ReComp: QoS-aware recursive service composition at minimum cost. - Vimmi Jaiswal; Amit Sharma 007; Akshat Verma (Integrated Network Management, 2011)

Network-Centric Recommendation: Personalization with and in Social Networks. - Amit Sharma 007; Dan Cosley (SocialCom/PASSAT, 2011)

Algorithms for Generating Ordered Solutions for Explicit AND/OR Structures. - Priyankar Ghosh; Amit Sharma 007; P. P. Chakrabarti 001; Pallab Dasgupta (J. Artif. Intell. Res., 2012)

PopCore: a system for network-centric recommendation. - Amit Sharma 007 (CSCW Companion, 2013)

Friends, Strangers, and the Value of Ego Networks for Recommendation. - Amit Sharma 007; Mevlana Gemici; Dan Cosley (ICWSM, 2013)

Algorithms for Generating Ordered Solutions for Explicit AND/OR Structures : Extended Abstract. - Priyankar Ghosh; Amit Sharma 007; Partha Pratim Chakrabarti; Pallab Dasgupta (IJCAI, 2013)

A Research Platform for Recommendation within Social Networks. - Amit Sharma 007 (RSWeb@RecSys, 2013)

Pairwise learning in recommendation: experiments with community recommendation on linkedin. - Amit Sharma 007; Baoshi Yan (RecSys, 2013)

Do social explanations work?: studying and modeling the effects of social explanations in recommender systems. - Amit Sharma 007; Dan Cosley (WWW, 2013)

Modeling the effect of people's preferences and social forces on adopting and sharing items. - Amit Sharma 007 (RecSys, 2014)

Studying and Modeling the Connection between People's Preferences and Content Sharing. - Amit Sharma 007; Dan Cosley (CSCW, 2015)

Estimating the Causal Impact of Recommendation Systems from Observational Data. - Amit Sharma 007; Jake M. Hofman; Duncan J. Watts (EC, 2015)

The Interplay of Personal Preference and Social Influence in Sharing Networks. - Amit Sharma 007 (2015)

Distinguishing between Personal Preferences and Social Influence in Online Activity Feeds. - Amit Sharma 007; Dan Cosley (CSCW, 2016)

Predictability of Popularity: Gaps between Prediction and Understanding. - Benjamin Shulman; Amit Sharma 007; Dan Cosley (ICWSM, 2016)

Averaging Gone Wrong: Using Time-Aware Analyses to Better Understand Behavior. - Samuel Barbosa; Dan Cosley; Amit Sharma 007; Roberto M. Cesar Jr. (WWW, 2016)

Exploring Limits to Prediction in Complex Social Systems. - Travis Martin; Jake M. Hofman; Amit Sharma 007; Ashton Anderson; Duncan J. Watts (WWW, 2016)

Split-door criterion for causal identification: Automatic search for natural experiments. - Amit Sharma 007; Jake M. Hofman; Duncan J. Watts (CoRR, 2016)

Harvesting Randomness to Optimize Distributed Systems. - Mathias Lécuyer; Joshua Lockerman; Lamont Nelson; Siddhartha Sen 001; Amit Sharma 007; Aleksandrs Slivkins (HotNets, 2017)

FATREC Workshop on Responsible Recommendation. - Michael D. Ekstrand; Amit Sharma 007 (RecSys, 2017)

Auditing Search Engines for Differential Satisfaction Across Demographics. - Rishabh Mehrotra; Ashton Anderson; Fernando Diaz 001; Amit Sharma 007; Hanna M. Wallach; Emine Yilmaz (WWW (Companion Volume), 2017)

Reports of the Workshops Held at the 2018 International AAAI Conference on Web and Social Media. - Jisun An; Rumi Chunara; David J. Crandall; Darian Frajberg; Megan French; Bernard J. Jansen; Juhi Kulshrestha; Yelena Mejova; Daniel M. Romero; Joni Salminen; Amit Sharma 007; Amit P. Sheth; et al. (AI Mag., 2018)

Moments of Change: Analyzing Peer-Based Cognitive Support in Online Mental Health Forums. - Yada Pruksachatkun; Sachin R. Pendse; Amit Sharma 007 (CHI, 2019)

