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The data and decision sciences team undertakes cutting-edge research in the field of artificial intelligence (AI), machine learning (ML), and analytics to create enterprise automation offerings.


With an emphasis on autonomous intelligent systems and knowledge systems, the group is working on the following areas:

  • Planning and control: This team works on improving the efficiency of networked operational systems in domains such as transportation, logistics, and supply chain, as well as automating decision-making in competitive, multi-agent situations

  • Knowledge extraction and text and data mining: This group focuses on three areas: extracting information elements such as named entities, relations, and events from given documents; building analytics-based tools for automatic candidate evaluation, performance appraisal mining, trainings recommendation, survey responses mining, and human capital evaluation; and building tools for fraud and money laundering detection in domains such as stock markets and banking

  • Knowledge representation and reasoning: The focus of this team is on learning and reasoning using structured knowledge graphs for complex automation tasks such as question answering and problem resolution for specific domains. The techniques used range from Bayesian hierarchical modelling and probabilistic graphical models, to probabilistic logic, Monte Carlo sampling, and natural language processing (NLP). The goal is to significantly improve the accuracy and efficiency of business operations

  • Natural language processing, text mining, and speech: This team develops user-friendly natural language chat and voice interfaces for business applications to aid the extraction of business intelligence and enable the self-help line of applications

  • Analytics for cyber-physical systems: This group works on developing analytics for cyber-physical systems that have physical sensing and actuation tightly coupled with real-time control. Key result areas include efficient utilities operations, smart mobility management, and smart parking systems

  • Intelligent transportation: This team uses image processing, machine learning, and mobile computing to tackle emerging challenges in transportation

  • Requirements and contracts analysis: The research focus of this group is automating the disambiguation and interpretation of complex texts such as regulations and contracts to solve practical problems in software engineering using NLP, machine learning, and deep learning

People & Patents

  • Research team: Led by Anand Sivasubramaniam, the team includes Harshad Khadilikar; Shripad Salsingkar; Sanjay Bhat; Sharadha Ramanan; Girish Palshikar; Rajiv Srivastava; Manoj Apte; Sachin Pawar; Swapnil Hingmare; Lipika Dey; Indrajit Bhattacharya; Rajesh Jayaprakash; Avinash Achar; Arvind Ramanujam; C. Anantaram; Sunilkumar Kopparapu; Arun Vasan; Srinarayana Nagarathinam; Venkataramakrishna P.; Smita Ghaisas; P. Rajaram; Sangameshwar Patil; Preethu Rose; Abhishek Sainani; Ramasubramanian Suriyanarayanan

  • Academic partners: IIT Madras, India; IIT Bombay, India; IIIT Hyderabad, India; IIT Kharagpur, India

  • Patents and publications (2016 onwards): This team has received six patents and has put out more than 140 publications in leading conferences and journals

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