Lilit Yolyan, Developer in Yerevan, Armenia
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Lilit Yolyan

Verified Expert  in Engineering

Bio

Lilit is an applied scientist with more than six years of experience. She's enthusiastic about solving real-life, everyday problems with computer vision, digital signal and image processing, and neural network development. She works with an end-to-end AI pipeline, from problem definition, data cleaning, and preparation to modeling, testing, and preparing the model for further deployment.

Portfolio

Harman
Signal Processing, Computer Vision, Machine Learning, Image Processing...
Yerevan State University
Computer Vision, Deep Learning, Artificial Neural Networks (ANN)...
BRAND BOUTIQUE LAWYERS PTY LTD Trading as Inkse
Google Cloud, Google Cloud Platform (GCP), Image Generation, Image Manipulation...

Experience

  • Image Segmentation - 4 years
  • PyTorch - 4 years
  • OpenCV - 4 years
  • Deep Learning - 4 years
  • Python - 4 years
  • Machine Learning - 4 years
  • Computer Vision - 4 years
  • Object Detection - 4 years

Availability

Part-time

Preferred Environment

PyCharm, Slack, GitHub, GitLab, Teams, Visual Studio

The most amazing...

...thing I've developed is an algorithm for remote heart rate detection, designed for drivers, which was integrated into the systems of major car manufacturers.

Work Experience

Senior Machine Learning Engineer

2022 - PRESENT
Harman
  • Developed a rPPG algorithm capable of real-time heart rate detection, specifically tailored for driver health monitoring. This solution enhances vehicle safety by continuously tracking the driver's physiological signals without physical contact.
  • Worked on the development of a real-time photoplethysmography (PPG) algorithm utilizing data from wearable devices. This algorithm is designed for integration into earphones, enabling continuous stress monitoring.
  • Developed a comprehensive pipeline for cleaning and preprocessing raw data from multiple sources, ensuring data quality and consistency for downstream analysis and model training.
Technologies: Signal Processing, Computer Vision, Machine Learning, Image Processing, Neural Networks, Deep Learning, Data Analysis, Data Visualization, Natural Language Processing (NLP), Python 3, PyTorch, Slurm Workload Manager, Docker, GitHub, Large Language Models (LLMs)

Lecturer

2019 - PRESENT
Yerevan State University
  • Created a syllabus for two different classes, Deep Learning and Large Scale Analytics.
  • Managed a group of teacher assistants to work with me on courses.
  • Held lectures and practical classes for 15–25 students.
Technologies: Computer Vision, Deep Learning, Artificial Neural Networks (ANN), Convolutional Neural Networks (CNNs), 2D, Data Science

Back-end Developer with Image Manipulation | Online Startup

2022 - 2023
BRAND BOUTIQUE LAWYERS PTY LTD Trading as Inkse
  • Created two PoCs to generate prints for clothing.
  • Documented the process and technology of the two PoCs fully.
  • Prepared reports and presentations for weekly meetings.
Technologies: Google Cloud, Google Cloud Platform (GCP), Image Generation, Image Manipulation, Generative Adversarial Networks (GANs), Artificial Intelligence (AI)

AI Developer

2022 - 2022
Mohammed Ehsan Ur Rahman
  • Fixed bugs and errors in GAN regarding training loops, data loaders, and network architecture.
  • Experimented with different network architectures to get the best results on the given dataset.
  • Optimized the code for faster performance and adhere to PEP8 standards.
Technologies: Computer Vision, Python 3, Generative Adversarial Networks (GANs), TensorFlow, Deep Learning, PyTorch

