Machine Learning Engineer specializing in Graph Neural Networks (GNNs), Knowledge Graphs, and Graph Representation Learning. Extensive experience in leveraging Neo4j, PyTorch Geometric for predictive modeling and graph-based recommendation systems. Passionate about applying graph techniques to real-world AI problems.
Hi, I’m
Corina Catarau-Cotutiu
Cluj-Napoca,Romania
Summary
Overview
11
years of professional experience
2
Certifications
Work History
Corina Catarau AI Consultancy S.R.L.
AI Consultant
10.2022 - Current
Job overview
- Designed, deployed, and optimized an LLM-powered document intelligence system for semantic search, text classification, and QA
- Integrated OpenAI GPT models and Hugging Face Transformers, leveraging Neo4j for graph-based data analysis and retrieval-augmented generation (RAG)
- In collaboration with the MLOps team built a scalable, cloud-native pipeline using Docker and AWS Lambda for efficient inference and orchestration
- Implemented CI/CD automation with GitHub, ensuring seamless deployment, monitoring, and model updates in production
- Developed and deployed an AI-driven document management system using MongoDB for structured storage and retrieval
- Implemented an ESG classifier and context-aware QA system, leveraging parent-child hierarchical modeling to enhance comprehension
- Applied chain-of-thought reasoning and context-aware generation (CAG) to improve answer accuracy and document coherence assessment
- Integrated summarization, sentiment analysis, and ESG classification models
- Developed an AI-driven mental health platform utilizing genogram graph data for personalized recommendations
- Leveraged advanced graph analysis and machine learning techniques to provide insights and support mental health practitioners
- Technologies & Tools: AI & Machine Learning: LLMs, Generative AI, NLP, Transformers, OpenAI GPT models, Hugging Face Transformers, PyTorch, LangChain, LLama Index, Cloud & MLOps: AWS (Lambda, EC2, S3), Pub-sub, Docker, LangChain, Weights & Biases, CI/CD
- Databases: Neo4j, MongoDB, PostgreSQL, MySQL
- Data Processing & Analysis: Pandas, NumPy, Dash (mvp interface)
- Natural Language Processing: spaCy, NLTK, BERT, GPT, LangChain
- Prompt Engineering & QA: Few-shot learning, fine-tuning models, context-based retrieval, fine-tuned finbert
City University of London
Visiting Lecturer MSc in Artificial Intelligence
12.2023 - 06.2024
Job overview
- Delivered comprehensive lectures on deep learning techniques for computer vision, covering convolutional neural networks (CNNs), transfer learning, and advanced model architectures (AlexNet, ResNet, Faster R-CNN, Yolo, FCN, vAEs, GNNs etc.)
- Taught key concepts and methods for sequence data analysis, including recurrent neural networks (RNNs), long short-term memory (LSTM) networks, and transformer models
- Independently designed and prepared all lab exercises, developing deep learning models from scratch in PyTorch for both computer vision and sequence analysis
- Systematically logged and tracked model performance using Weights & Biases (WandB), ensuring reproducibility and providing students with insights into model training, hyperparameter tuning, and evaluation
- Technologies & Tools: Deep Learning Frameworks: PyTorch, Computer Vision: CNNs, Transfer Learning, Object Detection, Object Classification, Image Segmentation, Graph Neural Networks, Representation Learning, Sequence Analysis: RNNs, LSTMs, Transformers, Experiment Tracking: Weights & Biases (WandB), Additional Tools: Jupyter Notebooks, Git, Docker
Spirable Ltd.
Lead Research and Development engineer
04.2020 - 11.2020
Job overview
- Company Overview: London
- Led a cutting-edge project to tackle the challenge of attention drop-off in online advertisements
- Developed and implemented an innovative approach inspired by cognitive theories to compute expected attention curves for each element within the creative component
- Analyzed these curves in conjunction with Facebook (FB) metrics, identifying key elements and effects that maximize audience engagement
- This analysis led to the creation of a new feature that significantly enhanced client satisfaction and engagement
- London
- Technologies & Tools: Machine Learning & Data Analysis: Python, Scikit-learn, Pandas, NumPy, Pytorch, Ad Tech & Analytics: Facebook Ads API, Google Analytics, Data Visualization & Experiment Tracking: Matplotlib, Seaborn, Weights & Biases (WandB), Cloud & DevOps: AWS (EC2, S3, Lambda), Docker
Spirable Ltd.
