Hi There! I'm Joel Simonoff a problem solver a team player a go-getter


About Me

About Me

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I'm an electrical engineering and computer science (EECS) student at UC Berkeley class of 2020.

I have a serious passion for building disruptive technology. This passion was born in high school while working on a rehab exoskeleton for kids with Cerebral Palsy at Not Impossible Labs. That same fire has stuck with me throughout college and my work on Predictim where we used AI to improve parents’ ability to find safe childcare. I'm looking for roles at innovative and disruptive companies where I can thrive.

I'm currently seeking summer 2019 internships in technical program and product management, embedded systems, robotics, artificial intelligence, and space technologies. I have 3+ years of professional experience in software engineering and embedded systems, and 2 years of technical program and product management experience.

Here are some fun facts about me:

  • I'm an expert snowboarder and motorcycle enthusiast!
  • I spent Christmas 2017 in an electrical engineering lab working on my electric snowboard!
  • I won the flow-rider surfing competition on the Royal Carribean ship Freedom of The Seas!
  • I once had over 12 cups of coffee in 1 day at work ☕

  • Name: Joel Simonoff
  • Age: 21
  • Seeking: Summer 2019 Internship
  • GPA: 3.9/4.0
  • Phone: 310-729-0944
  • Address: Berkeley, california
  • Email: joelsimonoff@berkeley.edu
  • Studying: UC Berkeley: Electrical Engineering and Computer Science
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Technical Co-Founder & CTO - Predictim
May 2018 - January 2019

The first AI-powered platform that can assess an individual’s trust and safety using Natural Language Processing and Computer Vision, Predictim's mission is to improve trust and reliability in the sharing economy, starting with childcare.

  • Took off Summer 2018 and Fall 2018 to work full time on Predictim at UC Berkeley SkyDeck Accelerator.
  • Raised initial angel funding of $100k.
  • Led the technology team while acting as the liaison between business and engineering departments. I also interfaced with several labs on campus to learn about how their research could improve our product.
  • Ran the engineering team using the extreme programming methodology and daily sprints in order to meet our development milestones within the incredibly short time frame given by our investors.
  • Signed our first B2B client, Sittercity.com, and acted as the sales engineer for that contract.
  • Used convolutional neural nets (CNNs) for text classification.
  • Worked hands on with SpaCy, and Prodigy to build main classification and entity recognition tools.
  • Used TensorFlow and SciKit Learn for auxiliary AI models.
  • Wrote backend server code in Golang.
  • Wrote MongoDB database queries using the Golang MGO bindings library.
  • Constructed MongoDB aggregation queries in JavaScript directly in the Mongo shell.
  • Assisted with frontend development during rapid development. I worked with HTML (using Bootstrap and GOHTML templating), CSS (LESS), and JavaScript.
Technical Co-Founder & CTO - Social Filter
February 2016 - May 2017

An AI tool that helps you present your best self online by identifying and helping you remove social media posts that are potentially harmful to your reputation.

  • Scanned over 20 million social media posts and contributed to the business strategy that brought us to small scale profitability.
  • Used agile development methodology and pair programming to build the product.
  • Helped the business with marketing and sales and brought the business to profitability at small scale.
  • Went through the full dev cycle multiple times.
  • Got accepted to Haas School of Business Launch Startup Accelerator program and successfully completed the program.
  • Acted as technical manager and liason for our B2B partnership with Synapse Media Group.
  • Used a combination of bag of words and Glove Embedding based SVM and random forest classifiers.
  • Built a proprietary pattern matching algorithm and scripting language.
  • Wrote backend server code in Golang and interfaced with MongoDB via the MGO bindings library.
  • Wrote MongoDB aggregation scripts for our business intelligence folks.
Embedded Systems/Software Engineering Intern - Not Impossible Labs
June 2014 - January 2016

Not Impossible aims to re-engineer high-cost medical devices so they can be built and deployed in less developed countries. At Not Impossible I worked on a rehab exoskeleton and device that allows deaf people to experience sound.

