Definition
Sunita Sarawagi is an Indian computer scientist and professor at the Indian Institute of Technology Bombay (IIT Bombay). She is recognized for her research contributions in data mining, machine learning, database systems, and information extraction.
Overview
Sarawagi earned her Ph.D. in Computer Science from the University of Pennsylvania in 1996, under the supervision of Michael J. Cafiero. She joined the faculty of IIT Bombay in 1997, where she has held positions ranging from Assistant Professor to full Professor in the Department of Computer Science and Engineering. Her research agenda focuses on probabilistic models for structured data, pattern mining, web data extraction, and scalable algorithms for large‑scale data analysis. She has authored and co‑authored numerous papers in top conferences and journals, including SIGMOD, VLDB, ICML, and KDD. Notable works include the development of algorithms for frequent pattern mining, contributions to Conditional Random Fields for sequence labeling, and techniques for entity extraction from semi‑structured web sources. Sarawagi has mentored many graduate students and served on program committees for major international conferences. She has received several recognitions, such as the ACM SIGKDD Service Award (2009) and the Indian National Science Academy (INSA) Young Scientist Medal (2003).
Etymology/Origin
The given name “Sunita” derives from Sanskrit, where it commonly means “well‑behaved,” “good conduct,” or “wise.” The surname “Sarawagi” is associated with a merchant community in North India, historically linked to trading and business activities. Both components are typical of Indian naming conventions.
Characteristics
- Academic Position: Professor, Department of Computer Science and Engineering, IIT Bombay.
- Research Interests: Data mining, machine learning, database systems, information extraction, probabilistic modeling, web mining.
- Key Contributions: Development of efficient algorithms for mining frequent patterns; advancements in Conditional Random Fields and structured prediction; scalable methods for extracting knowledge from web and social media data.
- Publications: Over 100 peer‑reviewed articles, several book chapters, and conference proceedings.
- Professional Service: Program committee member for conferences such as SIGMOD, VLDB, KDD, and ICML; editorial board member for journals including IEEE Transactions on Knowledge and Data Engineering.
- Awards & Honors: ACM SIGKDD Service Award (2009); INSA Young Scientist Medal (2003); Fellow of the Indian National Academy of Engineering (INAE) (2020).
Related Topics
- Data Mining
- Machine Learning
- Database Systems
- Information Extraction
- Conditional Random Fields
- Frequent Pattern Mining
- Indian Institute of Technology Bombay
- Indian Computer Science Community