Artificial Intelligence, Machine Learning, Data Science, Computational Social Science, Technology Policy
Projects and Publications
Optimal Transport and Occupational Skill Analysis
Understanding Job-Skill Relationships using Big Data and Neural Networks. Abhinav Maurya. Bloomberg Data for Good Exchange 2018.
Optimal Transport Embeddings for Understanding Occupations and Skills in the Labor Market. Abhinav Maurya. Working paper.
Bayesian Matching Models for Closing Labor Market Skill Gaps
Bayesian Multi-View Models for Member-Job Matching and Personalized Skill Recommendations. Abhinav Maurya, Rahul Telang. IEEE International Conference on Big Data 2017 (acceptance rate: 17.8%). Awarded IEEE Big Data student travel grant. Finalist for 2017 INFORMS Social Media Section's Best Paper Award. IZA 2018 Workshop on Matching Workers and Jobs Online.
Making Personalized Skill Recommendations using Bayesian Member-Job Matching. Abhinav Maurya, Rahul Telang, Sai Sundar. Poster presented at Amazon Graduate Research Symposium 2017, CMU Innovation with Impact Exhibition 2017, and ISBIS 2017.
Spike-and-Slab Hierarchical Dirichlet Process: A Sparse Nonparametric Admixture Model for Discovering Interdisciplinary Members and Jobs. Abhinav Maurya. Working paper.
Human-Machine Collaboration and the Future of Work
Understanding Human-AI Work Synergies using a Randomized Field Study. Abhinav Maurya, Sunder Kekre, Rahul Telang. AAAI HCOMP 2018 Doctoral Consortium. Invited talk at 2018 YinzOR Student Conference.
Understanding Tech Organizations using Big Data
Gender Disparities in Tech: Evidence and Insights from Employee Performance Evaluations and Peer Reviews. Abhinav Maurya, Alexandra Chouldechova, Rahul Telang. Working paper.
A Lens into Employee Peer Reviews via Sentiment-Aspect Modeling. Abhinav Maurya, Leman Akoglu, Ramayya Krishnan, Daniel Bay. ACM/IEEE ASONAM 2018.
Contrastive Anomaly Detection
Semantic Scan: Detecting Subtle, Spatially Localized Events in Text Streams. Abhinav Maurya, Kenton Murray, Yandong Liu, Chris Dyer, William W. Cohen, Daniel B. Neill. Technical Report: [arXiv:1602.04393]. Winner of seventh Yelp dataset challenge.
Contrastive Structured Anomaly Detection for Gaussian Graphical Models. Abhinav Maurya, Mark Cheung. ICML 2016 Workshop on Anomaly Detection. ACM/IEEE ASONAM 2018.
Bayesian Optimization of Non-convex Metrics for Binary Classification on Imbalanced Datasets
Optimizing Predictive Precision for Actionable Forecasting of Revenue Change from Clients Receiving Periodic Services. Abhinav Maurya, Aly Megahed, Ray Strong, Jeanette Blomberg. 11th INFORMS Workshop on Data Mining and Decision Analytics (DMDA). Finalist for 2016 INFORMS Service Science Cluster Best Paper Award.
Bayesian Optimization for Predicting Rare Internal Failures in Manufacturing Processes. Abhinav Maurya. IEEE International Conference on Big Data 2016 (acceptance rate: 18.7%). Winner of travel grant awarded by Robert Bosch GmbH.
WirelessAcrossRoad: Low-cost Traffic Congestion Detection for the Developing World
Road-RFSense: A Practical RF-Sensing Based Road Traffic Estimation System for Developing Regions. Rijurekha Sen, Abhinav Maurya, Bhaskaran Raman, Amarjeet Singh, Rupesh Mehta, Ramakrishnan Kalyanaraman. ACM Transactions on Sensor Networks, 2014.
KyunQueue: A Sensor Network System To Monitor Road Traffic Queues. Rijurekha Sen, Abhinav Maurya, Bhaskaran Raman, Rupesh Mehta, Ramakrishnan Kalyanaraman, Nagamanoj Vankadhara, Swaroop Roy, Prashima Sharma. 10th ACM Conference on Embedded Networked Sensor Systems, 2012 (acceptance rate: 18.7%).
Machine Learning Algorithms for Road Traffic State Classification in WirelessAcrossRoad. Abhinav Maurya. Master's Thesis, IIT Bombay.
Optimal Transport in Statistical Machine Learning: Selected Review and Some Open Questions. Abhinav Maurya. [pdf]
IEEE Big Data 2017 Panel Discussion on Bias and Transparency. Abhinav Maurya. AI Matters, Volume 4 Issue 2, July 2018. [pdf]
Honors and Awards
Invited talk at MIT Sloan School of Management (2019).
Invited public policy seminar at Burning Glass Technologies, a job market analytics firm (2019).
Awarded the LinkedIn economic graph challenge grant in 2015 ($25K).
Supported by Tepper-sponsored Dempo fellowship for research on the future of digital work in 2017-2018 ($18K).
Winner of Yelp's seventh dataset challenge ($5K).
Inventor Award from IBM Research for patent filing ($3.75K).
Awarded a travel grant by Robert Bosch Gmbh for attending IEEE BigData 2016 ($2K).
Awarded a student travel grant for attending IEEE BigData 2017 ($750).
Awarded a computing resources grant by Microsoft Azure for Research ($3K).
DARPA funding for attending summer school on Probabilistic Programming for Advanced Machine Learning.
CMU's Social Innovation Fellowship 2017.
Finalist for 2017 INFORMS Social Media Section Best Paper Award.
Finalist for 2016 INFORMS Service Science Cluster Best Paper Award.
Invited talk at the INFORMS 2016 session on Data Analytics and Machine Learning.
Invited talk at YinzOR conference 2018.
All India Rank 46 (99.95 percentile) in Graduate Aptitude Test in Engineering for Computer Science (GATE-CS) 2010.
JRD Tata Scholarship for academic excellence awarded in years 2006, 2007, and 2008.
Finalist in Eureka'08, a business plan contest organized by IIT Bombay's Entrepreneurship Cell.
*taught by Prof. Larry Wasserman, favorite course at CMU, covered a lot of material new to me and expanded my worldview
Graduate Coursework at IIT Bombay
Foundations of Machine Learning
Advanced Machine Learning (Probabilistic Graphical Models and Structured Prediction)*
Topics in Machine Learning
Web Search and Mining
Organization of Web Information
Algorithms in Computational Biology
Introduction to Probability and Linear Algebra
Graduate Seminar on Data Center Systems
R&D Project (BriMon)
*taught by Prof. Sunita Sarawagi, favorite course at IIT Bombay, covered a lot of material new to me and expanded my worldview
I am a student in Dual PhD (Machine Learning, Public Policy) at Machine Learning Department and Heinz College, Carnegie Mellon University.
I have previously studied at VJTI Bombay and IIT Bombay, and worked at Microsoft Redmond before heading to CMU Pittsburgh for doctoral studies.
I am a proud alumnus of IIT Bombay, and I use the lessons I learned there almost every day of my life.
I value happiness over success, though there is nothing wrong with having both. I tremendously value thoughtfulness in people.
I believe that tertiary education in its current form is inefficient and obsolete, and that the flipped classroom model is a great replacement. We learn much better by acting on a lesson than listening to it.