Sargun Nagpal
Graduate Student at NYU Center for Data Science- Claim this Profile
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Bio
Ridam Pal
I have no hesitation in stating that Sargun is one of the smartest and most detail-oriented people I have come across as a PhD student at IIIT-Delhi. We worked together on multiple research projects spanning NLP, Machine Learning and Statistics. Sargun brings a wealth of knowledge to the table, has a very strong research potential and develops innovative ideas to solve problems. With his extensive industrial experience, he is able to combine his data science expertise with exceptional programming skills to translate ideas to prototypes and products. He is an absolute delight to work with!
Ridam Pal
I have no hesitation in stating that Sargun is one of the smartest and most detail-oriented people I have come across as a PhD student at IIIT-Delhi. We worked together on multiple research projects spanning NLP, Machine Learning and Statistics. Sargun brings a wealth of knowledge to the table, has a very strong research potential and develops innovative ideas to solve problems. With his extensive industrial experience, he is able to combine his data science expertise with exceptional programming skills to translate ideas to prototypes and products. He is an absolute delight to work with!
Ridam Pal
I have no hesitation in stating that Sargun is one of the smartest and most detail-oriented people I have come across as a PhD student at IIIT-Delhi. We worked together on multiple research projects spanning NLP, Machine Learning and Statistics. Sargun brings a wealth of knowledge to the table, has a very strong research potential and develops innovative ideas to solve problems. With his extensive industrial experience, he is able to combine his data science expertise with exceptional programming skills to translate ideas to prototypes and products. He is an absolute delight to work with!
Ridam Pal
I have no hesitation in stating that Sargun is one of the smartest and most detail-oriented people I have come across as a PhD student at IIIT-Delhi. We worked together on multiple research projects spanning NLP, Machine Learning and Statistics. Sargun brings a wealth of knowledge to the table, has a very strong research potential and develops innovative ideas to solve problems. With his extensive industrial experience, he is able to combine his data science expertise with exceptional programming skills to translate ideas to prototypes and products. He is an absolute delight to work with!
Credentials
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Sequences, Time Series and Prediction
CourseraMar, 2022- Sep, 2024 -
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
CourseraFeb, 2022- Sep, 2024 -
Natural Language Processing in TensorFlow
CourseraFeb, 2022- Sep, 2024 -
AWS Machine Learning Foundations
UdacityOct, 2021- Sep, 2024 -
Natural Language Processing with Sequence Models
DeepLearning.AIJul, 2021- Sep, 2024 -
Natural Language Processing with Probabilistic Models
DeepLearning.AIMar, 2021- Sep, 2024 -
Natural Language Processing with Classification and Vector Spaces
DeepLearning.AIFeb, 2021- Sep, 2024 -
Linux Mastery
UdemyNov, 2018- Sep, 2024 -
Python for Data Science and Machine Learning Bootcamp
UdemyNov, 2018- Sep, 2024 -
Machine Learning
CourseraJun, 2018- Sep, 2024
Experience
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NYU Center for Data Science
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United States
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Higher Education
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1 - 100 Employee
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Graduate Student
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Aug 2022 - Present
Grade: 4/4 CILVR Lab (Multimodal models for NLQ based Zero-shot Object Detection in Videos) Grade: 4/4 CILVR Lab (Multimodal models for NLQ based Zero-shot Object Detection in Videos)
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Marsh McLennan
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United States
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Financial Services
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700 & Above Employee
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Data Science Graduate Intern
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May 2023 - Aug 2023
Peer-grouping of insurance clients based on claims data (LLMs, Clustering, Hypothesis Testing). Peer-grouping of insurance clients based on claims data (LLMs, Clustering, Hypothesis Testing).
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Ashoka University
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India
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Higher Education
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500 - 600 Employee
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Research Scientist
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Aug 2021 - Jul 2022
• Statistical Hypothesis Testing and Study design (Computational epidemiology) • Agent-based modeling and simulations • Social networks and Graph ML (Worked in ML2CT Lab under Prof. Gautam Menon (IISc) and Prof. Debayan Gupta (MIT, Yale). • Statistical Hypothesis Testing and Study design (Computational epidemiology) • Agent-based modeling and simulations • Social networks and Graph ML (Worked in ML2CT Lab under Prof. Gautam Menon (IISc) and Prof. Debayan Gupta (MIT, Yale).
