Simone Romano, Developer in Helsinki, Finland
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Simone Romano

Verified Expert  in Engineering

Machine Learning Developer

Location
Helsinki, Finland
Toptal Member Since
January 3, 2022

Simone is a machine learning scientist and engineer with experience in academia and enterprises, including Microsoft and Huawei. He likes to work at the intersection of deep machine learning, NLP, and information retrieval. Simone also loves to work on exploration analysis and building theoretically sound machine learning pipelines ready for production. He especially enjoys building web products.

Availability

Full-time

Preferred Environment

Windows, Linux, Visual Studio Code (VS Code), Jupyter Notebook, Google Colaboratory (Colab), Git, Amazon Web Services (AWS)

The most amazing...

...thing I've worked on is a low-latency and web-scale machine learning system for query suggestions used by hundreds of million users worldwide.

Work Experience

NLP and Machine Learning Solution Architect

2022 - PRESENT
Toptal
  • Defined the machine learning and data roadmap for startups with no in-house machine learning expert.
  • Identified the key machine learning solutions and technology for startups with no in-house machine learning expert.
  • Implemented actionable machine learning and data pipelines for MVPs and products.
  • Iterated on improving models and pipelines on existing ML products.
Technologies: Natural Language Processing (NLP), GPT, Generative Pre-trained Transformers (GPT), Machine Learning, Computer Vision, Location Services, Google Location API, Python, JavaScript, You Only Look Once (YOLO), Hugging Face, Transformers, Deep Learning, Amazon Web Services (AWS), Amazon SageMaker, Generative Adversarial Networks (GANs), Language Models, Competitive Programming, OpenAI, GPT-2, PyTorch, Generative Pre-trained Transformer 3 (GPT-3), PostgreSQL, Blockchain, Text Generation, GitHub, Information Extraction, Data Visualization, Statistical Analysis, Image Processing, TensorFlow, DALL-E, Generative Artificial Intelligence (GenAI), API Integration, Team Leadership, Speech Recognition, Random Forests, Supervised Machine Learning, Microservices Architecture, GPU Computing, NVIDIA TensorRT, Explainable Artificial Intelligence (XAI), Scraping, PDF Scraping, ChatGPT, Streamlit, OpenAI GPT-4 API, OpenAI GPT-3 API, Text to Speech (TTS), Computer Vision Algorithms, TensorFlow Deep Learning Library (TFLearn), Benchmarking, Open Neural Network Exchange (ONNX), Large Language Models (LLMs), Speech Synthesis, NLU, Deep Neural Networks, Diffusion Models, LLaMA, Image Recognition, Neural Networks, R&D

Indie Scientist, Engineer, and Business Developer

2020 - PRESENT
Self-employed
  • Brainstormed, researched, developed, and implemented fully functional web apps with machine learning at the core.
  • Developed productized services for a machine learning agency and a search engine customization agency.
  • Built a variety of products based on machine learning and web scraping. Used machine learning techniques like NLP, computer vision, and information retrieval.
  • Contributed to every part of the launch of a new project, including research, engineering, marketing, and business development.
Technologies: Machine Learning, Web, Stripe, REST APIs, Data Science, Amazon Web Services (AWS), Web UX Design, Web UI Design, Web Search, Web Scraping, Web Crawlers, Information Retrieval, Deep Learning, Neural Networks, Python, Django, BERT, Git, GitLab, Scikit-learn, Vue, jQuery, Artificial Intelligence (AI), Google Colaboratory (Colab), Data Mining, Generative Pre-trained Transformers (GPT), GPT, Natural Language Processing (NLP), English, Entity Extraction, Entity Relationships, MySQL, SQL, Object Detection, Object Recognition, Linear Regression, Hypothesis Testing, Data Analysis, Data Analytics, Natural Language Understanding (NLU), Text Mining, JSON, Statistical Data Analysis, OpenAI, GPT-2, PyTorch, Language Models, Generative Pre-trained Transformer 3 (GPT-3), Text Generation, GitHub, Information Extraction, Data Visualization, Statistical Analysis, Image Processing, TensorFlow, Generative Adversarial Networks (GANs), DALL-E, Generative Artificial Intelligence (GenAI), Stable Diffusion, DreamBooth, Midjourney, API Integration, Supervised Machine Learning, Microservices Architecture, GPU Computing, NVIDIA TensorRT, Streamlit, OpenAI GPT-4 API, OpenAI GPT-3 API, Text to Speech (TTS), Computer Vision Algorithms, TensorFlow Deep Learning Library (TFLearn), Open Neural Network Exchange (ONNX), Large Language Models (LLMs), Speech Synthesis, NLU, Deep Neural Networks, Diffusion Models, LLaMA, Image Recognition, R&D

