Erik Arakelyan, Developer in Copenhagen, Denmark
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Erik Arakelyan

Verified Expert  in Engineering

Bio

Erik is an ML researcher currently pursuing a PhD in machine learning at the University of Copenhagen (UCPH), specializing in topics of NLP, Knowledge Graphs optimizations, and explainability in NLP. He is looking for opportunities to apply his deep learning and software engineering skills in an exciting and challenging project.

Portfolio

Arm
Python 3, C++, Deep Learning, Image Processing, TensorFlow, PyTorch, Keras...
Armenia National SDG Innovation Lab (UNDP)
Python 3, PyTorch, TensorFlow, Generative Pre-trained Transformers (GPT)...
American University of Armenia
University Teaching, C++, Python 3, Algorithms, Deep Learning, Machine Learning...

Experience

Availability

Full-time

Preferred Environment

Ubuntu, Atom, Visual Studio Code (VS Code), Python 3, PyTorch, TensorFlow

The most amazing...

...thing I've developed is a robot system for answering complex queries over Knowledge Graphs. It won the Best Paper award at ICLR 2021.

Work Experience

Machine Learning Engineer | Tech Lead

2020 - 2021
Arm
  • Led a tech team in applied machine learning (AML) for tailoring deep learning (DL) models.
  • Implemented model quantization and optimization pipelines and maintained the internally optimized model repo with complete CI/CD. This resulted in fourfold smaller and faster models across various architectures.
  • Implemented ML pipelines as a part of the AML team. Researched efficient DL methods.
  • Developed models for various NLP tasks and image processing.
Technologies: Python 3, C++, Deep Learning, Image Processing, TensorFlow, PyTorch, Keras, Chainer, Algorithms, Optimization, Hardware Drivers, Linear Algebra, Continuous Integration (CI), Continuous Deployment, DevOps, Machine Learning, Flask, Reinforcement Learning, Docker, Pipelines, Servers, Networking, Artificial Intelligence, Jupyter, Python, Data Science, GitHub, SQL, Statistics, Data Analysis, ETL, Audio, Document Parsing, NLU, Deep Neural Networks (DNNs), Test-driven Development (TDD), Large Language Models (LLMs), Language Models, Chatbots, Classification, Text Classification, Data Pipelines, Graphs

Senior Data Scientist

2019 - 2020
Armenia National SDG Innovation Lab (UNDP)
  • Implemented innovative solutions for improving public policy decision-making and created a platform for real-time analysis and prediction of current touristic activities in Armenia.
  • Created DL models for continuous analysis of time series, images, and text.
  • Created pipelines for continuous scraping and optimized flow for database management and ETL.
Technologies: Python 3, PyTorch, TensorFlow, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), Image Processing, Signal Processing, Algorithms, SQL, CouchDB, Machine Learning, Flask, Reinforcement Learning, Docker, Pipelines, Servers, Networking, Artificial Intelligence, Amazon Mechanical Turk (MTurk), Jupyter, Python, Data Science, GitHub, SpaCy, Statistics, Data Analytics, R, Data Analysis, ETL, Web Scraping, Document Parsing, NLU, Deep Neural Networks (DNNs), Test-driven Development (TDD), Large Language Models (LLMs), Language Models, Chatbots, Classification, Text Classification, Data Pipelines, Graphs

Teaching Associate

2017 - 2020
American University of Armenia
  • Performed as a teaching associate of the deep learning and data structure course at AUA.
  • Conducted weekly problem-solving sessions and programming labs.
  • Directed a final project and bachelor capstone guidance. Composed and graded homework and exams.
Technologies: University Teaching, C++, Python 3, Algorithms, Deep Learning, Machine Learning, Flask, Pipelines, Jupyter, Python, GitHub, SpaCy, Statistics, Data Analytics, R, Data Analysis, ETL, Document Parsing, NLU, Large Language Models (LLMs), Language Models, Classification

