• Hi!
    I'm Attiano

    I am working as a senior AI Research Engineer at Lockheed Martin's Advanced Technology Center

    Previously I worked at Robotire as a Computer Vision Engineer

    Also I worked at Raytheon as a Software Engineer

    To learn more about me, plese go visit my Linkedin

  • I have an M.S. in CS and a B.S. in EE from UCLA

    My primary research topics of interest lie in computer vision and optimization

    Please visit for further details my Linkedin

    View CV

About me

Who Am I?

Cogito ergo sum + Ubuntu - I think therefore I am, however I am because we are.

I am pedantic and semantic. I like homonyms, homophones, homographs, synecdoches, stenography, steganography (No I didn't hide any messages in the opaque Basquiats, trust me looking through the binary of those would be a waste of time, seriously), and other estoteric words.

I have an idiosyncratic philosophy that stems from a syncretic snythesis of eastern & western religions and science.

Like most engineers I am motivated by understanding things, however I understand life is about people, and I put them first. I evaluate things based on: 1. The People, 2. The Place, 3. The Thing.

Basically I am Attiano Purpura-Pontoniere.

I am currently employed as a senior AI research engineer at Lockheed Martin's Advanced Technology Center in Palo Alto.

My research interests lie primarily in computer vision and stochastic optimization, which I view machine learning as a subset of.

Ways to find me include:

Find me on Github. Most repositories are public.

Connect with me on Linkedin.

For detailed information on my past
simply visit my Linkedin!

My History
Technical Roles

My Papers

2021 at UCLA & Stanford

Machine Learning

  • Paper in semi-supervised learning submitted and rejected from CHIL 2022, ISBI 2022, MedNeurIPS 2022... will be published on ArXiv

2021 at Lockheed Martin

Machine Learning

  • Whitepaper in Advanced HTI processing submitted to NGA BAA, was not recommended for further development. E. Berkson, A. Purpura-Pontoniere

2020 at Robotire

Machine Learning

  • Robotire purchased IP for Lugnut Identification Using State of the Art Regional and Fully Convolutional Neural Networks, A. Purpura-Pontoniere, D. Terzopolous
My Projects

Most Recent Projects

UCLA Cardiovascular Data Science Lab
Current | Medical data analysis | 2

UCLA Cardiovascular Data Science Lab

Working with Dylan Steinecke to research and develop machine learning techniques for medical data analysis. We are currently investigating ML vs. deterministic algorithms for ECG compression for mobile health.

Current | Mentorship | 3

UCLA Eta Kappa Nu Alumni Mentorship Program

Mentor 3 students from UCLA HKN (electrical enginering honor society - implies consistent strong academic performance) 1-on-1 for 1 hour weekly, through the almuni mentorship program. Particpated in 2021, and 2022.

Stanford RSL
December 2021 | Computer Vision (segmentation, classification, denoising, etc) | 4

Stanford RSL - AI/ML Medical Image Analysis

Worked with Abdullah Imran when he was a post-doc at Stanford RSL to research and develop self-supervised and semi-supervised machine learning techniques for medical image analysis

December, 2020 | Object Detection | 2

Lug nut centriod identification

Worked with Robotire to provide a state of the art computer vision service that performs object detection of lug nuts in captured images through optical sensing

December, 2020 | NLP, NLG | 3

Rap Lyric Generator

Lead a team of M.S. students to create a rap lyric generator using SOTA NLP at the time. Now ChatGPT can probably do it better :/

June, 2020 | Quantum Computing | 3

Quantum Computer Evaluation

Lead a team of M.S. students and one PhD to evaluate IBM & Regetti quantum computers and simulators Pyquil and Qiskit implementations of standard QC algos

December, 2019 | Neuro signal processing | 1

EMG Signal Decomposition

Given real EMG data obtained from electrodes implanted in monkeys, used Matlab for signal decomposition to find 4 motor neurons. Used FFT to bandpass relevant frequencies, threshold spikes (action potentials) based on RMS power, and then use K-means on the top PCA eigenvalues of the filtered signal to cluster Motor Unit Action Potentials. Advised by Dr. Wentai Liu

March, 2019 | Computer Vision | 2

Handwritten Character Recognition

Used deep learning to perform optical character recognition on two datasets of increasing difficulty as the capstone project for my B.S. in EE at UCLA in a two person team with Brian Tehrani.

