Niyati is a Senior Computer Scientist at the Big Data Experience Lab, Adobe Research, Bangalore, India. Her research interests include affective computing, computational linguistics, natural language processing, and machine learning.

Psycholinguistics, Computational Linguistics, and Machine learning put together can be efficiently leveraged to understand online users, their content preferences, and specifically their reactions including moods, opinions, and emotions. Niyati focuses on this research Affective Computing for Language and Text. Her work has applications towards Personalization at Scale for Content Authoring and towards creating personalized experiences.

She completed her Ph.D. from University of Maryland Baltimore County (UMBC) in September 2012. Her dissertation was on Joint Inference for Extracting Soft Biometric Text Descriptors from Patient Triage Images. She completed her M.S. in computer science from UMBC in May 2010 and B.E. from University of Pune (India) in 2008. Her work experience includes research internships at National Library of Medicine, National Intitutes of Health, Bethesda, MD.

  Research Area

• Affective Computing for Language: This research focuses on the analysis of content, specifically text and language towards creating and understanding target, specific audience reactions using Psychographics, Sociology, Psychology, and Computational Linguistics approaches.
• Brand Content Understanding: Like the content and the online user, brands also create a footprint for themselves through their marketing communication and brand presence. The research here focusses on understanding various brand metrics and intangibles from their published content point of view.
• Data-driven Content: Online activities or aggregate user interactions are a key indicator of whether a specific kind of content worked well or not. These indicators also drive the content present in digital media in various places. The research focusses on harvesting the right indicators to influence content served to specific audiences and targets.
• Social Media Analysis: The focus is on understanding the role of user-generated content on personifying the online user. The research here includes content expert identification in social communities, scoring creatives, and understanding a user across different networks.