Ruby on Rails Engineer
2021 - PRESENTSelf-employed- Developed, maintained, and updated Phytohub, a plant information related web application using Ruby on Rails.
- Developed back-end data pipelines that import plant-related datasets from online resources.
- Built front-end interface using JavaScript, CoffeeScript, and Slim.
- Worked with Redis, NGINX, Puma, Capistrano, JSON, RSpec, MySQL, Active Admin, and Digital Ocean.
- Deployed the Phytohub application on distributed servers that are being used by researchers at INRAE and other agriculture-based research institutions.
Technologies: Ruby on Rails (RoR), MySQL, Redis, NGINX, Capistrano, Puma, Administration, DigitalOcean, JavaScript, CoffeeScript, JSON API, Code Review, Ruby, HTML, Git, REST APIs, CSS, API Integration, Bootstrap, Full-stack, API Development, Back-end, Test-driven Development (TDD)Artificial Intelligence Engineer
2020 - 2022Huawei Technologies Co.- Researched and developed deep reinforcement learning technologies with MCTS, UCB, Bandits, DQN, AlphaZero, AlphaGo, and ResNets.
- Developed ML and RL end-to-end frameworks using Python, C++, TensorFlow, PyTorch, TVM, and Halide.
- Trained very large deep neural networks, including ResNets, using GPU parallelization.
- Deployed a deep RL-based product to GPU, CPU, and NPU servers being used in production.
- Published a paper in ICTAI improving the state-of-the-art results in tensor optimization (TVM) using a Bandit-based reinforcement learning algorithm.
- Published a heuristic search paper in SoCS based on memory-bounded best-first beam search for scheduling halide programs.
Technologies: Machine Learning, Deep Reinforcement Learning, Heuristics, PyTorch, TensorFlow, Monte Carlo Tree Search (MCTS), ResNet, Deep Neural Networks, Beam Search, Genetic Algorithms, Python 3, C++11, Source Code Review, Code Review, Python, Artificial Intelligence (AI), Deep Learning, Git, API Integration, CI/CD Pipelines, Back-end, Test-driven Development (TDD)Software Developer
2019 - 2020Drugbank- Developed, maintained, and updated a large-scale drug information SaaS Drugbank application with one million daily users using Ruby on Rails.
- Developed back-end data pipelines that import drug-related datasets from online resources.
- Built internal software libraries and RESTful APIs to facilitate biological data exchange using Her and Faraday libraries.
- Worked with Sidekiq, Redis, Elasticsearch, Puma, Unicorn, NGINX, Capistrano, Haml, JSON, RSpec, MySQL, Active Admin, AWS, Google Cloud Engine, New Relic, AppSignal.
- Developed front-end JavaScript and HTML using JQuery, Slim, ERB, and CoffeeScript.
- Implemented SVM, RNN, Transformer, skip-gram, and BOW models for a multi-classification task to predict the type of interactions between drugs and proteins from natural language.
- Implemented spaCy NER classification algorithm to predict different entities like drugs and proteins from the text. Implemented BERT from PyTorch-Transformers for this task.
Technologies: Ruby on Rails (RoR), Python 3, JSON REST APIs, Sidekiq, Redis, Elasticsearch, MySQL, Capistrano, Puma, jQuery, JavaScript, New Relic, Google Cloud Engine, Natural Language Processing (NLP), PyTorch, Transformers, BERT, SpaCy, RNN, Support Vector Machines (SVM), Source Code Review, Code Review, Python, Ruby, HTML, Artificial Intelligence (AI), Deep Learning, Git, REST APIs, CSS, API Integration, Google Cloud Platform (GCP), Bootstrap, Scrapy, Full-stack, API Development, Amazon Web Services (AWS), CI/CD Pipelines, Back-end, Test-driven Development (TDD)Artificial Intelligence and Robotics Developer
2018 - 2019A&K Robotics- Researched and developed AI software that predicts objects and their distance from the camera and other sensors like LIDAR and IR, implementing YOLO, R-CNN, and SSD.
- Worked with Python, C++, TensorFlow, PyTorch, Detectron, and Darknet.
- Implemented firmware applications with Arduino and Raspberry Pi and UNIX-based systems on ROS.
- Implemented best practices of Agile software design, Trello cards and epics, pull requests, and GitHub issues.
Technologies: Darknet, Detectron, TensorFlow, PyTorch, Python 3, C++, Arduino, Raspberry Pi, Deep Neural Networks, Computer Vision, Robotics, Source Code Review, Code Review, Python, Artificial Intelligence (AI), Deep Learning, Image Processing, Git, Test-driven Development (TDD)Software Developer in R&D
2014 - 2016The Metabolomics Innovation Center- Developed, maintained, and updated multiple web application software, servers and databases using Agile software engineering with a team of software developers.
- Created large-scale web applications to handle more than 300,000 users per month on Drugbank and Human Metabolome Database.
- Published five research papers, academic journals, and over ten bioinformatics application servers and databases using Ruby on Rails, MongoDB, MySQL, AngularJS, JQuery, Twitter Bootstrap, and Python Django.
- Developed internal software libraries and RESTful APIs to facilitate biological data exchange.
- Worked on system administration with cloud servers hosted on Google Compute Engine, Digital Ocean, and AWS.
Technologies: Ruby on Rails (RoR), MySQL, AngularJS, JavaScript, MongoDB, Bootstrap, Python, Django, Google Compute Engine (GCE), DigitalOcean, Puma, Capistrano, Redis, Elasticsearch, jQuery, JSON API, New Relic, SaltStack, NGINX, Agile, Source Code Review, Code Review, Ruby, HTML, Git, REST APIs, CSS, API Integration, Google Cloud Platform (GCP), Full-stack, API Development, Amazon Web Services (AWS), CI/CD Pipelines, Back-end, Test-driven Development (TDD)