Abay Bektursun, Artificial Intelligence Engineer and Developer in Austin, United States
Abay Bektursun

Artificial Intelligence Engineer and Developer in Austin, United States

Member since July 27, 2022
Abay is an engineer with over five years of experience building and shipping machine learning products. Specializing in AI and computational neuroscience research, he relies on first principles thinking and understands low- and high-level execution. Abay contributed to projects in different sectors and built the most extensive deep learning community in Texas.
Abay is now available for hire

Portfolio

  • Eagle Eye Networks
    C, Machine Learning, Deep Learning, Computer Vision, Linux, Python 3...
  • Apple
    TensorFlow, Deep Learning, Computer Vision, System Design, Python 3...
  • Hewlett Packard Enterprise
    Hadoop, Python 3, Machine Learning, Data Science, Data Visualization, Tableau...

Experience

Location

Austin, United States

Availability

Full-time

Preferred Environment

Linux, MacOS, vim, Visual Studio Code, Deep Learning, Artificial Intelligence (AI)

The most amazing...

...thing I've built is a computer vision system for physical Apple stores.

Employment

  • Computer Vision Engineer

    2020 - 2022
    Eagle Eye Networks
    • Developed embedded vision features deployed to tens of thousands of cameras worldwide.
    • Prototyped state-of-the-art deep learning methods for surveillance computer vision by harnessing large amounts of surveillance video.
    • Created prototypes with various edge accelerators for computer vision.
    Technologies: C, Machine Learning, Deep Learning, Computer Vision, Linux, Python 3, TensorFlow, C++, Leadership, Project Leadership, Team Leadership, Python, NumPy, JSON, CSV, Artificial Intelligence (AI), Machine Learning Operations (MLOps), Image Processing, Neural Networks, Cloud, Machine Vision, Data Engineering, Data Reporting, Data Analytics, Artificial Neural Networks (ANN), Scripting, Deep Neural Networks, PyTorch, Software Engineering, Cloud Services, DevOps, Pandas, SQL, Linear Regression, Clustering, Visualization Tools, Docker, Google Cloud Platform (GCP), Modeling, Data Mining, Back-end, Distributed Systems, GitHub, Back-end Development, Facial Recognition, Google Cloud, REST APIs, Scikit-learn, Keras, LLM, Generative Research, AI Design, Internet of Things (IoT), Analytics, Computer Vision Algorithms, OpenCV, Data Analysis, Jupyter, Git
  • Computer Vision Engineer

    2019 - 2020
    Apple
    • Developed the vision system that detects people's presence in Apple stores.
    • Led the team that developed a computer vision system for Apple store analytics.
    • Applied ideas from an academic research paper to a real-world product.
    Technologies: TensorFlow, Deep Learning, Computer Vision, System Design, Python 3, Object Detection, Object Tracking, Machine Learning, Leadership, Project Leadership, Team Leadership, Python, NumPy, JSON, CSV, Artificial Intelligence (AI), Data Modeling, Machine Learning Operations (MLOps), Image Processing, Neural Networks, Cloud, Machine Vision, Data Engineering, Data Reporting, Data Analytics, Artificial Neural Networks (ANN), Scripting, Deep Neural Networks, PyTorch, Software Engineering, Cloud Services, DevOps, Generative Adversarial Networks (GANs), Pandas, SQL, Pytest, Linear Regression, Clustering, Visualization Tools, Docker, Modeling, Data Mining, Back-end, Distributed Systems, GitHub, Java, Back-end Development, Facial Recognition, Data Pipelines, TypeScript, Google Cloud, REST APIs, Scikit-learn, Keras, Generative Research, AI Design, Analytics, eCommerce, Signal Processing, Computer Vision Algorithms, OpenCV, Data Analysis, Jupyter, Git
  • Machine Learning Developer

    2016 - 2019
    Hewlett Packard Enterprise
    • Joined the company as an intern and was recognized as one of the top three interns.
    • Led a development team for an entirely automated financial department. Reported to the CEO and saved the company $3 million.
    • Took leadership roles outside everyday work. Led employee volunteering programs, organized hackathons, and taught technical classes on Linux and machine learning.
    • Participated in NLP projects, summarizing and classifying company reviews to improve branding and analyzing employee survey text to improve the company culture.
    Technologies: Hadoop, Python 3, Machine Learning, Data Science, Data Visualization, Tableau, TensorFlow, Deep Learning, C++, Leadership, Project Leadership, Team Leadership, Python, NumPy, JSON, CSV, Word2Vec, Artificial Intelligence (AI), Data Modeling, Machine Learning Operations (MLOps), Robot Operating System (ROS), Image Processing, Forecasting, Neural Networks, Cloud, Machine Vision, Data Engineering, Data Reporting, Data Analytics, Artificial Neural Networks (ANN), Scripting, Automation, Automated Data Flows, Deep Neural Networks, PyTorch, Software Engineering, Cloud Services, DevOps, Text Mining, Pandas, SQL, ETL, Linear Regression, Clustering, Visualization Tools, Amazon Web Services (AWS), Docker, Google Cloud Platform (GCP), Modeling, Predictive Modeling, Predictive Analytics, Data Mining, Back-end, Distributed Systems, GitHub, Java, Back-end Development, Facial Recognition, Web Scraping, Data Pipelines, Google Cloud, REST APIs, Big Data, Scikit-learn, Keras, AI Design, Internet of Things (IoT), Analytics, Computer Vision Algorithms, OpenCV, Amazon S3 (AWS S3), Data Analysis, Jupyter, Git, Reinforcement Learning
  • Software Engineer Intern