Learnings from an Ongoing Deployment of an IVR-based Platform for Voter Awareness. - Ramaravind Kommiya Mothilal; Devansh Mehta; Alok Sharma; William Thies; Amit Sharma 007 (CSCW Companion, 2019)

Learnings from deploying a voice-based social platform for people with disability. - Karn Dubey; Palash Gupta; Rachna Shriwas; Gayatri Gulvady; Amit Sharma 007 (COMPASS, 2019)

Optimizing peer referrals for public awareness using contextual bandits. - Ramaravind Kommiya Mothilal; Amulya Yadav; Amit Sharma 007 (COMPASS, 2019)

Mental health in the global south: challenges and opportunities in HCI for development. - Sachin R. Pendse; Naveena Karusala; Divya Siddarth; Pattie Gonsalves; Seema Mehrotra; John A. Naslund; Mamta Sood; Neha Kumar 001; Amit Sharma 007 (COMPASS, 2019)

Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data. - Jackson A. Killian; Bryan Wilder; Amit Sharma 007; Vinod Choudhary; Bistra Dilkina; Milind Tambe (KDD, 2019)

Causal Inference and Counterfactual Reasoning (3hr Tutorial). - Emre Kiciman; Amit Sharma 007 (WSDM, 2019)

Quantifying Infra-Marginality and Its Trade-off with Group Fairness. - Arpita Biswas; Siddharth Barman; Amit Deshpande; Amit Sharma 007 (CoRR, 2019)

Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers. - Divyat Mahajan; Chenhao Tan; Amit Sharma 007 (CoRR, 2019)

Cross-Cultural Differences in the Use of Online Mental Health Support Forums. - Sachin R. Pendse; Kate Niederhoffer; Amit Sharma 007 (Proc. ACM Hum. Comput. Interact., 2019)

Learn2Earn: Using Mobile Airtime Incentives to Bolster Public Awareness Campaigns. - Saiganesh Swaminathan; Indrani Medhi-Thies; Devansh Mehta; Edward Cutrell; Amit Sharma 007; William Thies (Proc. ACM Hum. Comput. Interact., 2019)

Facilitating Media Distribution with Monetary Incentives. - Devansh Mehta; Alok Sharma; Ramaravind Kommiya Mothilal; Chiraag; Anurag Shukla; Vishnu Prasad; William Thies; Venkanna U 001; Colin Scott; Amit Sharma 007 (CHI Extended Abstracts, 2020)

"Like Shock Absorbers": Understanding the Human Infrastructures of Technology-Mediated Mental Health Support. - Sachin R. Pendse; Faisal M. Lalani; Munmun De Choudhury; Amit Sharma 007; Neha Kumar 001 (CHI, 2020)

Causal Inference and Counterfactual Reasoning. - Amit Sharma 007; Emre Kiciman (COMAD/CODS, 2020)

Using Mobile Airtime Credits to Incentivize Learning, Sharing and Survey Response: Experiences from the Field. - Devansh Mehta; Ramaravind Kommiya Mothilal; Alok Sharma; William Thies; Amit Sharma 007 (COMPASS, 2020)

Explaining machine learning classifiers through diverse counterfactual explanations. - Ramaravind Kommiya Mothilal; Amit Sharma 007; Chenhao Tan (FAT*, 2020)

Alleviating Privacy Attacks via Causal Learning. - Shruti Tople; Amit Sharma 007; Aditya Nori (ICML, 2020)

Causal Factors of Effective Psychosocial Outcomes in Online Mental Health Communities. - Koustuv Saha; Amit Sharma 007 (ICWSM, 2020)

Engagement Patterns of Peer-to-Peer Interactions on Mental Health Platforms. - Ashish Sharma 004; Monojit Choudhury; Tim Althoff; Amit Sharma 007 (ICWSM, 2020)

Learnings from Technological Interventions in a Low Resource Language: A Case-Study on Gondi. - Devansh Mehta; Sebastin Santy; Ramaravind Kommiya Mothilal; Brij Mohan Lal Srivastava; Alok Sharma; Anurag Shukla; Vishnu Prasad; Venkanna U 001; Amit Sharma 007; Kalika Bali (LREC, 2020)