Principal Scientist

2019 - 2020
Huawei Technologies Co.
  • Designed and developed an NLP multilingual auto-moderation system.
  • Guided the project engineering and machine learning strategy.
  • Performed extensive research, literature review, and comparative analysis.
  • Gathered data and supervised the collection of text data performed by third parties.
  • Implemented machine learning pipelines to automatically classify text data in multiple languages achieving over 90% accuracy.
  • Interfaced with the development team to deploy models and pipelines in the Huawei Cloud infrastructure.
  • Published patents to protect intellectual property.
Technologies: Python, PyTorch, TensorFlow, TensorBoard, Ansible, Jupyter Notebook, Hugging Face, Cloud, Pandas, Flask, Docker, Scikit-learn, SciPy, Linux, Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT), GPT, Machine Learning, Data Science, Data Mining, Artificial Intelligence (AI), Google Colaboratory (Colab), Web, English, Entity Extraction, Entity Relationships, REST APIs, Web Scraping, Linear Regression, Hypothesis Testing, Data Analysis, Data Analytics, Natural Language Understanding (NLU), Text Mining, JSON, Statistical Data Analysis, GPT-2, Language Models, Generative Pre-trained Transformer 3 (GPT-3), PostgreSQL, Text Generation, GitHub, Information Extraction, Data Visualization, Generative Artificial Intelligence (GenAI), API Integration, Team Leadership, Deep Learning, Supervised Machine Learning, Microservices Architecture, GPU Computing, Explainable Artificial Intelligence (XAI), Recurrent Neural Networks (RNNs), PDF Scraping, Computer Vision Algorithms, TensorFlow Deep Learning Library (TFLearn), Benchmarking, Open Neural Network Exchange (ONNX), Large Language Models (LLMs), NLU, Deep Neural Networks, Image Recognition, Neural Networks, R&D

Scientific Advisor

2018 - 2020
Sciar
  • Provided advice on the state-of-the-art augmented reality and machine learning techniques to advance scientific discoveries in laboratories.
  • Provided advice on best practices to implement machine learning pipelines.
  • Advised on local tech hubs and startup venues locally and internationally.
Technologies: Augmented Reality (AR), HoloLens, Mixed Reality (MR), Machine Learning, Data Science, Computer Vision, Python, Artificial Intelligence (AI), Data Mining, English, Linear Regression, Data Analysis, Image Analysis, Image Analytics, Statistical Data Analysis, GitHub, Natural Language Processing (NLP), GPT, Generative Pre-trained Transformers (GPT), Information Extraction, Data Visualization, Statistical Analysis, TensorFlow, Team Leadership, Microservices Architecture, GPU Computing, Explainable Artificial Intelligence (XAI), Computer Vision Algorithms, TensorFlow Deep Learning Library (TFLearn), Benchmarking, Open Neural Network Exchange (ONNX), Deep Neural Networks, Image Recognition, Neural Networks, R&D

Founder

2018 - 2019
Tywai
  • Put together a team of scientists and engineers to develop a deep learning and computer vision platform for photo processing.
  • Led the process of creating, operating, and growing a tech startup.
  • Developed a deep learning pipeline to process photos with augmented reality techniques.
  • Oversaw the design and development of a React Native app to interface with the machine learning back end.
Technologies: Computer Vision, Python, TensorFlow, Generative Adversarial Networks (GANs), Augmented Reality (AR), React Native, Android, iOS, PyTorch, Business Development, Business Design, Startups, Lean Startups, Amazon Web Services (AWS), 3D, Google Cloud, PIL, Scikit-image, Artificial Intelligence (AI), Machine Learning, Data Mining, Web, English, Azure, Object Detection, Object Recognition, Linear Regression, Data Analysis, Google Cloud Platform (GCP), Image Analysis, Image Analytics, Text Mining, JSON, Statistical Data Analysis, GitHub, Information Extraction, Data Visualization, Image Processing, API Integration, Team Leadership, Microservices Architecture, GPU Computing, NVIDIA TensorRT, Explainable Artificial Intelligence (XAI), Computer Vision Algorithms, TensorFlow Deep Learning Library (TFLearn), Open Neural Network Exchange (ONNX), NLU, Deep Neural Networks, Image Recognition, Neural Networks

