Shreya Chakrabarti
Shreya Chakrabarti
Applied Science Manager, Amazon
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Cited by
Cited by
Spatio-temporal progression of cortical activity related to continuous overt and covert speech production in a reading task
JS Brumberg, DJ Krusienski, S Chakrabarti, A Gunduz, P Brunner, ...
PloS one 11 (11), e0166872, 2016
Progress in speech decoding from the electrocorticogram
S Chakrabarti, HM Sandberg, JS Brumberg, DJ Krusienski
Biomedical Engineering Letters 5, 10-21, 2015
GIST 2.0: A scalable multi-trait metric for quantifying population representativeness of individual clinical studies
A Sen, S Chakrabarti, A Goldstein, S Wang, PB Ryan, C Weng
Journal of biomedical informatics 63, 325-336, 2016
Correlating eligibility criteria generalizability and adverse events using Big Data for patients and clinical trials
A Sen, PB Ryan, A Goldstein, S Chakrabarti, S Wang, E Koski, C Weng
Annals of the New York Academy of Sciences 1387 (1), 34-43, 2017
The representativeness of eligible patients in type 2 diabetes trials: a case study using GIST 2.0
A Sen, A Goldstein, S Chakrabarti, N Shang, T Kang, A Yaman, PB Ryan, ...
Journal of the American Medical Informatics Association 25 (3), 239-247, 2018
LORE: a large-scale offer recommendation engine with eligibility and capacity constraints
R Makhijani, S Chakrabarti, D Struble, Y Liu
Proceedings of the 13th ACM Conference on Recommender Systems, 160-168, 2019
An Interoperable Similarity-based Cohort Identification Method Using the OMOP Common Data Model Version 5.0
S Chakrabarti, A Sen, V Huser, GW Hruby, A Rusanov, ...
Journal of Healthcare Informatics Research 2017, 1-18, 2017
Neural insights for digital marketing content design
F Kong, Y Li, H Nassif, T Fiez, R Henao, S Chakrabarti
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023
Predicting mel-frequency cepstral coefficients from electrocorticographic signals during continuous speech production
S Chakrabarti, DJ Krusienski, G Schalk, JS Brumberg
Proceedings of the Sixth International Neural Engineering Conference, 2013
How Have Cancer Clinical Trial Eligibility Criteria Evolved Over Time?
A Yaman, S Chakrabarti, A Sen, C Weng
Proceedings of AMIA Joint Summits, 2016
Assessing eligibility criteria generalizability and their correlations with adverse events using big data for EHRS and clinical trials
A Sen, P Ryan, A Goldstein, S Chakrabarti, S Wang, C Weng
Proceedings of the Data Science Learning and Applications to Biomedical and …, 2016
Characterization and Decoding of Speech Representations From the Electrocorticogram
S Chakrabarti
Progressive horizon learning: Adaptive long term optimization for personalized recommendation
C Yi, D Zumwalt, Z Ni, S Chakrabarti
Proceedings of the 17th ACM Conference on Recommender Systems, 940-946, 2023
Method, system, and manufacture for min-cost flow item recommendations
D Struble, R Makhijani, Y Liu, S Chakrabarti
US Patent 11,367,118, 2022
LORE: A large-scale offer recommendation engine through the lens of an online subscription service
R Makhijani, S Chakrabarti, D Struble, Y Liu
Using ECoG Gamma Activity to Model the Mel-Frequency Cepstral Coefficients of Speech
DJK S. Chakrabarti, J.S. Brumberg, A. Gunduz, P. Brunner, G. Schalk
Proceedings of the Fifth International Brain-Computer Interface Meeting, 2013
CMOS Implementation of the resistive network model of the outer plexiform layer of the retina.
S Chakrabarti, A Sahu
Proceedings of the Internal Conference on Scientific Paradigm Shift in …, 2011
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