Sugreev Chawla

Sugreev Chawla has a diverse range of work experience in various research and data science roles. Sugreev is currently working as a Senior Research Engineer at System Inc. since December 2021. Prior to this, they worked at Attune as a Data Scientist from September 2019 to December 2021, and at WellDone International as a Data Science Advisor from July 2018 to December 2020. Sugreev also has experience as a Data Scientist at Thorn: Digital Defenders of Children from February 2015 to October 2017, where they played a crucial role in improving anti-child abuse investigative tools and collaborating with law enforcement agencies. Before that, they worked as a Data Scientist at Ejenta from September 2013 to February 2015. Sugreev has also gained research experience during their time at Lawrence Livermore National Laboratory (2009-2014) and Electric Propulsion and Plasma Dynamics Lab, Princeton University (2005-2007), where they led experimental research campaigns and conducted data analysis in laser fusion and plasma physics respectively. Additionally, they gained valuable research skills as an Undergraduate Research Assistant at Lawrence Berkeley National Laboratory (2003-2005). With their extensive experience in research and data science, Sugreev Chawla has developed expertise in data analysis techniques, experimental diagnostics, and project management.

Sugreev Chawla has a strong educational background in the field of physics and engineering. Sugreev obtained a Doctor of Philosophy (PhD) degree in Engineering Physics from UC San Diego, as well as a Master of Science (MS) degree in Engineering Physics from the same institution. Prior to their graduate studies, they completed a Bachelor of Arts (BA) degree in Physics from the University of California, Berkeley. Additionally, they also hold a Bachelor of Arts (BA) degree in Applied Mathematics from the University of California, Berkeley.

In addition to their formal education, Sugreev Chawla has also acquired several certifications related to natural language processing and machine learning. Sugreev completed courses such as "Natural Language Processing with Probabilistic Models," "Natural Language Processing with Classification and Vector Spaces," "Structuring Machine Learning Projects," "Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization," and "Neural Networks and Deep Learning" through Coursera. These certifications indicate their dedication to expanding their knowledge and staying updated in the field of artificial intelligence.