Hello I'm

Parag Dakle

Senior Data Scientist at Fidelity Investments, Boston

I am a Senior Data Scientist at Fidelity Investments. I recently completed my Ph.D. in Computer Science at the University of Texas at Dallas.
My main research interests include, and are not limited to, natural language processing, cognitive science, and machine learning.
When I am not working I like to travel, cook, write and am a Chelsea FC fan!

Experience

Fidelity Investments

Data Scientist Jan 2022 - present
  • Working on various NLP problems in the Financial Domain

The University of Texas at Dallas

Teaching Assistant Aug 2021 - Dec 2021
  • Artificial Intelligence and Natural Language Processing (Fall 2021)

Lymba Corporation

Software Engineer Intern (PT) Jun 2021 - Aug 2021
  • Created a system architecture for Open-Domain Question Answering and developed the Information Retrieval component of the system
  • Python
  • Question Answering
  • Information Retrieval
  • Deep Learning

The University of Texas at Dallas

Teaching Assistant Aug 2020 - May 2021
  • Artificial Intelligence and Web Programming Languages (Fall 2020)
  • Artificial Intelligence and Natural Language Processing (Spring 2021)

Lymba Corporation

Software Engineer Intern (PT) May 2020 - Aug 2020
  • Created a Word Sense Disambiguation tool using word embeddings and a rule based system
  • Designed a benchmarking framework for a Python based machine learning framework
  • Python
  • Java
  • Shell
  • Jenkins
  • NER

The University of Texas at Dallas

Teaching Assistant Aug 2019 - May 2020
  • Computer Networks (Fall 2019)
  • Object Oriented Analysis and Design (Spring 2020)

Lymba Corporation

Software Engineer Intern Jun 2019 - Aug 2019
  • Created a task agnostic machine learning framework to facilitate integration of Python deep learning tools with the existing Java NLP pipeline
  • Designed Named Entity Recognition system using BERT and BiLSTM in Pytorch.
  • Python
  • Java
  • Deep Learning
  • NER

The University of Texas at Dallas

Teaching Assistant Aug 2018 - May 2019
  • Design and Analysis of Algorithms (Fall 2018)
  • Artificial Intelligence (Spring 2019)

Lymba Corporation

Software Engineer Intern May 2018 - Aug 2018
  • Implemented a semi-supervised topic-based keyword extraction system using word embeddings giving 2x accuracy and 8x time reduction over the existing system
  • Designed algorithms to extract lexicons and generate BRAT configurations from an ontology.
  • Java
  • NER
  • Jenkins

The University of Texas at Dallas

Teaching Assistant Aug 2017 - May 2018
  • Web Programming Languages (Fall 2017 and Spring 2018)

Bottle Rocket

Software Engineer Intern Jun 2017 - Aug 2017
  • Fixed two blocker bugs for the Qdoba Android App. Updated Google and RxJava libraries used by the project
  • Implemented multiple UX/UI stories for two more Android applications which have been released on Play Store
  • Followed SCRUM practice, GIT version control and JIRA for all the projects
  • Finished Kotlin Level 1 training.
  • Android
  • Kotlin

Muffin

Full Stack Developer Feb 2016 - Jul 2016
  • Engineered and developed the Muffin Android Application
  • Developed Spring-Boot modules, and assisted in designing the product system architecture, user experience and interface.
  • Android
  • Spring-Boot
  • System Architecture

Great Software Laboratory

Software Engineer Jul 2014 - Jan 2016
  • Developed an audio and text communication web application Atklique using HTML, CSS, Javascript, XMPP and SIP
  • Researched integrating WebRTC with Skreen.me to transform the client-server architecture of the later to peer-to-peer
  • Found points of failure in an existing system and successfully scaled it up by more than 200%. Redesigned the system architecture and streamlined the communication between different processes
  • Created a medical data analytics web application using D3, HTML, CSS, Javascript, PHP, and MySQL
  • Mentored a junior employee for developing a web-based graphical user interface for SIPp tool
  • Worked on developing the base PHP server and Node.JS signaling server
  • Investigated the WebRTC protocol and modified it for an Elderly Video Calling application.
  • HTML5
  • CSS
  • Angular
  • WebRTC
  • Php
  • System Architecture
  • Shell
  • Python
  • VoIP

Spectrum Education

Mathematics Tutor Mar 2012 - Jun 2013
  • Worked as a Mathematics Tutor for Class X (Geometry) and Class XII (Probability and Statistics)
  • Developed classroom content for mathematics, conducted and assessed tests.

