I am a third-year Ph.D. student and a Graduate Research Assistant at the Department of CSE, at Pennsylvania State University, under the supervision of Dr. Rui Zhang (co advised by Dr. Rebecca J. Passonneau). My research interest lies in Natural Language Processing, Machine Learning, Computer Vision, and Data Mining.
Working as a graduate research assistant in Pennsylvania State University. Currently working on multiple NLP projects e.g. Few-Shot Sequence Labeling, Named Entity Recognition, Relation Extraction, coreference resolution etc.
Worked on different Neural Ranking techniques to research their efficacy in search and recommendation.
Worked as a graduate research assistant under supervision of Dr. Mohammed Eunus Ali in CSE, BUET. Multiple research projects are funded by the government of Bangladesh.
Sarkar Snigdha Sarathi Das, Arzoo Katiyar, Rebecca J. Passonneau, Rui Zhang.
CONTaiNER: Few-Shot Named Entity Recognition via Contrastive Learning.
ACL 2022. [pdf] [code]
Sarkar Snigdha Sarathi Das, Subangkar Karmaker Shanto, Masum Rahman, Md. Saiful Islam, Atif Rahman, Mohammad Mehedy Masud, Mohammed Eunus Ali.
BayesBeat: A Bayesian Deep Learning Approach for Atrial Fibrillation Detection from Noisy Photoplethysmography Data.
IMWUT (UbiComp) 2022
Sarkar Snigdha Sarathi Das, Mohammed Eunus Ali, Yuan-Fang Li, Yong-Bin Kang, Timos Sellis.
Boosting House Price Predictions using Geo-Spatial Network Embedding.
Data Mining and Knowledge Discovery(2021)
Md. Ashraful Islam, Mir Mahathir Mohammad, Sarkar Snigdha Sarathi Das, Mohammed Eunus Ali.
A Survey on Deep Learning Based Point-Of-Interest (POI) Recommendations.
Sarkar Snigdha Sarathi Das, Syed Md. Mukit Rashid, Mohammed Eunus Ali.
CCCNet: An Attention Based Deep Learning Framework for Categorized Crowd Counting.
2020 IEEE International Joint Conference on Neural Networks (IJCNN)
Syed Md. Mukit Rashid, Sarkar Snigdha Sarathi Das, Mohammed Eunus Ali.
Categorized Crowd Counting based on Different Body State Detection.
International Conference on Networking, Systems and Security, December 2018