About Sruthikeerthi N Rajagopalakrishnan
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Viewed 769
About me
Inquisitive and energetic computer science graduate with a strong foundation in mathematics, programming logic, deep learning and cloud computing. An industrious researcher who is driven by the pursuit of excellence. Adept at motivating self and others. Passionate about Artificial Intelligence and Data Science. Equipped with a diverse and promising skill-set. Proficient in various platforms and frameworks.
General: Data Visualization, Machine Learning, Deep Learning, Statistical Analysis, Data Structures and Algorithms.
Technical: PostgreSQL, Oracle DB, MongoDB, Python, R, Java, Scikit-Learn, Keras/TensorFlow, Dash, Plotly, Hadoop, Bokeh, Folium, Apache Spark, Tableau, AWS, GCP, Spacy, Splunk
Education
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2021 - Present
University of Buffalo
Master of Science in Data Science
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2016 - 2020
Amrita Vishwa Vidyapeetham
Bachelor of Technology in Computer Science
Experience
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2022 - Present
nuVizz Inc.
Data Science Intern
• Working on developing e-commerce warehouse clusters using multidimensional graph and density based clustering algorithms to find the optimal path to pick orders.
• Devised a pipeline using AWS and Spacy to extract invoice information from PDF documents.
• Processed raw documents using AWS Textract to obtain raw invoice information with a confidence level of 97-99%.
• Developed a named entity recognition model using Spacy to recognize custom tags consisting entities from the invoice preprocessed.
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2020 - 2019
Robert Bosch Centre for DS and AI
Project Associate
• Developed a dashboard using Dash and Plotly to display real-time operations of ambulance five districts in Tamil Nadu, India.
• Developed a clustering algorithm based on DBSCAN to identify the incident locations of an emergency request placed to the EMS system which identified the exact coordinates with an accuracy of 87% over five precision levels.
• Developed a static ambulance allocation algorithm using optimization of a custom loss function. Improved the area covered by the ambulances with 13% lesser ambulances.
• Constructed epidemiology models to track the spread and analyze the interventions during the COVID 19 pandemic for State Government of Tamil Nadu.
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2020 - 2022
Omdena
Lead ML Engineer
• Led the modelling team on developing a named entity recognition model using Spacy, BERT and LSTM models to recognize deed and gazatte document information. Model gave an accuracy of 92%.
• Collaborated with data collection team to extract images from Sentinal 1, 2 and 2A.
• Worked on a semantic segmentation model to access climate risk factors on flood prone areas satellite images datasets with an accuracy of about 89.5% was developed.