Applied Scientist

2016 - 2017
Microsoft
  • Worked on Bing and Windows query autosuggest, which are currently used by hundreds of million users worldwide.
  • Optimized the machine learning-based autosuggest system capable of a very low-latency throughput worldwide, spelling correct, making suggestions based on the user context and background.
  • Deployed various machine learning and data pipelines A/B testing their performance on hundreds of million users.
  • Worked with machine learning pipelines crunching terabytes of data.
  • Interfaced with researchers from Microsoft Research to design new innovative ways to work on text data.
Technologies: C#, Machine Learning, Apache Hive, Azure Machine Learning, Jenkins, Microsoft Cognitive Toolkit (CNTK), A/B Testing, Linear Regression, Linear Optimization, Deep Learning, Microsoft, Big Data, Data Science, Data Mining, Generative Pre-trained Transformers (GPT), GPT, Natural Language Processing (NLP), SQL, JavaScript, Git, Microsoft AI, Search Engines, Web, Artificial Intelligence (AI), English, Entity Extraction, Entity Relationships, Azure, Hypothesis Testing, Data Analysis, Data Analytics, Natural Language Understanding (NLU), Text Mining, JSON, Data Engineering, Statistical Data Analysis, Competitive Programming, Language Models, GitHub, Information Extraction, Data Visualization, Statistical Analysis, API Integration, Supervised Machine Learning, Microservices Architecture, GPU Computing, Explainable Artificial Intelligence (XAI), Recurrent Neural Networks (RNNs), Benchmarking, NLU, Deep Neural Networks, Neural Networks, R&D

Research Scientist

2016 - 2016
National Institute of Informatics
  • Worked on the analysis of high-dimensional datasets.
  • Developed techniques to be more effective in high-dimensional datasets. These techniques are based on the intrinsic dimensionality theory.
  • Presented results at conferences and in research seminars.
  • Applied novel techniques to data from the World Health Organization (WHO) and energy consumption data to increase energy efficiency.
Technologies: MATLAB, C, Amazon Web Services (AWS), Correlation Analysis, Information Theory, Intrinsic Dimensionality, C++, Git, Artificial Intelligence (AI), Machine Learning, Data Mining, English, Linear Regression, Hypothesis Testing, Data Analysis, Data Analytics, Statistical Data Analysis, GPT, Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT), Information Extraction, Data Visualization, Statistical Analysis, GPU Computing, Explainable Artificial Intelligence (XAI), Benchmarking, Deep Neural Networks, Neural Networks, R&D

Academic Tutor

2014 - 2015
University of Melbourne
  • Taught to bachelor and master students fundamentals on data mining and natural language processing.
  • Designed Kaggle competition about Twitter geolocation.
  • Designed tests and final exams to assess students' skills.
Technologies: University Teaching, Java, Generative Pre-trained Transformers (GPT), GPT, Natural Language Processing (NLP), Association Rule Learning, Twitter, Dynamic Programming, Data Science, Data Mining, Artificial Intelligence (AI), English, Linear Regression, Hypothesis Testing, Data Analysis, Data Analytics, Text Mining, Statistical Data Analysis, Data Visualization, Deep Neural Networks