Senior Research and Development engineer
09.2019 - 04.2020
Job overview
- Company Overview: London
- Led efforts to address the challenge of frequent changes in Facebook metrics that impacted our ad pushing platform
- Proposed and implemented a Neo4j graph database solution to streamline the collection and processing of metrics data
- Developed a groundbreaking persona discovery tool leveraging Facebook metrics data and non-negative matrix factorization (NMF)
- London
- Impact: The implementation of the Neo4j graph database enhanced our data processing capabilities, allowing clients to access the latest metrics data promptly and make informed decisions
Spirable Ltd.
Full-stack developer
09.2017 - 09.2019
Job overview
- Company Overview: London
- Contributed to the development and enhancement of the Spirable platform, a client-facing application used by clients to create and push ads across multiple social media platforms
- Designed and implemented the first automatic ad-pushing pipeline, including an early validation system to detect and correct formatting issues before the ad push
- London
- Impact: The implementation of this automated pipeline became the standard template for future client engagements, significantly improving the efficiency of the client-service team
Accesa IT Systems
Junior Full-stack developer
07.2015 - 04.2017
Job overview
- Company Overview: Cluj-napoca, Romania
- Cluj-napoca, Romania
EBS
Developer intern
07.2014 - 08.2014
Job overview
- Company Overview: Cluj-napoca, Romania
- Cluj-napoca, Romania
Education
City, University of London
PhD. from Artificial General Intelligence
10.2020 - 12 2024
University Overview
- PhD title: A model of functional creativity using adaptive concept formation for generalisation enhancement.
- Fully funded- thesis written, viva has to be held
City, University of London
M.Sc. from Artificial Intelligence
09.2019 - 9 2020
University Overview
- 8 topics covered over the course of 1 year: Introduction to Artificial Intelligence, Programming and Mathematics for Artificial Intelligence, Agents and Multi-agents systems, Computational Cognitive Systems, Classification, Prediction, Optimization, Explainable Artificial Intelligence
- Thesis title: Computational creativity for puzzle solving generalisation and transfer
- GPA: Distinction. First of the cohort.
City, University of London
PGCert. from Data Science
09.2018 - 6 2019
University Overview
- 4 topics covered over the course of 1 year: Principles of data-science, Visual Analytics, Neural computing, Big data
- GPA: Post-graduate certificate with distinction.
University of Gdańsk
from European Agent Systems
08.2017 - 8 2017
University Overview
14 topics covered over the course of 1 week: Automated Security Analysis for Multi-agent Systems, Cooperative Games in Structured Environments, Modelling and Analysis of Cyber-Social Systems, Decision Making for Artificial Intelligence, Assignment Problems - from Classical Mechanism Design to Multi-Agent Systems.
Technical University of ClujnapocaCluj-napoca
B.Sc. from Computer Science
10.2013 - 7 2017
University Overview
- Final project: Heart disease classification using genetic generated neural network layout
- 54 Modules studied in total over a course of four years: Fundamental Algorithms, Image Processing, Intelligent system, Knowledge-based system, Database design, Object oriented programming, Data structures and design, Computer architecture, User interface design, Functional programming, Prolog.
- GPA: GPA 8.5
Technical University of KosiceKosice
Android Development introduction
02.2016 - 2 2016
University Overview
Skills
Python
undefinedCertification
2017, IELTS, 8, 8, 8, 8, C1
Publications
Publications
- Aigenc: Ai generalisation via creativity, Catarau-Cotutiu, C., Mondragon, E., & Alonso, E., Proceedings of the 22nd EPIA Conference on Artificial Intelligence, EPIA 2023, https://doi.org/10.48550/arXiv.2205.09738
- Aigenc: An ai generalisation model via creativity, Catarau-Cotutiu, C., Mondragon, E., & Alonso, E., https://doi.org/10.48550/arXiv.2205.09738
Personal Information
Personal Information
Nationality: RomanianTimeline
Visiting Lecturer MSc in Artificial Intelligence
City University of London
12.2023 - 06.2024
AI Consultant
Corina Catarau AI Consultancy S.R.L.
10.2022 - Current
City, University of London
PhD. from Artificial General Intelligence
10.2020 - 12 2024
Lead Research and Development engineer
Spirable Ltd.
04.2020 - 11.2020
Senior Research and Development engineer
Spirable Ltd.
09.2019 - 04.2020
City, University of London
M.Sc. from Artificial Intelligence
09.2019 - 9 2020
City, University of London
PGCert. from Data Science
09.2018 - 6 2019
Full-stack developer
Spirable Ltd.
09.2017 - 09.2019
University of Gdańsk
from European Agent Systems
08.2017 - 8 2017
Technical University of Kosice
Android Development introduction
02.2016 - 2 2016
Junior Full-stack developer
Accesa IT Systems
07.2015 - 04.2017
Developer intern
EBS
07.2014 - 08.2014
Technical University of Clujnapoca
B.Sc. from Computer Science
10.2013 - 7 2017
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