Researcher2020 - PRESENTComputational Cognitive Development Group, Harvard
Technologies: Python, Deep Learning, Program Induction
- Developed machine learning models capable of leveraging "common sense reasoning" like human children and adults do.
Researcher2019 - PRESENTKnowledge Lab, UChicago
Technologies: Python, Deep Learning, Time-Series Analysis, Graph Learning
- Analyzed time-series social networks to discern the causal structure, build predictive models, and develop prescriptive models.
- Developed graphical models that learn over graph-like spaces to derive the causal structure of the graph.
- Developed graphical models that learn over graph-like spaces and make predictions about the future configurations of the graph.
- Developed graphical models that learn over graph-like spaces and make prescriptions about how to achieve future configurations of the graph.
Researcher2019 - PRESENTComputational Cognitive Science Group, MIT
Technologies: Python, Deep Learning, PyTorch
- Reimplemented a "Machine Theory of Mind" (MToM) to be used in future experiments.
- Analyzed the nuances of said MToM to determine it's learning process and determine if the model learns as portrayed or if the model exploits the latent capabilities of neural networks.
- Used the MToM in multi-agent settings to model coordination and planning with other agents and humans.
Researcher2018 - PRESENTNLP Group, UCF
Technologies: Deep Learning, PyTorch, Pandas, Matplotlib, Python
- Developed a questionnaire for use on Mechanical Turk to quantify how well summaries stick to the content in their source sentences.
- Developed a training methodology for summarization which generates more faithful summaries to their source articles.
- Performed analysis on all gathered data to determine how (1)"faithful" (doesn't introduce factual inconsistencies), (2) "covered" (only discusses information in the source sentences), and (3) what kind of sentence fusion generated the most ideal results.
Founder, Past President, Director2017 - PRESENT
Technologies: Deep Learning, Keras, TensorFlow, PyTorch, Python
- Served as a founding member of the UCF Data Science Team.
- Designed “Course” curriculum which is offered every semester.
- Coordinated and maintained [email protected] and Intel sponsorship, $2,500+/semester.
- Enabled uniform workshops and opened access to non-technical folk by writing an automation framework which runs the majority of managerial tasks for the group.
- Hosted 20+ workshops, introducing 40-100 students (each) to machine learning and data science techniques.
- Ran 15+ reading-group meetings where topics on computational cognitive science, implications of current machine learning, and current ML methods were discussed.
Researcher2018 - 2019Center for Research in Computer Vision, UCF
Technologies: Deep Learning, TensorFlow, Python
- Reimplemented multiple, state-of-the-art, action detection and segmentation Neural Networks.
- Worked towards developing a loss which would augment the training of the above networks by using less data.
Teaching Assistant, Grader2017 - 2019Udacity
Technologies: Deep Learning, Deep Reinforcement Learning, Natural Language Processing, Computer Vision, Self-Driving Cars, Robotics
- Provided mentorship to 300+ students about the listed technologies. Mentorship included career planning, clarifying technical details, among others.
- Graded various projects which fall into the above technologies.
Graduate Teaching Assistant2018 - 2018University of Central Florida (UCF)
Technologies: Computer Vision, Deep Learning, Keras, TensorFlow, Numpy
- Designed homework successfully reinforcing core deep learning concepts.
- Coordinated and designed infrastructure for students to complete assignments and final project, using the university’s supercomputer (SLURM batch manager).