Lovro Iliassich, Machine Learning Developer in Rijeka, Croatia
Lovro Iliassich

Machine Learning Developer in Rijeka, Croatia

Member since February 20, 2016
Lovro is a machine learning engineer and data scientist, especially enthusiastic about deep learning applications. Combining his academic knowledge with practical experience in the industry, he can contribute to any part of an AI software development process. Lovro's work experience ranges from startups to corporations—he worked as an engineer at Amazon—and research in academic institutions and universities.
Lovro is now available for hire




Rijeka, Croatia



Preferred Environment

Amazon Web Services (AWS), Python 3, Python

The most amazing...

...research I've developed is a post-doc project at the European Space Agency that uses computer vision for the Mars Lander navigation.


  • Machine Learning Engineer | Data Scientist | Technical Screener

    2017 - PRESENT
    Toptal and Toptal Clients
    • Interviewed 500 Toptal candidates as a technical screener for the artificial intelligence and data science specializations.
    • Worked for more than two years on an NLP project focusing on language models and social media post analysis.
    • Developed a computer vision pipeline with a convolutional neural network model for the visual analysis of lab samples.
    • Developed a predictive model for chronic disease detection from genomic data using Spark.
    • Built predictive models of customer behavior (churn, lifetime, and spending).
    • Developed a convolutional neural network model for sound recognition and classification.
    • Developed a computer vision/machine learning service for automatic lab sample assessment.
    • Architected an automated test assessment tool (computer vision, OCR).
    Technologies: Amazon Web Services (AWS), Keras, OpenCV, Pandas, Python 3, SQL, Artificial Intelligence (AI), Machine Learning, Algorithms, Scikit-learn, TensorFlow, Python, Computer Vision, Deep Neural Networks, Data Science, Natural Language Processing (NLP), Deep Learning, PyTorch, Regression, Regression Modeling, Classification, Neural Networks, Convolutional Neural Networks, XGBoost, Visualization, Recommendation Systems, Image Recognition, Predictive Modeling, CatBoost, Language Models, Linux, OCR, Minimum Viable Product (MVP)
  • Machine Learning Developer

    2021 - 2023
    Trust & Safety Laboratory Inc.
    • Developed and maintained an NLP model and the pipeline.
    • Processed texts from textual databases and reviews.
    • Developed language models for semantic text comparison.
    • Scraped web articles and social networks for targeted content.
    • Developed a model for detecting targeted content in posts.
    Technologies: Python, Machine Learning, Natural Language Processing (NLP), Deep Neural Networks, CatBoost, Language Models, Amazon Web Services (AWS), Regression, Regression Modeling, Classification, Neural Networks, XGBoost, Visualization, Deep Learning, PyTorch, Linux
  • Data Scientist

    2020 - 2021
    Freelance Clients
    • Developed a model for detecting early stages of cancer based on genomic data.
    • Developed a model for detecting chronic kidney disease based on genomic data.
    • Dealt with both small datasets and huge ones using Spark.
    Technologies: Data Science, Predictive Modeling, Predictive Analytics, Clinical Trials, Genomics, Classification
  • Software Development Engineer

    2017 - 2018
    • Developed services for Amazon's global fashion retail program.
    • Set up and deployed services for European markets.
    • Worked with notifications, email services, and templates.
    Technologies: Amazon Web Services (AWS), Full-stack, Java, Linux
  • Research Scholar

    2015 - 2016
    Drexel University
    • Brought in as a visiting scholar at the Department of Computer Science, Database Group.
    • Researched mining and modeling rank and preference data.
    • Implemented a Java library for handling and mining rank and preference data.
    • Published papers on novel approaches to model user preferences.
    Technologies: Pandas, Python 3, Data Science, Java, Artificial Intelligence (AI), Machine Learning, Algorithms, Python, Classification, Visualization
  • Research Engineer

