BONNIE HINES

AI RESEARCH DEVELOPER

Los Angeles/San Jose, CA 408-***-**** ad11rr@r.postjobfree.com

PROFESSIONAL

SUMMARY .

Analytical computer scientist skilled at collecting, processing, and executing statistical data analysis. Developer of AI object detection models in Python and experienced at integrating into new teams to quickly remedy bottleneck issues under tight deadlines. Pentesting hobbyist and actively improving with hackthebox.com by gaining root privilege on over 30 machines. Active volunteer at OSINT based ATTII, a community that provides details on human traffic cases. Member of UC Davis’ Cyber Security Club.

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SKILLS

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TOOLS AND LIBRARIES TECHNICAL KNOWLEDGE LANGUAGES

● Git

● Gdb

● OOP

● Latex

● Regex

● Tensorflow

● Pytorch

● ONNX

● Staff training

● Junior staff

management

● Database

development and

management

● Data Structures

● CNN

● C/C++

● R

● Python

● Go

● Javascript

● HTML

● CSS

● SQL

EXPERIENCE

Machine Learning Manager

Uniquify San Jose, CA

Machine Learning

Researcher

Uniquify San Jose, CA

August 2022 – Current

● Designed analysis script to quantitatively compare 10 different object detection and image segmentation models based on 15 image features..

● Managed and trained a team of 4 interns to train fully automated yolov4 models with custom data augmentations and learning rates schedulers.

● Designed video streaming app to select people and objects from video in real time using yolo Neural Network

● Led a team of developers to successfully quantize yolov3 weights to paper accuracy

August 2020 – Current

● Worked with a group of developers to create a python machine learning framework

● Wrote a program to detect court points in a basketball game

● Led a team of 5 developers to build a network of over 15 models to label image data

Machine Learning Intern

Uniquify San Jose, CA

Data Analyst

INV Tech New York, NY

Research Intern

UCD . Research Center Davis, CA

August 2020 – July 2021

● Converted PyTorch face recognition model, faceboxes to a TensorFlow framework

● Used data visualization tools to create charts to compare performance of models

August 2020 – February 2021

● Helped front-line teams make data-driven decisions by offering current, relevant insights

● Increased usefulness of analytical reports with enhanced data mining techniques

● Managed output and dashboard to effectively report on key business intelligence

August 2020 – February 2021

● Designed a web scraper to regularly check for and download newly published batch files

● Wrote program to clean and sort ocr data from the Library of Congress based on metadata

● Used NLP topic modeling and k-nearest neighbor to build a model from corpus database

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EDUCATION .

December 2019 Bachelor of Science (B.S.) – Computer Science University of California at Davis, Davis, CA

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TECHNICAL

ADVANCEMENTS .

● VFS (C) Created a virtual FAT file system with basic bash commands that utilized a multi-thread FIFO queue with a semaphore lock and signal handler

● Shell (C) Implemented a bash command Shell that parsed multiple command requests for piping, rerouted the file descriptors that used syscalls and executed primary UNIX commands

● Best-Curve Fit (Python) Implemented the least-squares formula to create a program which generated multiple functions that predicted linear regression trend-lines; by constructing a function that selected the best-fit equation from the least residual errors

● Probability Simulators (R) Developed multiple simulators to find the expectation, variance and conditional probability of a discrete distribution model that predicted the probability of a sum m or greater being cast in n rolls

● Babble Translator (PROLOG) Designed a translator that would output several complete sentence translations for over 1000 ambiguous words or partial sentences that an infant might speak

● Buffer Overflow (Python) Used gdb to inspect the stack of a program to overflow the memory address space into the rip register which distributed a shell payload

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