Edward is a Python back-end developer with profound knowledge of algorithms and data structures. With five years of industry experience, he has expertise in many back-end technologies, including Flask, Django, SQL, MongoDB, Redis, AWS, and CircleCI. He excels at identifying and fixing system bottlenecks. Edward has a strong passion for AI, space, and gene editing, a bachelor's degree in applied mathematics and computer science, and several prestigious technology awards.
Developed and maintained the app's back end that allowed users to search, track, and log hundreds of multiphase experiments with dynamically changing specifications.
Connected the app to Slack and Asana by using their APIs. Created bots to notify app users about their tasks and overall progress. Synchronized the data between the database, Slack, and Asana.
Developed the CI/CD that ran tests and database migrations and deployed the back end to AWS Lambda.
Optimized SQL queries containing dozens of joins. In some cases, query performance improved from one minute to one second.
Co-designed the SQL schemas and developed custom migrations, ensuring that database schemas met the project's demands.
Used the Google Sheets API to regularly ingest experiment templates from Google Sheets to the database using Amazon EventBridge.
Designed and developed the "dataset format for AI" and played a key role in getting the project from zero to 2,400 stars (Github.com/activeloopai/hub).
Co-developed the back end of the app that visualizes AI datasets and allows users to zoom in/out, batch, and more.
Developed a pipeline for ingesting datasets, training models, and running inference in a multimachine, parallelized environment using Kubernetes-like technology.
Developed a C++ back end, co-developed a Python back end, and took part in all stages of project development.
Designed and developed a custom, real-time database for aerial heatmaps with zoom-in-and-out support. The database and its Python back end allowed users to view 80 GB of data in real time despite strict I/O limitations.
Modified an open-source DSD project: created a cross-language interoperability layer between LabVIEW and C++, allowing LabVIEW developers to access the DSD functionality. The original project is available at Github.com/szechyjs/dsd.
Migrated a large portion of the project from Python 2 to Python 3.
Fixed unit and functional tests caused by Python 2 to Python 3 migration.
Handled most of the CI/CD (CircleCI) changes required when transitioning from Python 2 to Python 3. Made sure it worked well with the existing CI/CD systems.
A university project with the goal to parse photos of Sudoku into their digital form. I used OpenCV and open-source algorithms to crop the Sudoku grid from the background. Next, using breadth-first search (flood fill), I separated each digit from the grid into separate images. My optical character reader labeled each digit image. I used the handwritten MNIST dataset and a known convolution network to train the model to develop the OCR. After that, I fine-tuned it with programmatically generated (Pillow) printed digits with a dozen fonts. Resulting OCR had a 99% accuracy which translated into 90% accuracy for the entire Sudoku grid.
A research project to detect a drone or plane's location by tracking changes in surface images beneath the drone. This was a backup in case GPS navigation failed for any reason. Using linear algebra and OpenCV algorithms, my position detection algorithm got good results. While it could not detect the drone's precise position, it was enough to direct it to the desired place. The performance of the analysis was also acceptable enough to run on an onboard Raspberry Pi.
I started learning to program when I was 12. After rigorous and persistent training, I became exceptionally skilled at algorithms and data structures and won the silver medal at IOI 2014, Taiwan. From the IOI website:"The IOI is one of five international science olympiads. The primary goal of the IOI is to stimulate interest in informatics (computing science) and information technology. Another important goal is to bring together exceptionally talented pupils from various countries and to have them share scientific and cultural experiences."
The client, a signal processing company, needed a LabVIEW API allowing them to listen and transmit on a wide range of radio frequencies using HackRF devices. I developed a cross-language interoperability layer between LabVIEW and HackRF C++ drivers, allowing LabVIEW developers to build seamless and low-latency communication with HackRF devices.
Education
Bachelor's Degree in Applied Mathematics and Computer Science
