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CODS COMAD 2021 : ACM India Joint International Conference on Data Science & Management of Data

Bangalore, India
Event Date: Jan 02, 2021 - Jan 04, 2021
Submission Deadline: Jul 10, 2020
Notification of Acceptance: Oct 01, 2020
Camera Ready Version Due : Oct 24, 2020


The ACM India Joint International Conference on Data Science and Management of Data (CODS-COMAD) 2021 (8th ACM IKDD CODS and 26th COMAD), will be held in Bangalore, India on January 2-4, 2021.

For over two decades, the International Conference on Management of Data (COMAD), modelled along the lines of ACM SIGMOD, has been the premier international database conference hosted in India by Division II of Computer Society of India. The first COMAD was held in 1989, and it has been held on a nearly annual basis since then (except for a few breaks such as in the years when VLDB and ICDE were held in India). CODS started in 2014 as a very successful conference with an excellent program and has been growing very strongly since then on the base growing interest in AI/Machine Learning/Data Science. These two conferences came together for the first time in 2018. This year again, we are bringing together the two related communities closer under a common umbrella.

Call For Paper

Topics of Interest


Transaction processing, query processing, query optimisation, indexing and storage, distributed data platforms, spatio-temporal databases, RDBMS, NoSQL systems, key-value stores, cloud data management, big data systems, data cleansing, data analytics, data integration, benchmarking, tuning and testing, graph database management, security and privacy.

Data Science

Data pre-processing, classification and regression, parallel and distributed learning, semi- and unsupervised learning, matrix and tensor methods, graph mining, network analytics, reinforcement learning, feature engineering, deep learning, Bayesian methods, time series analysis, optimization, graphical models, relational models, text analytics and NLP, information retrieval, knowledge representation, knowledge-based systems, human-in-the-loop learning, planning and reasoning, ML for mobiles and other resource constrained environments, data mining, causality, fairness accountability and transparency, interpretability.


Social network analysis, recommender systems, online advertising, bioinformatics, computational neuroscience, systems biology, multimedia processing, crowdsourcing, robotics and autonomous systems, analytics on sensor networks and IoT, computer vision, surveillance/monitoring and anomaly detection in networked systems, urban computing, and technology for emerging markets.

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