PhD Student

2012 - 2015
University of Melbourne
  • Completed doctoral studies in machine learning and data mining.
  • Published work on several top-tier venues, such as The International Conference on Machine Learning (ICML), The Conference on Knowledge Discovery and Data Mining (KDD), and The Journal of Machine Learning Research (JMLR).
  • Won best paper award for ''A Framework to Adjust Dependency Measure Estimates for Chance" paper at the SIAM International Conference on Data Mining.
  • Worked on several domains and applications like web, social media, medicine, biology, traffic data, and sport.
  • Focused on improving classification algorithms, feature selection techniques, clustering algorithms, anomaly detection techniques, among others.
Technologies: Machine Learning, Data Mining, Weka, Java, MATLAB, R, Time Series Analysis, Analysis, Random Forests, Information Theory, Clustering, Anomaly Detection, Generative Pre-trained Transformers (GPT), GPT, Natural Language Processing (NLP), Amazon Web Services (AWS), Amazon S3 (AWS S3), Amazon Elastic Container Service (Amazon ECS), Amazon EC2, Regression, Classification Algorithms, Feature Selection, Artificial Intelligence (AI), English, Hypothesis Testing, Data Analysis, Data Analytics, Natural Language Understanding (NLU), Image Analysis, Image Analytics, Text Mining, Statistical Data Analysis, Information Extraction, Data Visualization, Statistical Analysis, Explainable Artificial Intelligence (XAI), Deep Neural Networks

Research Scientist

2011 - 2012
University of Padova
  • Worked on response prediction for the treatment of hepatitis C in collaboration with medical doctors.
  • Developed interpretable predictive models based on decision trees.
  • Created novel models that showed actions that doctors can take into consideration to improve treatment response.
Technologies: Data Mining, Medicine, Predictive Modeling, Artificial Intelligence (AI), Machine Learning, English, Hypothesis Testing, Data Analysis, Data Analytics, Statistical Data Analysis, Information Extraction, Explainable Artificial Intelligence (XAI), Deep Neural Networks

Data Analyst

2011 - 2012
Euromonitor International
  • Analyzed data from national markets in the clothing industry to predict future trends.
  • Wrote business intelligence reports for companies interested in understanding future trends.
  • Interviewed major players in the industry to ground prediction models on their background expertise.
Technologies: Market Research & Analysis, Regression, Technical Writing, Writing & Editing, Stakeholder Interviews, Interviews, Business Intelligence (BI), Predictive Analytics, Data Mining, English, Data Analysis, Data Analytics, Statistical Data Analysis, Statistical Analysis

Web Developer

2006 - 2008
Ewebb
  • Worked as a web developer and designer, building fully functional company websites and eCommerce websites.
  • Designed front ends and back ends working on client-side and server-side scripting.
  • Interfaced with clients to understand their user needs.
Technologies: Active Server Pages (ASP), ASP.NET, Full-stack, Back-end, Front-end, CSS, HTML, Ajax, PayPal, Web Development, Web UX Design, Web UI Design, Web, MySQL, SQL, Statistical Data Analysis, PostgreSQL

Bing and Windows Search

http://www.bing.com
An autosuggest system for the search engine Bing and Windows.

The system currently serves different markets in the US, Europe, Asia, and Australia. It can serve hundreds of thousands of keystrokes per second via a distributed algorithm.

Automatic Multilingual Content Moderation

https://consumer.huawei.com/en/mobileservices/appgallery/
Users download apps in the Huawei app gallery and write comments and reviews. They are allowed to reply to other users' reviews.

I was a key player in implementing a machine learning pipeline to perform automatic content moderation. This consisted of research and development of state-of-the-art NLP methods, data gathering, model development, and deployment to production.

Emojuju

https://emojuju.com/
The web app automatically recognizes faces on pictures to place emojis on them.

It makes use of a neural network written in JavaScript to process pictures on your device to assure privacy. No picture is uploaded to any back end for privacy purposes.

Tabslu

A marketplace where you are allowed to sell your data.

Your data is stored on a Google sheet that you own and can modify. By plugging in your data to Tabslu, your users can pay a subscription using Stripe to access it.

I built the whole marketplace from scratch and integrated it with Google APIs to use Google Sheets as the back end.

Tywai

A mobile app combined with a machine learning pipeline in the back end to automatically add augmented reality to your pictures.

I put together a team of scientists and engineers for this task. Managed the implementation of some end applications, such as changing the color of clothing and adding writings and advertising on it in a realistic way.

Business Link

An image-based search engine for company logos.

This system allows searching across companies' webpages to see if a particular logo is present. It uses OpenAI CLIP for image search. A scraper runs 24/7 to collect companies' websites.

Learning Parameters of 3D Simulations

https://ailivesim.com
AILiveSim is a realistic 3D simulation environment.

It allows to generate realistic maritime simulations. I implemented some computer vision algorithms based on transfer learning to learn parameters of 3D scenes out of the simulation.

