Sarkar Snigdha Sarathi Das

State College, Pennsylvania

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.


Research Assistant

Department of CSE, Pennsylvania State University

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.

January 2021 - Present

Applied Scientist Intern

Amazon Alexa, Sunnyvale CA

Worked on different Neural Ranking techniques to research their efficacy in search and recommendation.

June 2022 - August 2022

Research Assistant

Department of CSE, BUET

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.

May 2019 - December 2020


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
[pdf] [code]

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)

Conference Poster

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


The Pennsylvania State University

Ph.D. Candidate
Subject: Computer Science and Engineering (CSE)
January 2021 - Present

Bangladesh University of Engineering and Technology (BUET)

Obtained Degree: B.Sc. Engg
Subject: Computer Science and Engineering (CSE)

CGPA: 3.88/4.00

February 2015 - April 2019


Technical Skills
  • Languages: Python, C, C++, Java, Assembly Language((Intel x86 Architecture, MIPS Architecture).
  • Scripting Language: Bash, HTML, CSS, PHP, LATEX, SQL.
  • Deep Learning Frameworks: Keras, PyTorch, TensorFlow.
  • Software Tools: MS Word, PowerPoint, Excel.
  • Hardware Tools: Adruino, ESP and Different Micro-controllers and Networking chips.
  • SQL Database: Oracle SQL, MySQL, PostgreSQL, SQLite.
  • NoSQL Database: MongoDB, ArangoDB.
  • Design Tools: Proteus circuit simulator, AutoCAD and CISCO packet tracer.


Research Interests

  • Machine Learning.
  • Computer Vision.
  • Natural Language Processing.
  • Data Mining.

Hobbies and Other Interests

  • Reading books
  • Watching movies
  • Gaming
  • Overclocking


  • Dr. Tse-Yun Feng Outstanding Graduate Student Award, 2022
  • Champion: Huawei Seeds for the Future, 2019 
  • HSC Board Merit scholarship 2014
  • Junior Merit Scholarship: 2010
  • Primary Merit Scholarship: 2007