Nicolas Morgan

• Magna Cum Laude
• LMU Seaver College of Science and Engineering Dean’s List:
  • 2018 - 2022
• 2nd Place HackerRanker: Git Gud Competition (2019 - open)
• 3rd Place HackerRank: Git Gud Competition (2020 - upperclassmen)
• 3rd Place HackerRank: Git Gud Competition (2021 - upperclassmen)
• LMU Achievement Award

• KECK (CS) Lab - TA/Lab Assistant, helped students complete course work and understand the basic programming paradigms, data structures, and algorithms
• LMU ACM - Loyola Marymount Association for Computing Machinery club member
• LMU EFH - Loyola Marymount Engineer for Humanity
• Ski and Snowboard Club - Helped facilited and organize group transportation and trip planning for club members

Programming (or other) Languages:

• Python, JavaScript, Swift, Java, C++, Solidity

Software & Tools:

• TensorFlow, Keras, PyTorch, scikit-learn, Spark, XGBoost, Numpy, Pandas, Polars, Docker, AWS (SageMaker, EC2, Lambda, RDS, DynamoDB), Snowflake, Databricks, Flask, ReactJS, NodeJS, Google Firebase, Django, SQL/noSQL Databases, RESTful architecture, Microsoft Office

Machine Learning, Artificial Intelligence, Multi-Agent Systems and Distributed AI, Natural Language Processing, Cognitive Systems Design, Data Science, Data Structures, Algorithms, Natural Language Processing, Software Architecture, Programming Languages, Databases, Networks and Internets, Computer Systems Organization, Interaction Design, Theory of Computation, Linear Algebra, Calculus (I, II, III), Methods of Proofs, Discrete Methods, Complex Analysis

Easily create a better Diet Tracking Experience for everyone, anywhere

• Collaborated closely with the co-founders to define the product roadmap, prioritize features, and architected the frontend, backed, and machine learning AI systems for B2C SaaS for research universities to leverage in scientific studies
• Designed and trained ML/AI models for meal recommendations take combined foods into meals, from USDA food database comprised of 2M+ samples, resulting in high performance, accuracy, and semantically relevant results
• Responsible for the deployment and maintenance of AWS production server for LLM, ML, and backend SQL functionalities
• Designed and implemented Azure LLM to help chatbot interactions with users assist with food/weight logging, recommendations, nutrition information, and comparisons between foods/meals
• Created MVP, designed UI, and implemented login and initial pages with functional features for the MVP IOS application

Travelers takes on the risk and provides the coverage you need to protect the things that are important to you — your home, your car, your valuables and your business — so you don’t have to worry. We have been around for more than 165 years and have earned a reputation as one of the best property casualty insurers in the industry because we take care of our customers.

• Implemented DGLM to model and predict home insurance premiums for dwellings across the Northeast region
• Developed and implemented new factors and added variables for condo modeling to allow for more accurate premiums
• Spearheaded implementation of Microsoft Copilot for the PI R&D department
• Responsible for migration of legacy SAS code and Machine Learning models to updated and modernized Python structure

"99% of the ethical life is being kind to people." - James Martin, S.J.

• Fall 2022: Computer Programming and Lab (CMSI 1010)
  • Presented and helped design two, hour and a half sessions per week to teach the basics paradigms and techniques
  • Taught data structures, basic algorithms, recursion, and object-oriented programming to undergraduate students

• Generative Chatbot
  • Design and implementation of two baseline models, a rule-based approach and information retrieval (IR)-based approach, then an encoder-decoder model to create generative automatic chatbot responses
• USDA Model Solutions Competition
  • Identify new approaches to linking Department of Agriculture (USDA) Economic Research Service (ERS)’s Food and Nutrient Database for Dietary Studies (FNDDS) to Information Resources, Inc. (IRI) retail store data in producing the Purchase to Plate Crosswalk (PPC).

Travelers takes on the risk and provides the coverage you need to protect the things that are important to you — your home, your car, your valuables and your business — so you don’t have to worry. We have been around for more than 165 years and have earned a reputation as one of the best property casualty insurers in the industry because we take care of our customers.

• Created a bidirectional LSTM neural network, using TensorFlow, to predict insurance claim severity
• Created two baseline models, Logistic Regression and Naive Bayes (using SciKit-Learn and Numpy), to compare advanced Neural Network
• Used NLP to analyze 100k+ claims with 100+ documents per claim to enhance efficiency of claim professionals
• Used AWS SageMaker environment to implement, modify, and translate between dev and prod environments

Cytokinetics is committed to our mission of developing potential medicines that may improve the healthspan of people living with cardiovascular and neuromuscular diseases of impaired muscle function.

• Analyzed and processed experimental data to find relationships between novel compounds and effects, using SciKit-Learn
• Migrated legacy, on-premise Oracle Database to new AWS Postgres Aurora to help company with future cloud scalability.
• Created new data pipeline using Numpy and Pandas to replace current Oracle Pipeline Pilot.
  • Coded scripts to replace Cytokinetics’ current data pipeline, which allowed Scientists to transfer and store experimental data in the newly created AWS database.

"Keck is not a place, it is a people" - Random Keck Regular

• Spring 2021: Algorithms (CMSI 282)
  • Held remote office hours on ZOOM, 6 hours per week. Coached and assisted sophomores and juniors to help them develop their fundamental algorithmic techniques, including:
    • Dynamic Programming, BFS, DFS, A* Search, Mini-max Search, Memoization, CSPs, etc
• Fall 2021: Computer Programming and Lab (CMSI 1010)
  • Held in person office hours on campus, teaching and mentoring students of all ages who needed help supplemental help.
  • Attended in person classes as a teaching assistant for two different sections to enhance the students learning environment.

• Programmed proof-of-concept visual monitoring system, using Python, Raspbery Pi, OpenCV, and SciKit-Learn with a camera module, to provide the Scientists a 24/7 visual imaging to allow scientists to constantly monitor test subjects health and condition.
• Started prototyping for updating current, legacy inventory management systems to a web application using Django and AWS.

• Made food, cleaned dishes, delivered pizza, and worked as a cashier.
• Responsible for all aspects of customer service and experience.