For example, I wanted to answer questions like if it is possible to predict the time of the day based on a picture?

Prediction of Hepatitis C Treatment Response

Developed interpretable models based on decision trees to predict outcomes for Hepatitis C treatment.

I performed an in-depth statistical analysis of the medical data provided. It involved dealing with missing values, categorical data, and censored data.

This work happened in collaboration with medical doctors.

Prediction of Fungal Infections

Patients who are severely immunocompromised can incur fungal infections if hospitalized for a long time.

A fungal infection is a major cause of mortality for these patients.

I developed an early diagnostic tool to predict if an infection is starting for doctors to act quickly.

Web App to Find Relevant HTML Tags on Webpages

A machine learning pipeline to identify relevant HTML tags on a web page.

Some examples include:
• Identify the date of a published news article.
• Identify partners on a company's landing page.
• Identify logos of technology in use.

Data is continuously scraped from the web. A custom-built preprocessing engine makes sense of the HTML data and builds the suitable feature representation to apply machine learning approaches.

Relevant tags are automatically found using NLP machine learning techniques.

Adjusting and Designing Dependency Measures

Dependency measures are fundamental for several important applications in machine learning and data mining.

They are ubiquitously used for feature selection, clustering comparisons and validation, splitting criteria in a random forest, and to infer biological networks.

This is my PhD work, and it proposes a series of contributions to improve the accuracy and scalability of machine learning techniques that extensively employ dependency measures.

Search Engines as a Service

A service product where we build small search engines based on machine learning.

Search can be performed on web pages, documents, or images, using textual queries and images as queries. All tech is implemented with open source technology.

Languages

Python, Java, R, SQL, C#, C, Active Server Pages (ASP), CSS, HTML, JavaScript, C++, UML

Frameworks

Django, Streamlit, Flask, React Native, ASP.NET, Bootstrap, OAuth 2, Selenium, JUnit, Spark, Spring Boot, LightGBM, Ruby on Rails (RoR)

Libraries/APIs

PyTorch, TensorFlow, Pandas, Scikit-learn, SciPy, Natural Language Toolkit (NLTK), Stanford NLP, Ggplot2, Matplotlib, XGBoost, NumPy, TensorFlow Deep Learning Library (TFLearn), Stripe, REST APIs, Beautiful Soup, PIL, OpenCV, OpenGL, Fabric, jQuery, Stripe API, Google APIs, Keras, Dask, Vue, Google Location API

Tools

LaTeX, MATLAB, Weka, Stanford NER, Stanford CoreNLP, IPython, IPython Notebook, Microsoft AI, Amazon SageMaker, GitHub, Git, TensorBoard, GitLab, Scikit-image, Ansible, Azure Machine Learning, Jenkins, HoloLens, Canvas, Google Sheets, Asana, GitLab CI/CD, Amazon Elastic Container Service (Amazon ECS), Boto, Boto 3, You Only Look Once (YOLO)

Paradigms

Data Science, Anomaly Detection, Object-oriented Programming (OOP), Web UX Design, Model View Controller (MVC), ETL, Microservices Architecture, Web UI Design, Functional Programming, Parallel Computing, Dynamic Programming, Business Intelligence (BI), Distributed Computing, Unit Testing, Agile Software Development, Continuous Delivery (CD), DevOps, Clean Code, Microservices, Scrum

Platforms

Windows, Visual Studio Code (VS Code), Jupyter Notebook, Web, Amazon EC2, Amazon Web Services (AWS), Linux, Docker, AWS Elastic Beanstalk, Google Cloud Platform (GCP), Android, iOS, Twitter, Ubuntu, Magento, Drupal, Microsoft, AWS Lambda, Azure, Blockchain

Storage

Databases, PostgreSQL, MySQL, JSON, Apache Hive, Amazon S3 (AWS S3), Data Pipelines, Google Cloud, SQLite, Amazon DynamoDB, Database Modeling

