Daniel Perez

London, UK · 2cdanielperez@gmail.com

I'm currently a software engineer at Google. I received my PhD in Modeling, Simulation and Visualization Engineering at Old Dominion University in 2021. My main areas of expertise are machine learning, computer graphics and computational photography.

Experience

Software Engineer

Google

Technical leader of Android Backup & Restore 0P/1P team. Coordinating engineer work and communication with Android teams that use the B&R framework to backup their data.

Part of the computational photography and image editing team on Google Photos Android. Building and maintaining ML-powered effects used by millions: Magic Eraser, Photo Unblur, Best Take, Auto-Enhance with Real Tone.

Other projects include redesigning the real-time rendering framework of the image editor, showcasing computational effects in other surfaces of the app, and fast experimentation to increase usage of the editor.

August 2021 - Present

Graduate Research Assistant

Old Dominion University

Research on the areas of computer graphics and deep learning.

Leader of the MSVE Demo team.

Teacher assistant of Computer Graphics and Intro To Game Development.

August 2016 - May 2021

Student Chair in the MSV Student Capstone Conference

Old Dominion University and Virginia Modeling, Analysis and Simulation Center (VMASC)

Handling all communication and coordination between faculty at ODU and administration at VMASC.

Responsible for digital media, marketing, website development, student coordination, conference handbook publication, and track chair coordination.

January 2017 - May 2021

Software Engineer Intern

Google

Research on machine learning techniques to improve Draco: a library for compression and decompression of 3D geometric meshes.

Successfully reduced prediction error by 20-40% with respect to Draco’s parallelogram predictors.

May 2020 - August 2020

Studio Tools Research Intern

Pixar Animation Studios

Research on machine learning techniques focused on the automatic generation of 3D models.

Development of a pipeline for the parameterization of 3D models into geometric images without loss of information.

May 2019 - August 2019

Virtual Reality Intern

Navteca

Virtual Reality development for Samsung Gear VR and Oculus Rift.

Data Processing using Amazon Web Services.

March 2016 - June 2016

Education

Doctor of Philosophy in Modeling, Simulation and Visualization Engineering

Old Dominion University

Dissertation: Feature Extraction and Design in Deep Learning Models

GPA: 3.98

August 2016 - May 2021

Master of Engineering in Modeling, Simulation and Visualization Engineering

Old Dominion University

GPA: 3.98

August 2016 - August 2019

Advance Engineering Certificate in Cyber systems Security

Old Dominion University
August 2019

Bachelor of Science in Computer Engineering

Old Dominion University
Minor: Computer Science

GPA: 3.91

August 2013 - May 2016

Skills

Computer Skills
  • Programming Languages: Python, MATLAB, C/C++, Java, C#, OpenGl, Tensorflow, Keras, Pytorch
  • Development Tools: Unity, Houdini, Maya, USD, QT, Git, Android Studio, Microsoft Visual Studio, Amazon Web Services
  • Development Platforms & Devices: Windows, Linux, Android, Oculus Rift, HTV Vive, Microsoft HoloLens, Galaxy Gear VR
Languages
  • Spanish - Native Language
  • English - Proficiency