Machine Learning Scientist

2020 - 2022
SmartClick
  • Developed a product roadmap, established a hypothesis, and identified experiments to run.
  • Researched models, methods, and technologies that can solve real-life problems, including object detection, image segmentation, few-shot learning, image processing, etc. Implemented research methods and evaluated the results.
  • Improved the existing technologies by optimizing inference time and speed on real-life applications.
  • Worked with the team, brainstormed and discussed possible solutions, and helped team members overcome blocking issues and achieve end goals.
Technologies: Artificial Intelligence (AI), Computer Vision, Computer Vision Algorithms, Deep Learning, Deep Neural Networks (DNNs), GitHub, GitLab, Image Classification, Image Processing, Image Segmentation, Machine Learning, Machine Vision, MongoDB, Neural Networks, Object Detection, OpenCV, NoSQL, Python, PyCharm, PyTorch, Self-supervised Learning, SQL, Object Tracking, Team Leadership, TensorFlow, Slack, Cloud, Kubernetes, Artificial Neural Networks (ANN), Generative Adversarial Networks (GANs), Convolutional Neural Networks (CNNs), 3D Image Processing, 2D, Data Science, Optical Character Recognition (OCR), Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP)

Machine Learning Scientist

2020 - 2021
SmartClick
  • Worked on end-to-end processes, including data collection and preparation, cleaning, modeling, testing, and error analysis.
  • Implemented computer vision techniques such as classification, object detection, segmentation, and metric learning for solutions in various domains. Modified and adapted models for specific solutions.
  • Collaborated with the engineering team for model deployment.
Technologies: Image Classification, Object Detection, Image Segmentation, Computer Vision, Deep Learning, Machine Learning, Python, PyTorch, OpenCV, Object Tracking, Computer Vision Algorithms, Artificial Neural Networks (ANN), Convolutional Neural Networks (CNNs), 2D, Data Science

Data Scientist

2018 - 2020
Menu Group
  • Developed machine learning models for customer behavior prediction.
  • Automated reporting processes for sales and management teams.
  • Created end-to-end machine learning pipelines for different products.
Technologies: Python, Machine Learning, Convolutional Neural Networks (CNNs), 2D, Data Science, Marketing, Enterprise Resource Planning (ERP)

Experience

CutPaste Model Implementation

https://github.com/LilitYolyan/CutPaste
CutPaste is a self-supervised learning algorithm created by Google. I implemented the code from scratch on GitHub by writing the model, training, and data loading codes. I also reproduced the results of the paper.

Development of Few-shot Learning Technology

I've developed an end-to-end few-shot learning technology that works with images of money, stamps, and other flat objects. The purpose of the model is to detect an object in the given images, compare it with the database, and output the most similar image. I trained the model and developed the database structure and API code to bring it together.

3D Deep Learning with Python

I am the co-author of the book "3D Deep Learning with Python," which will be released soon. It includes a theoretical and practical description of various applications of 3D computer vision using Python.

Education

2017 - 2019

Master's Degree in Data Science

Yerevan State University - Yerevan, Armenia

Certifications

FEBRUARY 2022 - PRESENT

Nvidia Deep Learning Institute Certification

Nvidia Deep Learning Institute

Skills

Libraries/APIs

PyTorch, OpenCV, TensorFlow

Tools

PyCharm, Slack, GitHub, GitLab, Visual Studio

Languages

Python, SQL, Python 3

Storage

MongoDB, NoSQL, Google Cloud

Industry Expertise

Marketing

Platforms

Kubernetes, Google Cloud Platform (GCP), Docker

Other

Deep Learning, Image Classification, Object Detection, Image Segmentation, Artificial Intelligence (AI), Image Processing, Machine Vision, Neural Networks, Deep Neural Networks (DNNs), Computer Vision Algorithms, Artificial Neural Networks (ANN), Convolutional Neural Networks (CNNs), 2D, Data Science, Machine Learning, Computer Vision, Team Leadership, Self-supervised Learning, Cloud, Object Tracking, Point Clouds, Generative Adversarial Networks (GANs), 3D Image Processing, Optical Character Recognition (OCR), Natural Language Processing (NLP), Enterprise Resource Planning (ERP), Generative Pre-trained Transformers (GPT), Large Language Models (LLMs), Few-shot Learning, Voice Cloning, Text to Speech (TTS), Image Generation, Image Manipulation, Stable Diffusion, DALL-E, Teams, Signal Processing, Data Analysis, Data Visualization, Slurm Workload Manager

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