Bursts of Activity: Temporal Patterns of Help-Seeking and Support in Online Mental Health Forums. - Taisa Kushner; Amit Sharma 007 (WWW, 2020)

Counterfactual Generation and Fairness Evaluation Using Adversarially Learned Inference. - Saloni Dash; Amit Sharma 007 (CoRR, 2020)

DoWhy: An End-to-End Library for Causal Inference. - Amit Sharma 007; Emre Kiciman (CoRR, 2020)

The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective. - Naman Goel; Alfonso Amayuelas; Amit Deshpande; Amit Sharma 007 (AAAI, 2021)

Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End. - Ramaravind Kommiya Mothilal; Divyat Mahajan; Chenhao Tan; Amit Sharma 007 (AIES, 2021)

"Can I Not Be Suicidal on a Sunday?": Understanding Technology-Mediated Pathways to Mental Health Support. - Sachin R. Pendse; Amit Sharma 007; Aditya Vashistha; Munmun De Choudhury; Neha Kumar 001 (CHI, 2021)

Sayer: Using Implicit Feedback to Optimize System Policies. - Mathias Lécuyer; Sang Hoon Kim; Mihir Nanavati; Junchen Jiang; Siddhartha Sen 001; Aleksandrs Slivkins; Amit Sharma 007 (SoCC, 2021)

MINDNOTES : A Mobile Platform to enable users to break stigma around mental health and connect with therapists. - Prateek Chanda; Amogh Wagh; Jemimah A. Johnson; Swaraj Renghe; Vageesh Chandramouli; George Mathews; Sapna Behar; Poornima Bhola; Girish N. Rao; Paulomi Sudhir; T. K. Srikanth; Amit Sharma 007; et al. (CSCW Companion, 2021)

Domain Generalization using Causal Matching. - Divyat Mahajan; Shruti Tople; Amit Sharma 007 (ICML, 2021)

Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions. - Yanbo Xu; Divyat Mahajan; Liz Manrao; Amit Sharma 007; Emre Kiciman (WSDM, 2021)

Technology Readiness Levels for Machine Learning Systems. - Alexander Lavin; Ciarán M. Gilligan-Lee; Alessya Visnjic; Siddha Ganju; Dava J. Newman; Sujoy Ganguly; Danny Lange; Atilim Günes Baydin; Amit Sharma 007; Adam Gibson; Yarin Gal; Eric P. Xing; et al. (CoRR, 2021)

Causally Constrained Data Synthesis for Private Data Release. - Varun Chandrasekaran; Darren Edge; Somesh Jha; Amit Sharma 007; Cheng Zhang 005; Shruti Tople (CoRR, 2021)

DoWhy: Addressing Challenges in Expressing and Validating Causal Assumptions. - Amit Sharma 007; Vasilis Syrgkanis; Cheng Zhang 005; Emre Kiciman (CoRR, 2021)

The Connection between Out-of-Distribution Generalization and Privacy of ML Models. - Divyat Mahajan; Shruti Tople; Amit Sharma 007 (CoRR, 2021)

Causal Regularization Using Domain Priors. - Abbavaram Gowtham Reddy; Sai Srinivas Kancheti; Vineeth N. Balasubramanian; Amit Sharma 007 (CoRR, 2021)

Omitted Variable Bias in Machine Learned Causal Models. - Victor Chernozhukov; Carlos Cinelli; Whitney Newey; Amit Sharma 007; Vasilis Syrgkanis (CoRR, 2021)

Matching Learned Causal Effects of Neural Networks with Domain Priors. - Sai Srinivas Kancheti; Abbavaram Gowtham Reddy; Vineeth N. Balasubramanian; Amit Sharma 007 (ICML, 2022)

Probing Classifiers are Unreliable for Concept Removal and Detection. - Abhinav Kumar 001; Chenhao Tan; Amit Sharma 007 (NeurIPS, 2022)

Evaluating and Mitigating Bias in Image Classifiers: A Causal Perspective Using Counterfactuals. - Saloni Dash; Vineeth N. Balasubramanian; Amit Sharma 007 (WACV, 2022)

Deep End-to-end Causal Inference. - Tomas Geffner; Javier Antorán; Adam Foster 001; Wenbo Gong 001; Chao Ma 019; Emre Kiciman; Amit Sharma 007; Angus Lamb; Martin Kukla; Nick Pawlowski; Miltiadis Allamanis; Cheng Zhang 005 (CoRR, 2022)