Publications

Journal Papers
  • D. Perez, Y. Shen, and J. Li. "Mesh Convolutional Networks With Face and Vertex Feature Operator." In IEEE Transactions on Visualization and Computer Graphics 2021.
  • M. Hasan, D. Perez, Y. Shen, and H. Yang. "Distributed Microscopic Traffic Simulation with Human-in-the-Loop Enabled by Virtual Reality Technologies." In Advances in Engineering Software 2021.
  • B. Ayhan, C. Kwan, B. Budavari, L. Kwan, Y. Lu, D. Perez, J. Li, D. Skarlatos and M. Vlachos. "Vegetation Detection Using Deep Learning and Conventional Methods." In Remote Sensing. 2020.
  • C. Kwan, B. Ayhan, B. Budavari, Y. Lu, D. Perez, J. Li, S. Bernabe and A. Plaza. "Deep Learning for Land Cover Classification Using Only a Few Bands." In Remote Sensing. 2020.
  • D. Perez, K. Islam, V. Hill, R. Zimmerman, B. Schaeffer, Y. Shen and J. Li. "Quantifying Seagrass Distribution in Coastal Water with Deep Learning Models." In Remote Sensing. 2020.
  • C. Kwan, L. Hagen, B. Chou, D. Perez, J. Li, Y. Shen and K. Koperski. "Simple and effective cloud- and shadow-detection algorithms for Landsat and Worldview images." In Signal, Image and Video Processing. 2019.
  • D. Perez, M. Hasan, Y. Shen and H. Yang. "AR-PED: A Framework of Augmented Reality Enabled Pedestrian-in-the-Loop Simulation." In Simulation Modeling Practice and Theory. 2019.
  • C. Kwan, X. Zhu, F. Gao, B. Chou, D. Perez, J. Li, Y. Shen, K. Koperski and G. Marchisio. "Assessment of Spatiotemporal Fusion Algorithms for Planet and Worldview Images." In Sensors, 18(4), 1051. 2018.
  • E. Oguslu, K. Islam, D. Perez, V. Hill, W. Bissett, R. Zimmerman and J. Li. "Detection of Seagrass Scars Using Sparse Coding and Morphological Filter." In Journal of Remote Sensing of Environment. 2018.
  • H. Yang, Y. Shen, M. Hasan, D. Perez and J. Shull. "A Framework for Interactive M3 Visualization of Microscopic Traffic Simulation." In Journal of the Transportation Research Board. 2018.
Conference Papers
  • C. Kwan, B. Chou, J. Yang, D. Perez, Y. Shen, J. Li and K. Koperski. "Fusion of Landsat and Worldview Images." In SPIE Defense + Commercial Sensing. 2019.
  • D. Perez. "Capsule Networks: Review of the Structures and Visualization of Features." In 13th Annual Modeling, Simulation & Visualization Student Capstone Conference. 2019.
  • K. Islam, D. Perez and J. Li. "A Transfer Learning Approach for the 2018 FEMH Voice Data Challenge." In IEEE International Conference on Big Data. 2018.
  • D. Perez, Y. Lu, C. Kwan, Y. Shen, K. Koperski and J. Li. "Combining Satellite Images with Feature Indices for Improved Change Detection." In IEEE Ubiquitous Computing, Electronics & Mobile Communication Conference. 2018.
  • Y. Lu, D. Perez, M. Dao, C. Kwan and J. Li. "Deep Learning with Synthetic Hyperspectral Images for Improved Soil Detection in Multispectral Imagery." In IEEE Ubiquitous Computing, Electronics & Mobile Communication Conference. 2018.
  • R. Hoque, K. Islam, D. Perez, V. Hill, B. Schaeffer, R. Zimmerman, and J. Li. "Seagrass Propeller Scar Detection using Deep Convolutional Neural Network." In IEEE Ubiquitous Computing, Electronics & Mobile Communication Conference. 2018.
  • D. Perez, K. Islam, V. Hill, B. Schaeffer, R. Zimmerman and J. Li. "DeepCoast: Quantifying Seagrass Distribution in Coastal Water through Deep Capsule Networks." In Chinese Conference on Pattern Recognition and Computer Vision. 2018.
  • K. Islam, D. Perez, V. Hill, B. Schaeffer, R. Zimmerman and J. Li. "Seagrass Detection in Coastal Water through Deep Capsule Networks." In Chinese Conference on Pattern Recognition and Computer Vision. 2018.
  • D. Perez, K. Islam, V. Hill, B. Schaeffer, R. Zimmerman and J. Li. "Deep Learning for Effective Quantification of Seagrass in Coastal Areas." In 12th Annual Modeling, Simulation & Visualization Student Capstone Conference. 2018.
  • D. Perez, Y. Shen, J. Dayanghirang, J. Li, S. Wang, and Z. Zheng. "Deep Learning for Pulmonary Nodule CT Image Retrieval- An Online Assistance System for Novice Radiologists." In IEEE International Conference on Data Mining (Workshop). 2017.
  • D. Perez, D. Banerjee, C. Kwan, M. Dao, Y. Shen, K. Koperski, G. Marchisio and J. Li. "Deep Learning for Effective Detection of Excavated Soil Related to Illegal Tunnel Activities." In IEEE Ubiquitous Computing, Electronics & Mobile Communication Conference. 2017.
  • D. Perez. "A Systems Dynamic Approach to Predict the Trend of Superhero Movies over Time." In 11th Annual Modeling, Simulation & Visualization Student Capstone Conference. 2017.
Posters, Presentations and Abstracts
  • D. Perez, M. Hasan, Y. Shen and H. Yang. "AR-PED: Augmented Reality Enabled Pedestrian-in-the-Loop Simulation." In Transportation Research Board Annual Meeting. 2019.
  • H. Yang, Y. Shen, M. Hasan, D. Perez and J. Shull. Interactive M3 Visualization of Microscopic Traffic Simulation. In 12th Annual Modeling, Simulation & Visualization Student Capstone Conference. 2018.
  • H. Yang, Y. Shen, M. Hasan, D. Perez and J. Shull. A Framework for Interactive M3 Visualization of Microscopic Traffic Simulation. In Transportation Research Board Annual Meeting. 2018.
  • M. Hasan, D. Perez, Y. Shen and H. Yang. "Enhancing Microscopic Traffic Simulation with Virtual Reality." In 11th Annual Modeling, Simulation & Visualization Student Capstone Conference. 2017.
  • D. Perez, Y. Shen, J. Dayanghirang, J. Li, S. Wang, and Z. Zheng. "Deep Learning for Pulmonary Nodule CT Image Retrieval- An Online Assistance System for Novice Radiologists." In BioImage Informatics Conference. 2017.

Awards