Niyati is a 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.
Predicting Email Opens with Domain-Sensitive Affect Detection
BATframe: An Unsupervised Approach for Domain-sensitive Affect Detection
Corpus-based Automatic Text Expansion
Leveraging Site Search Logs to Identify Missing Content on Enterprise Webpages
Identifying Suggestions for Improvement of Product Features from Online Product Reviews
EnTwine: Feature Analysis and Candidate Selection for Social User Identity Aggregation
Probabilistic Deduplication of Anonymous Web Traffic
Joint inference of Soft Biometric Features
Combining Soft Biometrics from Images to Generate Text Descriptors
Joint Inference for Extracting Text Descriptors from Triage Images of Mass Disaster Victims
Robust Face Detection in Patient Triage Images.
Joint Inference for Extracting Text Descriptors from Triage Images of Mass Disaster Victims