    2012 - 2015
    • Parallelized machine learning algorithms (SVM, affinity propagation (AP), gradient descent, and more).
    • Conducted high-performance computing low-level optimization. Adapted algorithms for a large-memory (8 TB RAM) NUMA architecture, on a low level (in C/C++), with cache processes' awareness, memory block latencies, and process to the core assignment.
    • Worked on a semantic web project (RDF, Wikidata mining). Implemented a crawler and category recommender system for Wikipedia.
    Technologies: Python 3, Data Science, Java, Machine Learning, Algorithms, MATLAB, Python, C, C++, Classification, Visualization, Linux
  • Assistant Professor

    2011 - 2012
    Metropolitan University
    • Taught at the undergraduate and graduate level, including courses in web systems and applications, distributed systems, and information system design.
    • Worked on the development of the university information system and its business process management workflow.
    Technologies: Java, UML, Web, University Teaching
  • Post-doc Researcher

    2010 - 2011
    University of Eastern Piedmont
    • Worked on a European Space Agency project on using computer vision for Mars Lander navigation.
    • Implemented a real-time navigation system in C/C++ with OpenCV. Analyzed the image stream from the camera attached to the bottom of Mars Lander with the task of calculating the position of the lander (coordinates, altitude, attitudes).
    • Tracked features in the video. Filtered the output and combined information with other sensors (lidar, inertial measurement unit).
    • Modeled Mars surface in Java 3D.
    • Built a Mars Lander landing simulator in C/C++ and MATLAB.
    Technologies: OpenCV, Java, Artificial Intelligence (AI), Machine Learning, Algorithms, MATLAB, C, C++, Computer Vision, Visualization, Image Recognition
  • Ph.D. Student

    2006 - 2010
    University of Turin, Department of Computer Science
    • Completed doctoral studies in the field of data mining and machine learning.
    • Performed text mining and document classification on local government data (NLP).
    • Researched sequential pattern mining, recognizing users by keyboard strokes.
    • Developed a log mining model for predicting usage of a grid computing network.
    • Contributed to fields of graph analysis and complex systems analysis.
    Technologies: Data Science, Java, Machine Learning, Algorithms, Weka, Predictive Modeling
  • Software Engineer

    2001 - 2006
    • Designed and architected a wide area network monitoring system used in several huge organizations and companies (banks and telecommunications).
    • Designed, implemented, and led the team of the hospital information system currently in use in about 75% of the hospitals in Serbia.
    • Gained experience in all aspects of the implementation of large information systems, from interviews, specifications, and UML models to database design, back-end business logic, front end, web (including web design), and stand-alone clients.
    • Designed, architected, and implemented a government information system, fleet management system, and more.
    Technologies: Full-stack, SQL, Java, UML, HTML, Web, Databases


  • Ranked Data Analysis

    Mining and modeling ranked (preference) data. The research project resulted in new methods of using partial user preferences for modeling user population.

  • It Snows

    A personal pet project: a ski community mobile application. I built the server back end and web services and implemented an Android mobile application as a front end.

  • Java Affinity Propagation Library

    A parallelized Java implementation of the affinity propagation clustering algorithm.

  • Mandrago

    A personal startup project of mine—a mobile workforce and dispatching system. I served as a co-owner, architect, designer, and developer. I implemented the whole stack, from the infrastructure, back end, web front end, and mobile front end.

  • Heliant HIS

    I architected and designed the hospital information system used currently by about three quarters of the hospitals and clinics in Serbia. The system covers the hospital workflow, scheduling, medical records, etc.

  • Network Monitoring System

    A wide-area network monitoring system. Used by the Academic Network of Serbia, National Bank, and a couple of banks and telecommunications companies.

  • Skidea

    My own startup project—Ski resort maps on Garmin GPS devices. I collected and processed OpenStreetMaps geospatial data to create custom Garmin ski maps. I implemented a web interface and back end, offering free and paid versions of ski resort maps.

  • Mountain Rescue Service Information System

    I worked on the architecture and development of the Mountain Rescue Service information system, including the workflow of mountain rescuers and ski patrollers: HRMS, shifts, rescue missions, and reports. I built the back end in AWS using lambda functions, API Gateway, DynamoDB, and Cognito. I developed the front end in React.

