Abay Bektursun
Verified Expert in Engineering
Artificial Intelligence Engineer and Developer
Austin, TX, United States
Toptal member since July 27, 2022
Abay is an AI engineer and tech leader specializing in computer vision and scalable AI systems. At Apple, he led the development of a global, multi-million-dollar computer vision product. He drove the technical vision as CTO and co-founder of Gridlines (raised $1 million). At Docme.ai, he created models measuring vital signs via an iPhone camera. At Copycopter.ai, he developed scalable AI for video and image generation. Abay leads a community of over 3,000 AI enthusiasts.
Portfolio
Experience
- Python 3 - 8 years
- Deep Learning - 7 years
- Machine Learning - 7 years
- Computer Vision - 5 years
- TensorFlow - 4 years
- C++ - 3 years
- PyTorch - 3 years
- Computational Neuroscience - 1 year
Work Experience
Autonomous AI Expert
AbstractAI
- Played a key role in establishing a finance AI startup, which successfully raised over $1 million in capital: https://gridlinesapp.com/.
- Helped a startup build computer vision capabilities that they were able to sell to the Japanese government: https://www.cropwatch.io/.
- Built a SOTA model for measuring health signals via iPhone camera: https://www.docme.ai/. Managed a team of four.
- Built an end-to-end vision system for a fashion startup.
- Built a scalable video and image generation system for https://copycopter.ai/.
Computer Vision Engineer
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.
Computer Vision Engineer
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.
Machine Learning Developer
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.
Software Engineer Intern
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.
Project History
AI for Wealth Management
Why Does Batch Normalization Work?
Built a Community of Three Thousand People
https://www.meetup.com/Austin-Deep-Learning/Large Language Models | Alignment Experiment
https://www.linkedin.com/feed/update/urn:li:activity:7072309610354728960/The participants were invited to design three tasks with varying difficulty levels – elementary, intermediate, and advanced – tailored explicitly for LLMs. The models used for this experiment included Vicuna-13B, Vicuna-13B Uncensored, and Vicuna-7B, which served as a baseline for comparison. The participants assessed and rated the performance of each model based on their respective tasks.
The central focus was to examine the impact of intense alignment bias on the overall efficacy of LLMs. The findings of this study provided substantial evidence to support the hypothesis. The Vicuna-13B Uncensored model, trained on an augmented dataset with fewer moral constraints, achieved an average score of 5.75 out of 10, whereas the censored model secured an average of 3.95. This observation could be attributed to the tendency for stronger alignment to encourage deeper mode-seeking within the model distribution.
Raw CUDA Implementation of Gaussian Splatting
https://github.com/abaybektursun/gauss_splatsProject Overview: Brook-ankle-f27.notion.site/Gaussian-Splats-in-CUDA 16ceb624d4e980c78338dd24954d0c44
Source Code: Github.com/abaybektursun/gauss_splats
Feel free to check them out!
Education
Bachelor's Degree in Computer Science
University of Central Arkansas - Conway, AR, USA
Certifications
Inferential Statistical Analysis
University of Michigan, via Coursera
AWS Machine Learning
AWS, via Coursera
Deep Learning Specialization
DeepLearning.AI, via Coursera
Machine Learning Specialization
Stanford University, via Coursera
The Arduino Platform and C Programming
Coursera
Skills
Libraries/APIs
NumPy, PyTorch, REST APIs, Keras, OpenCV, LSTM, OpenAI API, Hugging Face Transformers, TensorFlow, Pandas, Scikit-learn, PyTorch Lightning, Node.js
Tools
GitHub, Jupyter, Git, NVIDIA Jetson, NVIDIA Nsight Systems, Tableau, Vendor Independent Messaging (VIM), Scikit-image, Pytest, ChatGPT, Google AI Platform
Languages
Python 3, Python, SQL, CSS, HTML, Falcon, JavaScript, Java, TypeScript, C, C++, Rust, Embedded C
Paradigms
Automation, ETL, Parallel Programming, DevOps, Web App Design, Distributed Computing
Platforms
Visual Studio Code (VS Code), Linux, Amazon Web Services (AWS), Docker, Google Cloud Platform (GCP), AWS Lambda, MacOS, Oracle, Arduino, AWS IoT, NVIDIA CUDA
Storage
JSON, Google Cloud, Data Pipelines, Databases, MongoDB, Amazon S3 (AWS S3)
Frameworks
Hadoop, Django, Flask, Next.js
Other
Machine Learning, Data Science, Deep Learning, Computer Vision, System Design, Natural Language Processing (NLP), 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 (DNNs), Software Engineering, Linear Regression, Clustering, Modeling, Data Mining, Back-end, Back-end Development, Large Language Models (LLMs), AI Design, Analytics, Language Models, Data Analysis, CCTV, Architecture, Hugging Face, Fine-tuning, OpenAI GPT-4 API, Workshop Facilitation, Data Scraping, Statistical Methods, Statistical Data Analysis, Statistical Analysis, OpenAI, Llama 2, PEFT, BERT, Software Architecture, Chatbots, Dashboards, Speech-to-Text (STT), Google Speech-to-Text, Retrieval-augmented Generation (RAG), Serverless, Model Tuning, ChatGPT Prompts, ChatGPT API, Prompt Engineering, Open-source LLMs, Image Recognition, Convolutional Neural Networks (CNNs), Object Recognition, Meta Llama, Gemini, Gemini API, Edge AI, NVIDIA TensorRT, Quantization, model quantization, NVIDIA Jetson Nano, Text-to-Speech (TTS), Pattern Recognition, Data Visualization, 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, Signal Processing, Reinforcement Learning, Real-time Data, Hardware, Generative Artificial Intelligence (GenAI), Generative Pre-trained Transformers (GPT), Generative Pre-trained Transformer 3 (GPT-3), LoRa, OpenAI GPT-3 API, Financial Modeling, CTO, Object Detection, Object Tracking, Science, Calculus, Programming, Computational Neuroscience, Mathematical Analysis, Robot Operating System (ROS), Microcontrollers, Electronic Data Interchange (EDI), Distributed Systems, Web Scraping, Generative Research, Internet of Things (IoT), eCommerce, Recurrent Neural Networks (RNNs), Amazon Machine Learning, Embedded Systems, DALL-E, Stable Diffusion, Models, Startups, LangChain, CUDA Kernel, 3D Graphics
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