Education

Doctorate Degree The University of Texas at Dallas

2017-2021

Major: Computer Science

GPA: 3.95/4.00

Masters Degree The University of Texas at Dallas

2016-2021

Major: Computer Science

GPA: 3.95/4.00

Bachelors Degree Savitribai Phule Pune University

2010-2014

Major: Computer Engineering

GPA: 73/100 First Class with Distinction

Publications

2024
Jetsons at FinNLP 2024: Towards Understanding the ESG Impact of a News Article using Transformer-based Models

Parag Pravin Dakle, Alolika Gon, Sihan Zha, Liang Wang, SaiKrishna Rallabandi, and Preethi Raghavan, FinNLP, LREC-COLING, 2024.

Self-training Strategies for Sentiment Analysis: An Empirical Study

Haochen Liu, Sai Krishna Rallabandi, Yijing Wu, Parag Pravin Dakle, and Preethi Raghavan, Findings of the ACL: EACL, 2024.

2023
BlendSQL: A Scalable Dialect for Unifying Hybrid Question Answering in Relational Algebra

Parker Glenn, Parag Pravin Dakle, Liang Wang, and Preethi Raghavan, Arxiv, 2023.

Towards Leveraging LLMs for Conditional QA

Syed-Amad Hussain, Parag Pravin Dakle, SaiKrishna Rallabandi, and Preethi Raghavan, Arxiv, 2023.

An Empirical Study on Instance Selection Strategies in Self-training for Sentiment Analysis

Haochen Liu, Sai Krishna Rallabandi, Yijing Wu, Parag Pravin Dakle, and Preethi Raghavan, Arxiv, 2023.

Correcting Semantic Parses with Natural Language through Dynamic Schema Encoding

Parker Glenn, Parag Pravin Dakle, and Preethi Raghavan, 5th Workshop on NLP for Conversational AI Workshop at ACL, 2023.

Ner4Opt: Named Entity Recognition for Optimization Modelling from Natural Language

Parag Pravin Dakle, Serdar Kadioglu, Karthik Uppuluri, Regina Politi, Preethi Raghavan, SaiKrishna Rallabandi, and Ravisutha Srinivasamurthy, CPAIOR, 2023.

HeySQuAD: A Spoken Question Answering Dataset

Yijing Wu, SaiKrishna Rallabandi, Ravisutha Srinivasamurthy, Parag Pravin Dakle, Alolika Gon, Preethi Raghavan, Arxiv, 2023.

2022
A Hybrid Model for Named Entity Recognition in Optimization Problmes

Parag Pravin Dakle, Serdar Kadioglu, Karthik Uppuluri, Regina Politi, Preethi Raghavan, SaiKrishna Rallabandi, and Ravisutha Srinivasamurthy, NL4Opt Competition, NeurIPS, 2022.

Understanding BLOOM: An empirical study on diverse NLP tasks

Parag Pravin Dakle, SaiKrishna Rallabandi, and Preethi Raghavan, Arxiv, 2022.

Jetsons at the FinNLP-2022 ERAI Task: BERT-Chinese for mining high MPP posts

Alolika Gon, Sihan Zha, SaiKrishna Rallabandi, Parag Pravin Dakle and Preethi Raghavan, FinNLP, EMNLP, 2022.

Using Transformer-based Models for Taxonomy Enrichment and Sentence Classification

Parag Pravin Dakle, Shrikumar Patil, SaiKrishna Rallabandi, Chaitra Hegde, and Preethi Raghavan, FinNLP, IJCAI, 2022.

2021
Knowledge extraction from email conversations and its application to question answering

Parag Pravin Dakle Ph.D. Thesis, University of Texas at Dallas, 2021.

2020
CEREC: A Corpus for Entity Resolution in Email Conversations

Parag Pravin Dakle, and Dan I Moldovan, COLING, 2020.

A Study on Entity Resolution for Email Conversations

Parag Pravin Dakle, Takshak Desai and Dan I Moldovan, LREC, 2020.

Joint Learning of Syntactic Features Helps Discourse Segmentation

Takshak Desai, Parag Pravin Dakle and Dan I Moldovan, LREC, 2020.

2018
Generating Questions for Reading Comprehension using Coherence Relations

Takshak Desai, Parag Pravin Dakle and Dan I Moldovan, Proceedings of the 5th Workshop on Natural Language Processing Techniques for Educational Applications, 2018.