Machine Learning Engineer

2017 - 2018
Teamable
  • Created an end-to-end pipeline for automated CV parsing and analysis.
  • Developed models for various NLP tasks like NER, semantic parsing, and topic detection.
  • Developed models for image processing and Flask and Django apps for integration.
Technologies: Django, MongoDB, TensorFlow, PyTorch, SpaCy, Pandas, Flask, Python 3, C++, Cython, DevOps, Machine Learning, Reinforcement Learning, Docker, Pipelines, Servers, Networking, Artificial Intelligence, Amazon Mechanical Turk (MTurk), Jupyter, Python, Data Science, GitHub, SQL, Statistics, Data Analytics, Data Analysis, ETL, Web Scraping, Document Parsing, NLU, Deep Neural Networks (DNNs), Test-driven Development (TDD), Large Language Models (LLMs), Language Models, Classification, Text Classification, Data Pipelines, Graphs

Software Engineering Consultant

2016 - 2017
Wolfram Research
  • Created an end-to-end text to speech (TTS) pipeline integrated into Wolfram Mathematica.
  • Developed software in the signal processing team, enhancing functions within Wolfram Mathematica.
  • Created builds for different projects and optimized structure and flow in different projects.
Technologies: Signal Processing, C++, DevOps, Continuous Deployment, Continuous Integration (CI), Deep Neural Networks (DNNs), Test-driven Development (TDD), Classification

Oral Outstanding Paper Award | ICLR 2021

https://arxiv.org/pdf/2011.03459.pdf
Complex query answering with neural link predictors.

We proposed a framework for efficiently answering complex queries on incomplete Knowledge Graphs. We translated each question into an end-to-end differentiable objective, where a pre-trained neural link predictor computes the truth value of each atom.

Travelinsights

https://www.travelinsights.ai/
A platform for real-time analysis and prediction of current touristic activities in Armenia based on deep learning methods.

The tool allows for scalable real-time analysis of events, sentiments, topics, and insights into Armenia's touristic activities and trends.

Fifth Summer School on Mathematics and Applications at YSU

https://github.com/deeplanguageclass
Lectured and held workshops on NLP topics.

I created models for Armenian Transliteration and pipelines for Armenian Lemmatization and semantic segmentation.
Worked on improving word embeddings and held NLP workshops and sessions.

FastEnt

https://fastent.github.io/
Founder.

Created a pipeline for automated custom named entity recognition and disambiguation. Developed pipelines for continuous scraping and dataset generation and implemented robust methods for named entity generalization and detection.

TorchNorms

https://pypi.org/project/torchnorms/
Created a library for differentiable machine learning based on PyTorch for classic, parametric, and learnable T and S-norms.

The library supports the seamless addition of new differentiable modules and supports complete CI/CD for safety.
2021 - 2022

PhD Degree in Artificial Intelligence

University of Copenhagen - Copenhagen, Denmark

2018 - 2019

Master's Degree in Artificial Intelligence

University College London - London, United Kingdom

2014 - 2018

Bachelor's Degree in Computer Science

American University of Armenia - Yerevan, Armenia

Libraries/APIs

TensorFlow, PyTorch, Keras, SpaCy, Pandas

Tools

Jupyter, GitHub, Mathematica, Atom

Languages

Python 3, SQL, Python, C++, R

Paradigms

Dynamic Programming, Linear Programming, Testing, ETL, Test-driven Development (TDD), DevOps, Continuous Deployment, Continuous Integration (CI)

Platforms

Docker, Ubuntu, Visual Studio Code (VS Code)

Storage

MongoDB, CouchDB, Data Pipelines

Frameworks

Flask, Chainer, Django

Other

Optimization, Software Engineering, Calculus, Linear Algebra, Machine Learning, Deep Learning, Natural Language Processing (NLP), Probabilistic Graphical Models, Knowledge Bases, Knowledge Graphs, Learning Transfer, Signal Processing, Cython, Reinforcement Learning, Open Source Development, Pipelines, Artificial Intelligence, Data Science, Data Analytics, Data Analysis, Web Scraping, Audio, Document Parsing, NLU, Deep Neural Networks (DNNs), Large Language Models (LLMs), Language Models, Chatbots, Generative Pre-trained Transformers (GPT), Classification, Text Classification, Graphs, Research, Bayesian Inference & Modeling, Bayesian Statistics, Probability Theory, Statistics, Explainable Artificial Intelligence (XAI), Deep Reinforcement Learning, Image Processing, University Teaching, Servers, Networking, Amazon Mechanical Turk (MTurk), Algorithms, Statistical Methods, Causal Inference, Hardware Drivers, Fuzzy Logic

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