March, 2019 | Computer Vision | 2

UCLA Digital Signal Processing Lab

Utilized a DSP specific embedded system (TI's LCDK) to perform a series of digital signal processing tasks. Record and modulate speech, polygon recognition in images using the Hough Transform, and vowel recognition using deep learning and features extracted from the PSD of the input audio

June, 2018 | Robotics | 3

Autonomous Robocar

Contributed to an autonomous battery powered robot-car that avoids obstacles and finds the shortest path in a grid using Dijkstra's shortest path

June, 2017 | Software Engineering | 1

Battleship Videogame in C++

Used Object Oriented Programming in C++ to make a battleship game that output text to the command line as a GUI. Created three levels of intelligence for deterministic AI: easy player, mediocre player, and good player

June, 2016 | Software Engineering | 1

Coding For All

In high school I designed a two hour workshop to introduce young people with special needs to computer programming. Presented at the National Down Syndrome Congress Convention in Arizona, invited back the following year. Presented multiple times at the Silicon Valley Down Syndrome Network in Palo Alto.

Alma Mater


I received my M.S. in Computer Science, conferred December 2020 from University of California Los Angeles

  • Secondary Focus: QUANTUM COMPUTING

I received my B.S. degree from University of California Los Angeles Cum Laude, conferred March 2019. My undergraudate capstone culminated in OCR using RNNs and CNNs on a handwritten names dataset


Professional Experience


Senior AI Research Engineer April 2022 ~ present

AI Research Engineer April 2021 ~ April 2022

At Lockheed Martin, advised by Dr. Tarun Bhattacharya

  • Technical lead (key technical contributor + PM responsibilities) for a team developing a high priority cognitive application.


  • Awarded 2 publications
  • Delivered 9 talks on work & research - 2 external, 7 internal lightning talks
  • Submitted 3 invention disclosures
  • Proposed 3 IRADs
  • Nominated for Exceptional Engineering and Technology Award 2022
  • Winner of the Space Innovation Spotlight 2022
  • Nominated for Space Awards Night 2022
  • Featured on Space 2022 Greatest Hits
  • Winner of Data Science Sponsored Innovation 2021
  • Awarded NextGen Recognition from direct supervisors and senior engineers
  • Promoted in 1st year

Computer Vision Engineer July 2020 ~ December 2020

At Robotire, advised by Mr. Bradley Sliz

  • Specified, designed, and implemented custom object detection services from scratch. Integrated with industral articulated robots.
  • Created an LLC to manage contract and liability. (PurpleBridgeMakerTech LLC)

Software Engineer May 2019 ~ July 2020

At Raytheon Space and Airborne Systems, advised by Mr. Omar Channer

  • Injected random noise into SAR data→had a consensus of classifiers identify/correct mislabels resulting in >96% correction
  • Built a variable-size data augmenter w/ complex rotation, Rayleigh and Gaussian noise, improved classification by >14%
  • Developed a python script to automate the plotting of ROC curves given a classifier and a dataset using Tensorflow
  • Exstensive low-level (ELF object code) debugging of instrumentation/BDB maker for EO sensor servo codebase in SVN branch, pushed code that fixed Jenkins build

Lead Tutor August 2012 ~ June 2016

At Peralta Community Colleges, advised by Prof. Pinar Alscher and Prof. Jose Luis

  • Tutored students one-on-one or small groups in subjects such as Math, Chemistry, Physics and Computer Science. Hand-selected by Chair of Computer Science department at Laney College (Jose Luis Flores) to tutor student with autism, to positive feedback.