Other

Google Colaboratory (Colab), Machine Learning, Artificial Intelligence (AI), University Teaching, Data Mining, Conference Speaking, Presentations, Information Theory, Clustering, Classification Algorithms, Feature Selection, Linear Algebra, Hugging Face, Cloud, Natural Language Processing (NLP), A/B Testing, Linear Regression, Deep Learning, Correlation Analysis, Intrinsic Dimensionality, Computer Vision, Generative Adversarial Networks (GANs), Web Search, Random Forests, Regression, Technical Writing, Predictive Analytics, Predictive Modeling, Full-stack, Facial Recognition, Transformers, BERT, Scraping, Web Scraping, Convolutional Neural Networks, Hypothesis Testing, Decision Trees, Data Reporting, Data Visualization, Big Data, Data Cleaning, Random Forest Regression, Information Retrieval, Search Engines, Data Engineering, Learning Transfer, Neural Networks, Artificial Neural Networks (ANN), Image Processing, English, Entity Extraction, Data Analysis, Data Analytics, Natural Language Understanding (NLU), Image Analysis, Image Analytics, Text Mining, Statistical Data Analysis, Language Models, Competitive Programming, OpenAI, GPT-2, Generative Pre-trained Transformer 3 (GPT-3), Text Generation, Text Analytics, Information Extraction, Statistical Analysis, Generative Artificial Intelligence (GenAI), API Integration, Team Leadership, GPT, Generative Pre-trained Transformers (GPT), Supervised Machine Learning, GPU Computing, NVIDIA TensorRT, Explainable Artificial Intelligence (XAI), PDF Scraping, ChatGPT, OpenAI GPT-4 API, OpenAI GPT-3 API, Computer Vision Algorithms, Benchmarking, Open Neural Network Exchange (ONNX), Large Language Models (LLMs), Speech Synthesis, NLU, Deep Neural Networks, Diffusion Models, LLaMA, Image Recognition, R&D, Biomedical Skills, Time Series Analysis, Algorithms, Distributed Systems, Operations Research, Optimization, Augmented Reality (AR), Association Rule Learning, Analysis, Writing & Editing, Back-end, Front-end, Web Development, Segmentation Algorithms, Data Scraping, Web Crawlers, Startups, Lean Startups, Data Architecture, Recurrent Neural Networks (RNNs), Entity Relationships, Object Detection, Object Recognition, Cloud Infrastructure, APIs, DALL-E, Text to Speech (TTS), Analysis of Variance (ANOVA), Text Classification, Operating Systems, Algebra, Robotics, Signal Processing, Digital Electronics, Telemedicine, Biometrics, Microsoft Cognitive Toolkit (CNTK), Linear Optimization, Mixed Reality (MR), Market Research & Analysis, Stakeholder Interviews, Interviews, Medicine, Ajax, PayPal, OAuth, Statistics, Time Series, Geospatial Data, Servers, CI/CD Pipelines, Federated Learning, AWS DevOps, Elastic Load Balancers, Amazon RDS, Experimental Design, IT Project Management, Support Vector Machines (SVM), Google Drive, Feature Engineering, Scientific Data Analysis, 3D, Business Development, Business Design, Jina AI, Typesense, Reinforcement Learning, Amazon Machine Learning, Location Services, DreamBooth, Stable Diffusion, Midjourney, Speech Recognition

2012 - 2015

PhD Degree in Machine Learning

University of Melbourne - Melbourne

2009 - 2010

Master's Degree in Computer Engineering

University of Padova - Padova

2005 - 2009

Bachelor's Degree in Biomedical Engineering

University of Padova - Padova, Italy

MARCH 2023 - PRESENT

AWS Certified Solutions Architect Professional

Amazon Web Services

NOVEMBER 2022 - PRESENT

AWS Certified Database - Specialty

Amazon Web Services

OCTOBER 2022 - PRESENT

AWS Certified Data Analytics - Specialty

Amazon Web Services

AUGUST 2022 - AUGUST 2025

AWS Certified SysOps Administrator Associate

AWS

AUGUST 2022 - AUGUST 2025

AWS Certified Solutions Architect Associate

AWS

APRIL 2022 - PRESENT

AWS Certified Machine Learning - Specialty

Amazon Web Services

APRIL 2022 - PRESENT

AWS Certified Developer - Associate

Amazon Web Services

APRIL 2022 - PRESENT

AWS Certified Cloud Practitioner

Amazon Web Services

DECEMBER 2011 - PRESENT

Artificial Intelligence

Udacity

DECEMBER 2011 - PRESENT

Machine Learning

Coursera

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