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📰 Resume pdf

⚡ Summary

How I got here?

  • Neural networks are the reason I started my PhD in computer science.
  • The professor I talked asked me if I wanted to work on natural language processing and neural network.
  • The notion of neural networks sounded very exciting to me.
  • That’s when I knew that is what I want to do for my career.

Interest areas: Neural Networks, Deep Learning, Natural Language Processing, Reinforcement Learning, Computer Vision, Scaling Machine Learning.

Research:

  • My main research area is in NLP with focus on dialogue generation with persona.
  • I use the Friends TV corpus to train language models that can capture each of the main six characters personas.
  • Imagine a chatbot that sounds like Joey or Chandler.
  • This will make chatbots systems more engaging and allow shifting personas depending on a customer's mood which significantly increases customer experience.

In my free time:

  • I like to share my knowledge on NLP: I write tutorials from scratch on state-of-the-art language models like Bert and GPT2 with over 10k views. Check them out here.
  • Contribute to open-source software on GitHub – Hugging Face Transformer and Dataset library.
  • Technical reviewer for one of the first books published on transformers models for NLP. The book is called Transformers for NLP in Python, by Denis Rothman.
  • Most recently I was invited to be a technical reviewer for the next edition of the Transforms for NLP book.
  • I delivered a webinar on my tutorial GPT2 for Text Classification with 300+ participants and 50 of them requested me to publish more on this topic.

💼 Experience

Data Scientist, Part-Time

TCF Bank – Huntington Bank | Machine Learning Operations

  • Translated credit risk models into python and R with unit testing implementation.
  • Built a Proof of Concept (PoC) application around Machine Learning (ML) Operations (MLOps) framework on Kubernetes: automated model registry and deployment using MLFlow, data pipelines with Airflow, API model calls using FastApi and CI/CD pipeline in Jenikins.
  • Helped transition from MLOps solution vendor that reduced model deployment cost to zero.

Jan 2021 – Present

Data Scientist Intern

State Farm | Enterprise Data & Analytics

  • Created a PoC application for stock portfolio optimization using Reinforcement Learning (RL) in Python.
  • Built a RL framework tool that makes it transferable in different business areas to help create RL environments and models.
  • Helped create a PoC application that optimizes claims automatic payment process using RL in Python.

May 2020 – July 2020

Data Scientist – Machine Learning Engineer

University of North Texas (UNT) | Research Information Technology

  • Helped research labs with model implementations, debugging and attract more funding.
  • Helped maintain latest ML and deep learning frameworks for University of North Texas High Performance Computing (HPC) center.
  • Created and held workshops and tutorials on NLP and using HPC services that helped increased userbase by 20%.

Sep 2018 - May 2020

Machine Learning Engineer Intern

State Farm | Enterprise Data & Analytics

  • Automated modeling evaluation in python: build baselines and compare against target model reducing deployment timeline by 90%.
  • Wrote and published a python package for automatic model evaluation that can be used across different departments.
  • Built python program to generate HTML reports on baseline model evaluation and data analysis plots integrated in a CI/CD pipeline.

May 2019 – July 2019

Data Scientist Intern

State Farm | Enterprise &Data Analytics

  • Introduced GPUs in ML tutorials that speed up training by over 50%.
  • Used Natural Language Processing (NLP) tools in python to extract meaningful features from claims text data that were used in addition to existing claims feature to increase model baseline performance in predicting claims duration.

May 2018 – August 2018

Teaching Assistant – Computer Science

University of North Texas (UNT) | Department of Computer Science

  • Building and debugging C/C++ coding assignments and help coordinate coding exams. 􏰀* Peer mentor and grader for students in Computer Science basic and advance courses.

Sep 2017 – May 2018, Sep 2020 – May 2021

Artificial Intelligence – Machine Learning Researcher

University of North Texas (UNT) | Department of Computer Science

  • Implement concepts in python from research papers related to NLP and Computer Vision (CV). 􏰀* Building state of the art deep learning models in python in the domains of language modeling and image classification.

Jan 2017 - Present

🎓 Education

📜 Doctor of Philosophy (PhD) in Computer Science

University of North Texas (UNT) | Department of Computer Science

Research Areas: ML, deep learning, NLP, CV.

Dec 2021 | GPA 4.0

📜 Master of Computer Science

University of North Texas (UNT) | Department of Computer Science

Relevant Coursework: Machine Learning, Deep Learning, Big Data, Natural Language Processing, Image Processing.

Dec 2019 | GPA 3.9

🎣 Skills

Proficient: Python, Tensorflow, PyTorch

Need Warmup: Java, C, C++, Matlab, R

Intermediate: SQL, Docker, AWS, Swift, Android, Hadoop, HTML

👥 Reference

Dr. Rodney D. Nielsen

Associate Professor - Director HiLT Lab University of North Texas – Computer Science Engineer

📬 Email: Rodney.Nielsen@UNT.edu