Priyank Karia; Puneet Kala (ICDE, 2021)

GraphReach: Position-Aware Graph Neural Network using Reachability Estimations. - Sunil Nishad; Shubhangi Agarwal 001; Arnab Bhattacharya 001; Sayan Ranu (IJCAI, 2021)

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

Balance Maximization in Signed Networks via Edge Deletions. - Kartik Sharma; Iqra Altaf Gillani; Sourav Medya; Sayan Ranu; Amitabha Bagchi (WSDM, 2021)

Lagrangian Neural Network with Differentiable Symmetries and Relational Inductive Bias. - Ravinder Bhattoo; Sayan Ranu; N. M. Anoop Krishnan (CoRR, 2021)

A Neural Framework for Learning Subgraph and Graph Similarity Measures. - Rishabh Ranjan; Siddharth Grover; Sourav Medya; Venkatesan T. Chakaravarthy; Yogish Sabharwal; Sayan Ranu (CoRR, 2021)

Answering Regular Path Queries through Exemplars. - Komal Chauhan; Kartik Jain; Sayan Ranu; Srikanta Bedathur; Amitabha Bagchi (Proc. VLDB Endow., 2021)

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

FairFoody: Bringing In Fairness in Food Delivery. - Anjali Gupta; Rahul Yadav; Ashish Nair; Abhijnan Chakraborty; Sayan Ranu; Amitabha Bagchi (AAAI, 2022)

Gigs with Guarantees: Achieving Fair Wage for Food Delivery Workers. - Ashish Nair; Rahul Yadav; Anjali Gupta; Abhijnan Chakraborty; Sayan Ranu; Amitabha Bagchi (IJCAI, 2022)

Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network. - Ravinder Bhattoo; Sayan Ranu; N. M. Anoop Krishnan (NeurIPS, 2022)

GREED: A Neural Framework for Learning Graph Distance Functions. - Rishabh Ranjan; Siddharth Grover; Sourav Medya; Venkatesan T. Chakaravarthy; Yogish Sabharwal; Sayan Ranu (NeurIPS, 2022)

Unravelling the Performance of Physics-informed Graph Neural Networks for Dynamical Systems. - Abishek Thangamuthu; Gunjan Kumar; Suresh Bishnoi; Ravinder Bhattoo; N. M. Anoop Krishnan; Sayan Ranu (NeurIPS, 2022)

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

Enhancing the Inductive Biases of Graph Neural ODE for Modeling Dynamical Systems. - Suresh Bishnoi; Ravinder Bhattoo; Sayan Ranu; N. M. Anoop Krishnan (CoRR, 2022)

Learning Rigid Body Dynamics with Lagrangian Graph Neural Network. - Ravinder Bhattoo; Sayan Ranu; N. M. Anoop Krishnan (CoRR, 2022)

FoodMatch: Batching and Matching for Food Delivery in Dynamic Road Networks. - Manas Joshi; Arshdeep Singh; Sayan Ranu; Amitabha Bagchi; Priyank Karia; Puneet Kala (ACM Trans. Spatial Algorithms Syst., 2022)

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

Task and Model Agnostic Adversarial Attack on Graph Neural Networks. - Kartik Sharma; Samidha Verma; Sourav Medya; Arnab Bhattacharya 001; Sayan Ranu (AAAI, 2023)

KWIQ: Answering k-core Window Queries in Temporal Networks. - Mahdihusain Momin; Raj Kamal; Shantwana Dixit; Sayan Ranu; Amitabha Bagchi (EDBT, 2023)

Enhancing the Inductive Biases of Graph Neural ODE for Modeling Physical Systems. - Suresh Bishnoi; Ravinder Bhattoo; Jayadeva; Sayan Ranu; N. M. Anoop Krishnan (ICLR, 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)

Frigate: Frugal Spatio-temporal Forecasting on Road Networks. - Mridul Gupta; Hariprasad Kodamana; Sayan Ranu (KDD, 2023)

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

AirDelhi: Fine-Grained Spatio-Temporal Particulate Matter Dataset From Delhi For ML based Modeling. - Sachin Chauhan; Zeel B. Patel; Sayan Ranu; Rijurekha Sen; Nipun Batra 001 (NeurIPS, 2023)

Learning and Maximizing Influence in Social Networks Under Capacity Constraints. - Pritish Chakraborty; Sayan Ranu; Krishna Sri Ipsit Mantri; Abir De (WSDM, 2023)

Global Counterfactual Explainer for Graph Neural Networks. - Zexi Huang; Mert Kosan; Sourav Medya; Sayan Ranu; Ambuj K. Singh (WSDM, 2023)