  • Learned agile development methodology and project management tools such as Trello, Slack, code reviews and GitHub.
  • Flew to England to work directly with Jaguar Land Rover engineers on the exoskeleton project, gaining exposure to Jaguar’s internal project management and document versioning tools.
  • Gained hands on experience with PID loops, motor control circuitry, Bluetooth Low Energy, and iOS development.
  • While at Jaguar Land Rover, I gained exposure to use of CAN bus and UDP on human rated systems.
  • Worked extensively with C for embedded systems and robotics. I learned many embedded system tricks, tips, and hacks from senior engineers.
BS Electrical Engineering and Computer Science - UC Berkeley
2017 - 2020

GPA: 3.925

Program In Entreprenuership - UC Berkeley SkyDeck Startup Accelerator
June 2018 - Jan 2019

I worked full time on Predictim at SkyDeck in lieu of engineering coursework for the Fall 2018 semester.

Program In Entreprenuership - UC Berkeley Haas School of Business
Jan 2018 - May 2018

I went through the Launch startup accelerator which is 20 hours a week of business work done concurrently with my engineering coursework during the Spring 2018 semester.

Lower Division Engineering Coursework - Los Angeles Pierce College
August 2015 - June 2017

GPA: 4.0

Golang, C/C++, Python, Jupyter Notebook

Java, x86 and Risc-V Assembly, Pandas, NumPy

Mongo Query Language and Aggregation

SQL, HTML, CSS, JavaScript, Swift, Objective C

SpaCy, NLTK, SciKit-Learn, Matlab


Arduino Ecosystem, Function Generators, DVOMs, Power Supplies, Variacs, TI Launchpad

Raspberry Pi, Oscilliscopes, ATTiny Chipsets

Hayes AT Commands, Nordic nRF BLE boards


Bluetooth Low Energy

HAM Radio Operation (KK6KED)


Years Experience


Done Projects


Happy employers

my portfolio

my portfolio


get in touch

get in touch

Berkeley, California
2908 Channing Way, Berkeley
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If you have any suggestion, project or even you want to say Hello.. please fill out the form below and I will reply you shortly.



  • Date : May 2018 - Jan 2019
  • AI Technologies : SpaCy, TensorFlow, Jupyter Notebook, and SciKit-Learn.
  • Full Stack : Golang, MongoDB, HTML, CSS (LESS), JavaScript, Digital Ocean, AWS, Python, Flask, Gunicorn, and NGINX.
  • Funding : $100k
  • Roles : Co-Founder and CTO

The first AI-powered platform that can assess an individual’s trustworthiness using Natural Language Processing and Computer Vision. Predictim's mission is to improve the ability of community members to feel trust and reliance in the sharing economy, starting with childcare.

Each Predictim Report assesses an individual using four different personality features based on their web presence: propensity towards Bullying / Harrassment, Disrespectfulness / Bad Attitude, Explicit Content, and Drug Abuse.

We've been featured in major national and international news media both TV and written. We were on the front page of the printed Washington Post and we were trending on Apple News twice.

Visit Our Site

Social Filter

  • Date : Feb 2016 - April 2018
  • AI Technologies : NLTK, SciKit-Learn, and proprietary pattern matching.
  • Full Stack : Golang, MongoDB, HTML, CSS (LESS), JavaScript, Digital Ocean, AWS, Python, Flask, Gunicorn, and NGINX.
  • APIS : Facebook Graph API, Google Cloud Vision, Twitter REST API, Instagram REST API
  • Roles : Co-Founder and CTO

Social Filter is a tool that helps improve your online personal brand by identifying innapropriate and unprofessional social media posts that can harm your reputation. Social Filter does this using natural language processing and computer vision.

We advertised through word of mouth and Facebook ads. In totality, we scanned over 20 million social media posts, and helped numerous people erase thoughtless posts from their social media record. Additionally, we did bring the business to profitability in the small scale.

It took us about 8 months from idea to beta testing, and we rebuilt the entire codebase multiple times over the course of the project.

Check Us Out