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Indraprastha Institute of Information Technology, Delhi
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India
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Higher Education
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500 - 600 Employee
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Research Trainee
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Mar 2021 - May 2022
• Training and Interpretability of BERT-based Language models (contextual genome representations). • Social media analysis: Detection of Misinformation signals on Twitter. • Machine Learning & NLP to predict COVID-19 caseloads and emerging variants. (Worked in TavLab, under the guidance of Dr. Tavpritesh Sethi) • Training and Interpretability of BERT-based Language models (contextual genome representations). • Social media analysis: Detection of Misinformation signals on Twitter. • Machine Learning & NLP to predict COVID-19 caseloads and emerging variants. (Worked in TavLab, under the guidance of Dr. Tavpritesh Sethi)
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Fidelity Investments
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United States
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Financial Services
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700 & Above Employee
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Software Engineer - Data Science
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Jun 2019 - Jul 2021
• Document Intelligence: Information Extraction from unstructured PDFs (OCR, NER, Topic Modeling). • NLP: Abstractive text summarization, Vector space models, Semantic search. • ML & Software Development: Explainable AI, Fraud Surveillance service, Recommender systems. (Part of AI Incubator in Fidelity Center for Applied Technology (applied R&D team). • Document Intelligence: Information Extraction from unstructured PDFs (OCR, NER, Topic Modeling). • NLP: Abstractive text summarization, Vector space models, Semantic search. • ML & Software Development: Explainable AI, Fraud Surveillance service, Recommender systems. (Part of AI Incubator in Fidelity Center for Applied Technology (applied R&D team).
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Data Science Intern
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Jul 2018 - Dec 2018
Deployed a stacked LSTM model to predict the prices of the top hundred cryptocurrencies by market capitalization. The steps involved were - • Data scraping and collection • Preprocessing • Researching and engineering mathematical and domain-specific features • Building and testing deep learning models • Inference and storing the results in a database • Creating a batch job to asynchronously execute the prementioned tasks • Developing a REST API for the project •… Show more Deployed a stacked LSTM model to predict the prices of the top hundred cryptocurrencies by market capitalization. The steps involved were - • Data scraping and collection • Preprocessing • Researching and engineering mathematical and domain-specific features • Building and testing deep learning models • Inference and storing the results in a database • Creating a batch job to asynchronously execute the prementioned tasks • Developing a REST API for the project • Developing the front-end of the web application. The model was tested in a virtual cryptocurrency trading competition and its insights helped me rank in the 80th percentile. Show less Deployed a stacked LSTM model to predict the prices of the top hundred cryptocurrencies by market capitalization. The steps involved were - • Data scraping and collection • Preprocessing • Researching and engineering mathematical and domain-specific features • Building and testing deep learning models • Inference and storing the results in a database • Creating a batch job to asynchronously execute the prementioned tasks • Developing a REST API for the project •… Show more Deployed a stacked LSTM model to predict the prices of the top hundred cryptocurrencies by market capitalization. The steps involved were - • Data scraping and collection • Preprocessing • Researching and engineering mathematical and domain-specific features • Building and testing deep learning models • Inference and storing the results in a database • Creating a batch job to asynchronously execute the prementioned tasks • Developing a REST API for the project • Developing the front-end of the web application. The model was tested in a virtual cryptocurrency trading competition and its insights helped me rank in the 80th percentile. Show less
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Hindustan Petroleum Corporation Limited
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Oil and Gas
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700 & Above Employee
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Summer Intern
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May 2017 - Jul 2017
Developed a computational pipeline in Python to monitor and prevent pilferage and oil fraud. • Processed data from the Pipeline Intrusion Detection System (a Rs 500 lakhs system to detect vibrations over the oil pipeline near Bahadurgarh). • Identified the most frequent times of occurrence of warning alarms • Red flagged the locations prone to pipeline thefts so that appropriate measures could be taken. Developed a computational pipeline in Python to monitor and prevent pilferage and oil fraud. • Processed data from the Pipeline Intrusion Detection System (a Rs 500 lakhs system to detect vibrations over the oil pipeline near Bahadurgarh). • Identified the most frequent times of occurrence of warning alarms • Red flagged the locations prone to pipeline thefts so that appropriate measures could be taken.
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Education
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2022 - 2024
New York University
Master's degree, Data Science -
2015 - 2019
Birla Institute of Technology and Science, Pilani
B.E. (Hons.), Mechanical Engineering
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