Microsoft Research AI Software Engineer
As a Microsoft Research AI Resident, developed a state-of-the-art deep neural-net conversational agent model in Pytorch. The code and final draft are now publicly available. I also co-authored TwoPaneView for React Native which enables the dynamic rendering of Views on dual screen devices like the Microsoft Surface Duo.
Sept. 2019 - present
Solvvy Software Engineering Intern
As a software engineering intern at Solvvy, developed and trained large deep neural network models on hundreds of thousands of GCloud Kubernetes-managed, PostgreSQL-stored ticket queries to classify and draw insights from text data. Also wrote a Facebook Messenger Chat Plug-in interface for Solvvy's chatbot platform.
Jul. 2018 - Sept. 2018
Stanford Center for Design Research Research Assistant
Developed a model for automatic classification of dialogue acts in multiple-person design thinking team conversations by using Bidirectional Neural Networks.
Jun. 2017 - Jun. 2018
Stanford CS106B ACE Head Teaching Assistant
I was in charge of CS106B ACE which is an extra section for more in-depth overview of C++ topics and class material.
Sept. 2018 - Jun. 2019
Stanford Computer Science Research Assistant
Under the leadership of Stanford professor Silvio Savarese helped accomplish comprehensive 3D representation of indoor spaces by using multi-task convolutional neural networks trained on hundreds of thousands of indoor images
MS and BS in Computer Science (AI, Systems)
IDN Dialogue Act Classification With Conditional Random Fields and Recurrent Neural Networks
We set a new standard of accuracy for the task of dialogue act classification on the Interaction Dynamics Notation dataset through the use of Conditional Random Fields in addition to LSTM Recurrent Neural Networks.
Automatic IDN Dialog Act Tagging of Design-Team Conversations
This paper explores the effectiveness of leveraging transfer learning in neural networks for the classification of conversations into their respective dialog acts. For this task, we use as our tags the Interaction Dynamics Notation (IDN) developed at the Stanford Center for Design Research.
Homero Roman Roman
Temporal Analysis of International Relations Networks
In this project, we explore structural properties of the alliance, war, and sentiment graphs of the the Correlates of War dataset, including the roles of individual nodes, structural motifs, and graph-level communities. In contrast to most previous work, we also explicitly analyze changes to the graphs over time.
Homero Roman Roman Colin P. Gaffney, Luis F. Varela
Automatic cancer development prediction based on classification of mass lesions in mammograms
In this project, diagnosis is done through multiclass classification of mamammographs into normal, benign, and cancerous while the prevention characterization is done by the automatic prediction of cancer development through reinforcement learning.
Homero Roman Roman