Dennis Loevlie

Experience

• 

  West Virginia University

  Jan 2019 - Aug 2019

  My experience as an undergraduate researcher was extremely broad. I worked under Prof. Lima in the CODES group. The main projects that I worked on are listed below:• My first project involved the EPA’s chemical process sustainability software, GREENSCOPE, and its potential applications. • My second and more complex project involved mathematical modeling and optimization of large-scale ion transport membranes as an alternative to cryogenic air separation units for oxygen production. This involved MATLAB programming, ASPEN Plus modeling, as well as, building a custom mathematical model for the membrane in the simulation software SimCentral. Show less

  • Undergraduate Researcher

    Apr 2017 - Aug 2019

  • Student Grader

    Jan 2019 - May 2019
• 

  Carnegie Mellon University

  Dec 2019 - Jan 2021

  Graduate Student Researcher

  During my time at CMU, I was highly active in Dr. John Kitchin's research group. A few of my major contributions are listed below:• Recreated image analysis tools in Python (originally in Mathmatica) to be faster and more intuitive. • Developed a Python package, nb_search, to efficiently sort through, locate and open Jupyter notebook files. • Trained a CNN to accurately predict the relative amount of residuals deposited in the bottom of an experimental well.• Regressed parameters and used them to cluster different bimetallic catalysts (used in the Hydrogen Evolution Reaction) into 5 distinct groupings. Show less

• 

  AithELITE

  Jan 2021 - Jun 2021

  Data Scientist/Software Engineer

  • Developed web scraping scripts using Beautifulsoup and Selenium to automate data retrieval and keep the data up to date• Automated the data/feature engineering with Numpy and Pandas• Applied Machine Learning algorithms using Numpy and Sklearn to generate intelligent predictions from the data• Built and maintained relational (MySQL) and graph (Neo4J) databases, hosted on AWS• Built the front and backend of the NovAItion EliteAI website with Django, hosted on AWS

• 

  University of Pittsburgh

  Jun 2021 - Dec 2022

  Research Assistant

  At the University of Pittsburgh, I researched under Prof. Mpourmpakis (Yanni) in the CANELa group. My main contributions are listed below:• Developed a novel method for calculating cohesive energies of metal nanoparticles that led to a 71% improvement to the previous model. • Applied quantum/statistical mechanics through Density Functional Theory, Boltzmann statistics, and mixed integer optimization using the genetic algorithm to better understand structure property relationships for metal nanoparticles. • Organized and presented in several machine learning and software development meetings within the CANELa research group. Notable presentations include: version control using git/GitHub, an introduction to PyTorch and logistic regression, creating interactive visualizations with plotly and dash, and developing custom Python packages. • Mentored members of the group about ML fundamentals, building models with PyTorch, and evaluating ML results. Show less

• 

  KEF Robotics

  Jan 2023 - Aug 2024

  At KEF Robotics, I spearheaded the development and integration of advanced deep learning solutions, focusing on Universal Image Segmentation, object detection and Monocular Depth Prediction. My responsibilities spanned the entire pipeline: from data preprocessing to the selection, implementation, optimization, and integration of state-of-the-art (SoTA) models using PyTorch and PyTorch Lightning.Project 1: I led the machine learning efforts for a client-focused ground-vehicle/tethered UAS reconnaissance project, showcasing KEF's aerial autonomy within an Unreal Engine simulation. Utilizing the Mask2Former model with a Swin-L backbone, I was able to accurately segment challenging obstacles like power lines. This implementation not only marked a significant stride in infrared image segmentation but also set a new benchmark for KEF's capabilities. A pull request I made on the Hugging Face Transformers library enabling PyTorch 2.0 integration led to a 23% boost in inference speed, and a custom ResNet50 backbone further enhanced speed by 45% with a slight 4% accuracy trade-off.Project 2: I have the privilege of leading the NAMC 10x24 initiative at KEF Robotics, a significant project with a budget of $500,000 and a one-year timeline that combines advanced robotics with artificial intelligence to enhance our mission-critical operations. While my primary technical focus lies in the integration of object detection and state-of-the-art Monocular depth capabilities onto the two separate commercial drones for real-world hazard detection and avoidance, my overarching responsibility is to lead and manage a dedicated team of five engineers. Show less

  • Senior Computer Vision and Machine Learning Engineer

    May 2024 - Aug 2024

  • Computer Vision Engineer

    Jan 2023 - May 2024
• 

  Tufts University

  Aug 2024 - now

  ML Researcher in the Hughes Lab

  Working on multiple instance learning for 3D neuro-images. This work is directly applicable to video understanding problems. Currently developing ways to improve attention. Generally, my research is applicable to machine learning problems with limited amounts of labeled data.