I'm a bioengineer turned data scientist with a curiosity for exploring and
working with new technologies in biotech, scientific computing, and music information.
Overall, I just love building things.
Current: Data Scientist @ commercetools GmbH, Berlin, DE
Education: B.Eng Biomolecular Engineering @ Santa Clara University, California
Aposynthese is a tool to give anyone perfect pitch. It converts mp3 files into piano visualizations, giving the user the ability to learn any song they like. It works by decomposing the song's underlying constituent frequencies with the Short Time Fourier Transform (STFT), and mapping dominant frequencies to real piano notes across time. The program also leverages some advanced Music Information Processing techniques, available through the librosa audio processing library. These include Harmonic-Percussive Source Separation (HPSS) to remove drum beats, and iterative cosine similarity to remove vocals. Additional custom signal processing cleans up the STFT spectrograms and allows smoother tonality mapping that mimics the human ear.
Insula is the first device to create music from multiple biofeedback sensors. It was built for my bachelor's thesis on a team with 3 other engineers.
Our system creates live audio output by processing biodata from EEG, EMG, ECG, and breath rate sensors.
Physiological inputs (heart beats, muscle contractions etc.) are mapped to musical outputs (drum beats, chords) for the purpose
of meditation, physiotherapy, and artistry. Insula paints a meaningful and holistic picture of bioinformation, enabling users to
control and direct their body's natural rhythms into acoustic art.
I extended the original project with a "V2", which includes a glove with IMU sensor which allows intentional control of the music.
Our tech-stack includes Arduino, C++, Python, Processing (Java), and OpenBCI.
I learned Machine Learning through textbooks, Andrej Karpathy's CS231n course, and Udacity courses. There are some of my bigger projects I worked on through my learnings and till now.
Developed a behavioral cloning algorithm to predict steering angle commands from dashcam images. Additionally, I tested the efficacy of using Singlar Value Decomposition as a preprocessing step for background removal of stationary objects in the frame (dashboard, reflections etc). Used MIT's Deep Tesla dataset.
Developed a U-Net for semantic segmentation of cars on the road from a dashcam image. Implemented the original architecture from the U-Net paper on arXiv. Trained several iterations on a GPU, including ones for gradient checks, a control baseline, and augmentation/regularization.
This was a contract job to build a computer vision pipeline for detecting defects in watch faces on an assembly line. It uses OpenCV's SIFT Detector, a custom statistcal model based on a Gaussian Kernel Density Estimation and Homography Transform for image alignment, and a simple comparison for errors.
For my work at as an autmation engineer intern at Amyris, a synthetic biology company, I improved the computer vision algorithms for a automated cell-colony-counter robot. The algorithm uses a recursive Hough Circles to detect well plates, and cells, plus basic image filtering and thresholding. It significantly improved both quality and speed of identifications.
This is a real-time computer vision application to measure heart-rate from changes in optical intensity via a webcam. It uses Indepedent Component Analysis (ICA) to tease out the frequency of the heart rate based on the changing redness of skin during a heart contraction. Implementation of MIT paper: “Non-contact, automated cardiac pulse measurements using video imaging and blind source separation. Optics Express 18 (2010)"
For my work as a data science educator at General Assembly, I wrote several tutorials for my students explaining arcane data science topics that were not discussed in class. I wrote additional tutorials on Cython, Deep Learning Best Practices, Python Tricks, Computer Vision, C++, and more.
I built a novel algorithm using adaptive Bollinger Bars (Z-Scores) to predict stock prices. Back tested across 900 tickers and 12+ years of stock data from Quandl. I also built an interactive visualization app in with Python's Dash library.
Insula is the first device to create music from multiple biofeedback sensors. Our system aggregates biodata from EEG, EMG, ECG, and breath rate technology into live audio output. Insula paints a meaningful and holistic picture of bioinformation, enabling users to control and direct their physiologies into art.
Investigating the effects of spaceflight on bone strength and dynamics. Our team implemented an integrated model to mimic mechanical strain of exercise via cyclical loading (CL) in mice treated with the BP Zoledronate (ZOL) combined with hindlimb unloading (HU).
I describe my experiences and perspectives gained from working with the non-profit, Engineers Without Borders.