Nick Locascio

Deep Learning Consultant

Booth AI

Co-Founder, CEO

Standard Cognition 

I joined Standard AI as employee #7 and wore many hats throughout our unicorn growth cycle. I wrote critical pieces of our algorithms and inference stack, led and grew our Machine Learning Teams, spearheaded our Synthetic Data initiatives, landed 10+ machine learning models into production, and drove key metrics and ml product launches.

Director Of Engineering

Symantec

Built deep learning systems for dynamic cyber threat and insurance modeling.

Massachusetts Institute of Technology

Published 2 Machine Learning Papers. Founded and lectured MIT's Deep Learning course, 6.S191.

Papers:
[1] High-Risk Breast Lesions: A Machine Learning Model to Predict Pathologic Upgrade and Reduce Unnecessary Surgical Excision
Journal of Radiology '17

[2] Neural Generation of Regular Expressions from Natural Language with Minimal Domain Knowledge, EMNLP '16

Graduate Researcher

Perch

Developed deep learning computer vision models for early stage fitness technology startup.

Deep Learning Engineer

Pinterest

Worked on Machine Learning Recommendations team building big data prediction models with Hive+Hadoop.

Machine Learning Engineer

Fitbit

I worked on the iOS team doing various feature work.

Software Engineer

Mystery Snap

Mystery Snap was an ephemeral photo sharing iOS app.

Acquired +250,000 users. +3 million photos sent.

Mystery Snap held the #1 spot in the Norway Photo & Video Category for over two weeks.

Founder

Monster Cats

Monster Cats was a 2D action runner iPhone game.

Monster Cats reached #56 on the App Store
for Adventure Games and made the All Games Top 300 the first week of launch.
4.5 Star Rating. +150,000 downloads

Co-Founder / CEO at Booth AI (YC W23)

DoorDash

Member of Technical Staff

Standard AI

Staff ML Engineer

Sr ML Engineer

ML Engineer

Springboard

- Mentored students for a data science career track
- Advised and approved capstone projects

Mentor - Data Science Career Track

FogHorn Systems, Inc

- Developed an object detection POC for a customer to be run on a
Raspberry PI which is targeted to improve compliance. Implemented the YOLO
architecture using Keras and Tensorflow.

- Collaborated with customer to define requirements for 8 separate processes in an
industrial factory to gain insights into capacitor failures. Wrote scripts to gather
data and enable machine learning using a proprietary streaming functional
reactive language. Insights from the data increased production yield by 5%.

- Designed the backend of a machine learning application that reacted to streaming
data and published predictions.

- Founded a reading group for ML research papers. Served as the facilitator for
deep learning topics.

Data Scientist

Galvanize Inc

Data Scientist in Residence

Data Scientist at FogHorn Systems

Galvanize Data Science Immersive graduate

Computer Engineering undergrad - UC San Diego

Passion for technology, especially in deep learning. 

Self-motivated, self-starter that quickly picks up new concepts with the ability to apply them in software development projects.

taplio

The Battle

Nick Locascio

Kenneth Kihara

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