Using Interventions to Improve Out-of-Distribution Generalization of Text-Matching Recommendation Systems. - Parikshit Bansal; Yashoteja Prabhu; Emre Kiciman; Amit Sharma 007 (CoRR, 2022)

Counterfactual Generation Under Confounding. - Abbavaram Gowtham Reddy; Saloni Dash; Amit Sharma 007; Vineeth N. Balasubramanian (CoRR, 2022)

Controlling Learned Effects to Reduce Spurious Correlations in Text Classifiers. - Parikshit Bansal; Amit Sharma 007 (ACL (1), 2023)

Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization. - Jivat Neet Kaur; Emre Kiciman; Amit Sharma 007 (ICLR, 2023)

Causal Effect Regularization: Automated Detection and Removal of Spurious Correlations. - Abhinav Kumar 001; Amit Deshpande; Amit Sharma 007 (NeurIPS, 2023)

Rethinking Counterfactual Data Augmentation Under Confounding. - Abbavaram Gowtham Reddy; Saketh Bachu; Saloni Dash; Charchit Sharma; Amit Sharma 007; Vineeth N. Balasubramanian (CoRR, 2023)

Causal Effect Regularization: Automated Detection and Removal of Spurious Attributes. - Abhinav Kumar 001; Amit Deshpande; Amit Sharma 007 (CoRR, 2023)

Large Language Models as Annotators: Enhancing Generalization of NLP Models at Minimal Cost. - Parikshit Bansal; Amit Sharma 007 (CoRR, 2023)

Causal Inference Using LLM-Guided Discovery. - Aniket Vashishtha; Abbavaram Gowtham Reddy; Abhinav Kumar 001; Saketh Bachu; Vineeth N. Balasubramanian; Amit Sharma 007 (CoRR, 2023)

Pre-registration for Predictive Modeling. - Jake M. Hofman; Angelos Chatzimparmpas; Amit Sharma 007; Duncan J. Watts; Jessica Hullman (CoRR, 2023)

Machine Explanations and Human Understanding. - Chacha Chen; Shi Feng 005; Amit Sharma 007; Chenhao Tan (Trans. Mach. Learn. Res., 2023)

NICE: To Optimize In-Context Examples or Not? - Pragya Srivastava; Satvik Golechha; Amit Deshpande; Amit Sharma 007 (ACL (1), 2024)

Optimizing Novelty of Top-k Recommendations using Large Language Models and Reinforcement Learning. - Amit Sharma 007; Hua Li; Xue Li 005; Jian Jiao 007 (KDD, 2024)

Teaching Transformers Causal Reasoning through Axiomatic Training. - Aniket Vashishtha; Abhinav Kumar 001; Abbavaram Gowtham Reddy; Vineeth N. Balasubramanian; Amit Sharma 007 (CoRR, 2024)

Deep End-to-end Causal Inference. - Tomas Geffner; Javier Antorán; Adam Foster 001; Wenbo Gong 001; Chao Ma 019; Emre Kiciman; Amit Sharma 007; Angus Lamb; Martin Kukla; Nick Pawlowski; Agrin Hilmkil; Joel Jennings; et al. (Trans. Mach. Learn. Res., 2024)

Causal Reasoning and Large Language Models: Opening a New Frontier for Causality. - Emre Kiciman; Robert Osazuwa Ness; Amit Sharma 007; Chenhao Tan (Trans. Mach. Learn. Res., 2024)

Causal Order: The Key to Leveraging Imperfect Experts in Causal Inference. - Aniket Vashishtha; Abbavaram Gowtham Reddy; Abhinav Kumar 001; Saketh Bachu; Vineeth N. Balasubramanian; Amit Sharma 007 (ICLR, 2025)

On the Necessity of World Knowledge for Mitigating Missing Labels in Extreme Classification. - Jatin Prakash; Anirudh Buvanesh; Bishal Santra; Deepak Saini; Sachin Yadav 002; Jian Jiao 007; Yashoteja Prabhu; Amit Sharma 007; Manik Varma (KDD (1), 2025)