  • SailWeek Staff

    SailWeek is a company that organizes weekly yachting tours with 20–50 sailboats in a fleet. This requires managing skippers, hostesses, and boats.

    I worked on the architecture and development of the company's information system, which included the workflow of skippers and hostesses: HRMS, assigning boats, and reports. I built the back end in AWS using lambda functions, API Gateway, DynamoDB, and Cognito. I developed the front end in React.

  • Clustering Algorithms: From Start to State of the Art (Publication)
    Clustering algorithms are very important to unsupervised learning and are key elements of machine learning in general. These algorithms give meaning to data that are not labelled and help find structure in chaos. But not all clustering algorithms are created equal; each has its own pros and cons. In this article, Toptal Freelance Software Engineer Lovro Iliassich explores a heap of clustering algorithms, from the well known K-Means algorithm to the elegant, state-of-the-art Affinity Propagation technique.


  • Languages

    Python, Java, SQL, Python 3, CSS, HTML5, HTML, UML, C++, JavaScript, C
  • Libraries/APIs

    REST APIs, Scikit-learn, TensorFlow, Keras, OpenCV, XGBoost, Pandas, NumPy, PyTorch, Google API, React, Spark ML, jQuery, PySpark, Google Maps API, PayPal API, CatBoost
  • Tools

    Jupyter, Adobe Photoshop, Amazon Simple Queue Service (SQS), Amazon SageMaker, MATLAB, Trello, Amazon Cognito, AWS Simple Notification Service (AWS SNS)
  • Paradigms

    Distributed Computing, RESTful Development, Parallel Computing, REST, Model View Controller (MVC), Data Science, Object-oriented Programming (OOP), Functional Programming, ETL, High-performance Computing, Distributed Programming, Test-driven Development (TDD), Kanban
  • Platforms

    Jupyter Notebook, Amazon Web Services (AWS), Amazon EC2, Android, Linux, Windows, Web, Databricks, Google Cloud Platform (GCP), AWS Lambda, Docker
  • Storage

    Database Modeling, Amazon S3 (AWS S3), PostgreSQL, MySQL, Amazon DynamoDB, Google Cloud, Databases
  • Other

    Algorithms, Recurrent Neural Networks, Unsupervised Learning, Clustering Algorithms, Clustering, Regression Modeling, Regression, Classification Algorithms, Classification, Deep Neural Networks, Deep Learning, Convolutional Neural Networks, Neural Networks, Computer Vision, Machine Learning, Data Mining, Data Modeling, Scientific Computing, Data Visualization, Artificial Intelligence (AI), Natural Language Processing (NLP), Web Development, Software Architecture, Back-end, Data Scientist, APIs, Full-stack, Data Architecture, Recommendation Systems, Image Recognition, Predictive Modeling, Sentiment Analysis, Geospatial Data, Cloud Platforms, Graphical Models, Image Processing, Data Analysis, Time Series, Time Series Analysis, Data Analytics, Data Reporting, Statistics, Visualization, University Teaching, Minimum Viable Product (MVP), BERT, Data Scraping, Distributed Systems, Web Crawlers, Cloud, Big Data, Serverless, Data Engineering, OpenStreetMap, Stochastic Modeling, Web Scraping, Signal Processing, Robot Operating System (ROS), Reinforcement Learning, Generative Adversarial Networks (GANs), Web MVC, Mapping, Language Models, OCR, Amazon API Gateway, PDF, ChatGPT, A/B Testing, Predictive Analytics, Clinical Trials, Genomics
  • Frameworks

    Android SDK, Play Framework, Selenium, JUnit, Apache Spark, Spark


  • Ph.D. in Computer Science
    2006 - 2010
    University of Turin, Department of Informatics - Turin, Italy
  • Master of Science Degree in Computer Systems and Networks
    2001 - 2004
    University of Belgrade, School of Electrical Engineering - Belgrade, Serbia
  • Bachelor of Science Degree in Computer Science and Technology
    1995 - 2001
    University of Belgrade, School of Electrical Engineering - Belgrade, Serbia

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