Towards Fair Allocation in Social Commerce Platforms. - Anjali Gupta; Shreyans J. Nagori; Abhijnan Chakraborty; Rohit Vaish; Sayan Ranu; Prajit Prashant Sinai Nadkarni; Narendra Varma Dasararaju; Muthusamy Chelliah (WWW, 2023)

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

Empowering Counterfactual Reasoning over Graph Neural Networks through Inductivity. - Samidha Verma; Burouj Armgaan; Sourav Medya; Sayan Ranu (CoRR, 2023)

Graph Neural Stochastic Differential Equations for Learning Brownian Dynamics. - Suresh Bishnoi; Jayadeva; Sayan Ranu; N. M. Anoop Krishnan (CoRR, 2023)

EGraFFBench: Evaluation of Equivariant Graph Neural Network Force Fields for Atomistic Simulations. - Vaibhav Bihani; Utkarsh Pratiush; Sajid Mannan; Tao Du; Zhimin Chen; Santiago Miret; Matthieu Micoulaut; Morten M. Smedskjaer; Sayan Ranu; N. M. Anoop Krishnan (CoRR, 2023)

Learning the dynamics of particle-based systems with Lagrangian graph neural networks. - Ravinder Bhattoo; Sayan Ranu; N. M. Anoop Krishnan (Mach. Learn. Sci. Technol., 2023)

BroGNet: Momentum-Conserving Graph Neural Stochastic Differential Equation for Learning Brownian Dynamics. - Suresh Bishnoi; Jayadeva; Sayan Ranu; N. M. Anoop Krishnan (ICLR, 2024)

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

GNNX-BENCH: Unravelling the Utility of Perturbation-based GNN Explainers through In-depth Benchmarking. - Mert Kosan; Samidha Verma; Burouj Armgaan; Khushbu Pahwa; Ambuj K. Singh; Sourav Medya; Sayan Ranu (ICLR, 2024)

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

GraphTrail: Translating GNN Predictions into Human-Interpretable Logical Rules. - Burouj Armgaan; Manthan Dalmia; Sourav Medya; Sayan Ranu (NeurIPS, 2024)

FUGAL: Feature-fortified Unrestricted Graph Alignment. - Aditya Bommakanti; Harshith Reddy Vonteri; Konstantinos Skitsas; Sayan Ranu; Davide Mottin; Panagiotis Karras (NeurIPS, 2024)

EUGENE: Explainable Unsupervised Approximation of Graph Edit Distance. - Aditya Bommakanti; Harshith Reddy Vonteri; Sayan Ranu; Panagiotis Karras (CoRR, 2024)

GRAPHGINI: Fostering Individual and Group Fairness in Graph Neural Networks. - Anuj Kumar Sirohi; Anjali Gupta; Sayan Ranu; Sandeep Kumar; Amitabha Bagchi (CoRR, 2024)

TAGMol: Target-Aware Gradient-guided Molecule Generation. - Vineeth Dorna; D. Subhalingam; Keshav Kolluru; Shreshth Tuli; Mrityunjay Singh; Saurabh Singal; N. M. Anoop Krishnan; Sayan Ranu (CoRR, 2024)

Bonsai: Gradient-free Graph Distillation for Node Classification. - Mridul Gupta; Samyak Jain; Vansh Ramani; Hariprasad Kodamana; Sayan Ranu (CoRR, 2024)

Discovering symbolic laws directly from trajectories with hamiltonian graph neural networks. - Suresh Bishnoi; Ravinder Bhattoo; Jayadeva; Sayan Ranu; N. M. Anoop Krishnan (Mach. Learn. Sci. Technol., 2024)

InduCE: Inductive Counterfactual Explanations for Graph Neural Networks. - Samidha Verma; Burouj Armgaan; Sourav Medya; Sayan Ranu (Trans. Mach. Learn. Res., 2024)

The Road to Explainable Graph Neural Networks. - Sayan Ranu (SIGMOD Rec., 2024)

Bonsai: Gradient-free Graph Condensation for Node Classification. - Mridul Gupta; Samyak Jain; Vansh Ramani; Hariprasad Kodamana; Sayan Ranu (ICLR, 2025)

GNNMerge: Merging of GNN Models Without Accessing Training Data. - Vipul Garg; Ishita Thakre; Sayan Ranu (CoRR, 2025)

GRAIL: Graph Edit Distance and Node Alignment Using LLM-Generated Code. - Samidha Verma; Arushi Goyal; Ananya Mathur; Ankit Anand; Sayan Ranu (CoRR, 2025)