Text Mining (Biomedical application psychiatry), Natural Language Processing, Debiasing, Model Explanation
Shrestha, Ingroj, and Padmini Srinivasan. "Comparing Deep Learning and Conventional Machine Learning Models for Predicting Mental Illness from History of Present Illness Notations." AMIA Annual Symposium Proceedings. Vol. 2021. American Medical Informatics Association, 2021.
Shrestha, Ingroj, and Shreeya Singh Dhakal. "Fine-grained part-of-speech tagging in Nepali text." Procedia Computer Science 189 (2021): 300-311.
Shrestha, Ingroj, and Jonathan Rusert. "NLP_UIOWA at SemEval-2020 Task 8: You’re Not the Only One Cursed with Knowledge-Multi Branch Model Memotion Analysis." Proceedings of the Fourteenth Workshop on Semantic Evaluation. 2020.
Shrestha, Ingroj, and Shreeya Singh Dhakal. "A new stemmer for Nepali language." 2016 2nd International Conference on Advances in Computing, Communication, & Automation (ICACCA)(Fall). IEEE, 2016.
Shrestha, Ingroj, Dhakal, Shreeya, Kadariya, Madan. "A Comparative Study of Stemming Algorithms for Nepali Language". Proceedings of 3rd International IT conference on ICT for Intelligent Computing. Kathmandu, Nepal, 2016.
Debiasing racial bias in hate speech detection
Selling Drugs with Online Behavioral Advertising: Targeting Consumers Emotions on YouTube
- Assess whether online behavioral advertisements for prescription drugs on YouTube utilize Google search-query-derived data that identifies the emotional states of individual consumers, quietly matching consumers with ads calibrated to chime with their private thoughts, eroding consumer self-determination and implicating the autonomy interest in the process.Sentiment Analysis of Nepali Texts
- Extracted Nepali news and tweets and developed a sentiment corpus for Nepali language. Implemented Naive Bayes algorithm to perform sentiment analysis of Nepali texts. Visualized the results using Sinatra Google charts and Google map.