I am a Machine Learning Engineer at Chime Financial Inc., where I work on the problems at the integration of risk and fraud detection and building out the ML Platform.
Prior to joining Chime, I was a Machine Learning Engineer at Interos Inc. where I worked with Information Extraction team building machine learning models to extract information from unstructured data sources. My work focused specifically on building scalable NLP based models to solve problems like entity linking, entity extraction, and event detection. I also worked on a computer vision problem for building a scalable search engine with an active learning component.
Prior to joining industry, I was a graduate student at University of Maryland Baltimore County (UMBC) , where I was advised by Dr.Francis Ferraro. My research was focused on building multi-task learning models to enhance knowledge in downstream applications by training them jointly with information extraction tasks like knowledge graph embedding and fine-grain entity types.
During my time at UMBC, I also worked under Dr. Shiming Yang at the University of Maryland, School of Medicine (UMed) on exploring deep learning techniques to detect massive transfusion in trauma patients by studying their photoplethysmogram (PPG) signal My work at UMed specifically involved signal processing, representation learning and dimensionality reductions for processing PPG signals to study the underlying pattern through deep learning.
Education
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M.S. Computer Science, 2020
University of Maryland Baltimore County -
B.E. in Electronics and Telecommunication Engineering, 2014
Shivaji University, India
Recent News
- Started a new Role as Senior Machine Learning Engineer at Chime
Chime Financial Inc. - Presented Paper at the CASE Workshop 2023
CASE-2023 -Sept 2023 - Secured 2nd Place CASE 2023 Workshop on Causal News Corpus for Shared Task on Causal Event Detection
RANLP 2023 - Aug - Sept 2023 - Part of the core growth Team at The LevelUp Org
The LevelUp Org - June 2023 - Attending EMNLP 2020 16th Nov - 20th Nov
EMNLP 2020 - Paper Accepted at Deep Learning Inside Workshop at EMNLP 2020
Deep Learning Inside Out (DeeLIO) - 30th September - Attended SIGIR 2020 - 27th July - 29th July
SIGIR 2020 - Part of Beta BootCamp on Privacy Preserving Machine Learning(PPML) Hosted by Openmined - 24th July to 24th August
Openmined Beta Bootcamp on PPML