    2015 - 2016
    Centene
    • Developed and maintained a documentation website, both its front-end and back-end work. Wrote scripts to process and parse EDI files.
    • Ran routine jobs and processed health insurance claims. Automated manually run jobs and reports.
    • Produced ad-hoc and scheduled reports for different departments. Helped vendors resolve issues and support third-party software.
    Technologies: Python 3, Oracle, Databases, MongoDB, EDI, Neural Networks, Cloud, Machine Vision, Data Engineering, Data Reporting, Data Analytics, Artificial Neural Networks (ANN), Scripting, Automation, Automated Data Flows, Deep Neural Networks, PyTorch, Software Engineering, Cloud Services, DevOps, Django, Pandas, SQL, ETL, Linear Regression, Clustering, Visualization Tools, Modeling, Predictive Modeling, Predictive Analytics, Data Mining, Back-end, GitHub, Back-end Development, Web Scraping, REST APIs, Scikit-learn, Keras, Internet of Things (IoT), Analytics, OpenCV, Data Analysis, Jupyter, Git

Experience

  • Why Does Batch Normalization Work?
    https://abay.tech/blog/2018/07/01/why-does-batch-normalization-work/

    A theoretical and experimental exposition on Batch normalization that explains the real reason why it works so well. The ML community believes Batch Norm improves optimization by reducing internal covariate shift (ICS). As I show, ICS has little to no effect on optimization.

  • Built a Community of Three Thousand People
    https://www.meetup.com/Austin-Deep-Learning/

    Austin Deep Learning is the largest deep learning community in Texas. We invite talks from machine learners and data scientists applying deep learning to solve problems, with tutorials and lessons learned. Talks are open to all deep learning frameworks, such as TensorFlow, Keras, PyTorch, and others.

  • Robotic Surgery

    I built my surgery robot to insert electrodes into insects to record the spiking activation of neurons. I built decoding modeling using the spike data. For example, I used a cricket as a proximity sensor by reading its mind.

  • Personal NLP Projects

    Built my own language models, both with RNNs and transformers. I used large language models for multimodal architectures and have presented many popular NLP papers in the Deep Learning community I lead in Austin.

Skills

  • Languages

    Python 3, Python, SQL, JavaScript, Java, TypeScript, C, C++, Rust, Embedded C
  • Libraries/APIs

    NumPy, PyTorch, REST APIs, Keras, OpenCV, TensorFlow, Pandas, Scikit-learn, Node.js
  • Tools

    GitHub, Jupyter, Git, Tableau, Scikit-image, Pytest
  • Paradigms

    Data Science, Automation, ETL, Parallel Programming, DevOps
  • Platforms

    Visual Studio Code, Linux, Docker, Google Cloud Platform (GCP), MacOS, Oracle, Amazon Web Services (AWS), Arduino
  • Storage

    JSON, Google Cloud, Data Pipelines, Databases, MongoDB, Amazon S3 (AWS S3)
  • Other

    Machine Learning, Deep Learning, Computer Vision, Computer Vision Algorithms, CSV, Word2Vec, Artificial Intelligence (AI), Data Modeling, Machine Learning Operations (MLOps), Image Processing, Neural Networks, Cloud, Machine Vision, Data Reporting, Data Analytics, Artificial Neural Networks (ANN), Scripting, Deep Neural Networks, Software Engineering, Linear Regression, Clustering, Modeling, Data Mining, Back-end, Back-end Development, AI Design, Analytics, Data Analysis, Data Visualization, vim, Natural Language Processing (NLP), Statistics, Probability Theory, Numerical Optimization, Optimization, Leadership, Project Leadership, Team Leadership, Fairseq, Transformers, Forecasting, Data Engineering, Automated Data Flows, Cloud Services, Generative Adversarial Networks (GANs), Text Mining, Visualization Tools, Predictive Modeling, Predictive Analytics, Facial Recognition, Big Data, LLM, Signal Processing, System Design, Object Detection, Object Tracking, Science, Calculus, Programming, Computational Neuroscience, Mathematical Analysis, kears, Robot Operating System (ROS), Microcontrollers, EDI, Distributed Systems, Web Scraping, Generative Research, Internet of Things (IoT), eCommerce, Language Models, RNNs, AWS, Amazon Machine Learning, Reinforcement Learning, Embedded Systems
  • Frameworks

    Hadoop, Django

Education

  • Bachelor's Degree in Computer Science
    2014 - 2017
    University of Central Arkansas - Conway, AR, USA

Certifications

  • Inferential Statistical Analysis
    SEPTEMBER 2022 - PRESENT
    University of Michigan, via Coursera
  • AWS Machine Learning
    SEPTEMBER 2022 - PRESENT
    AWS, via Coursera
  • Deep Learning Specialization
    MAY 2018 - PRESENT
    DeepLearning.AI, via Coursera
  • Machine Learning Specialization
    NOVEMBER 2017 - PRESENT
    Stanford University, via Coursera
  • The Arduino Platform and C Programming
    NOVEMBER 2016 - PRESENT
    Coursera

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