Scroll To View More
Eric Freiling, Python Developer in San Diego, CA, United States
Eric Freiling

Python Developer in San Diego, CA, United States

Member since August 4, 2018
Eric is a senior data scientist based in San Diego, and prior to his current career, spent six years in the defense industry. He has a strong academic background culminating in a master's degree in mathematics and a PhD in electrical engineering. Some of the areas that he's worked in are algorithm development, signal/image processing, and machine learning.
Eric is now available for hire

Portfolio

Experience

  • Algorithms, 8 years
  • Clustering, 6 years
  • Digital Signal Processing, 6 years
  • Data Science, 3 years
  • Machine Learning, 3 years
  • Image Processing, 3 years
  • Python, 3 years
  • Keras, 1 year
San Diego, CA, United States

Availability

Part-time

Preferred Environment

PyCharm, MATLAB

The most amazing...

...project I've worked on was fingerprinting radios.

Employment

  • Senior Data Scientist

    2018 - PRESENT
    Sotera Wireless
    • Created new SpO2 calibration techniques, SpO2 feature calculations, and a PPG beat classification for signal quality metrics.
    • Developed unsupervised learning and clustering techniques in Python.
    Technologies: Python, Jupyter, PyCharm
  • Data Scientist

    2017 - 2018
    Teradata
    • Created event detection algorithms for several business use cases on signals regarding database health; developed those algorithms in Python and SQL.
    • Explored root cause data. Given a scenario of poor database performance or unusual behavior, explored massive data sets to find root cause with an accompanying explanation for customers (Python, SQL, and Tableau).
    Technologies: Teradata, SQL, Python, PyCharm, Tableau
  • Software Engineer - Scientist III

    2011 - 2017
    KAB Laboratories
    • Worked with a team of software engineers and algorithm developers to create handheld push-to-talk radio fingerprinting algorithms.
    • Worked on feature extraction and pattern detection on radio signals to uniquely identify radio devices, make, and model independent of the speaker.
    • Developed algorithms in MATLAB and collaborated with engineers to convert the code to C for production and helped deploy the product.
    • Created unique digital signal filtering techniques for radio fingerprinting. The project had been successful with moderate noise, but real-world applications had more noise than expected. These unique filtering techniques led to the success of the project in real-world noisy environments.
    • Developed an algorithm in MATLAB and converted it to C for production; the product was deployed and deemed successful.
    • Wrote signal modulation detection algorithms, pattern detection in the Fourier domain. Satellites can be saturated by unwanted signals. Detection of signal modulation and frequency was a way to classify wanted versus unwanted signals.
    • Developed algorithms in MATLAB and converted the code to C for production.
    • Designed and trained deep learning techniques and other machine learning algorithms to identify ship vessel type based on transit patterns; this project was short term.
    Technologies: MATLAB, C
  • Teaching Assistant

    2011 - 2014
    UCSD | University of California, San Diego
    • Assisted several professors in supplementing course material, hosting discussion sections, holding office hours, grading homework and exams for the following courses: Graduate Level Digital Image Processing, Graduate Level Random Processes, and Undergraduate Probability.
    • Received the "Best TA Award" in the Electrical Engineering department for a graduate class in digital image processing.
    Technologies: MATLAB
  • Teaching Assistant - Instructor

    2008 - 2010
    SDSU | San Diego State University
    • Acted as an instructor for two classes per semester: Statistics and Business Calculus.
    • Designed lesson plans, course material, and graded homework and exams.
    • Worked with the professors to assure that the lesson plans aligned with his teaching materials.
    Technologies: MATLAB

Experience

  • Transfer Learning on Small Datasets (Development)

    I compared the benefits of transfer learning on a small dataset to deep learning with data augmentation.

Skills

  • Other

    Algorithms, Principal Component Analysis (PCA), Clustering, Digital Signal Processing, Image Processing, Deep Learning
  • Languages

    Python, SQL, C
  • Frameworks

    Machine Learning
  • Libraries/APIs

    Keras, SciPy, NumPy
  • Tools

    PyCharm, MATLAB
  • Paradigms

    Data Science

Education

  • PhD degree in Electrical Engineering
    2010 - 2014
    University of California, San Diego - San Diego, CA, USA
  • Master's degree in Applied Mathematics
    2008 - 2010
    San Diego State University - San Diego, CA, USA
  • Bachelor's degree in Mathematics
    2006 - 2008
    University of California, San Diego - San Diego CA, USA
I really like this profile
Share it with others