Biography

I’m Tomislav Đuričić, a Senior Machine Learning Researcher at Know Center Research in Graz, Austria. I’m pursuing my PhD at Graz University of Technology, focusing on “Beyond-Accuracy Optimization in Social-based Recommender Systems.” I work primarily in the Fair AI Lab, developing advanced AI solutions for industry and research applications.

My work bridges academic research with industry applications. I’ve developed recommendation systems for student job platforms, time-series forecasting solutions for automotive inventory planning, and outlier detection systems for retail optimization. In my research, I explore graph neural networks, trust-based recommender systems, and evaluation metrics beyond simple accuracy, publishing findings in venues like RecSys, ECAI, and ASONAM. Throughout my career, I’ve led both research-focused and industry-oriented projects, including initiatives funded by the European Union.

My research interests include recommender systems, graph neural networks, trust networks, and user modeling. I’m currently focused on integrating large language models into immersive AR/VR environments for industrial applications, creating digital twins that enhance machine operation and training.

I earned my MSc and BSc in Software Engineering and Information Systems from the University of Zagreb’s Faculty of Electrical Engineering and Computing. Outside of work, I enjoy playing basketball with the Gold Diggers, jogging, and attending music events.

Interests
  • Recommender Systems
  • Trust-based Systems
  • Network Science & Complex Networks
  • Graph Neural Networks
  • User Modeling & Behavior Analysis
  • Information Retrieval
  • Machine Learning
  • Natural Language Processing
  • Large Language Models
  • Diversity & Fairness in AI
  • Computational Social Science
Education

  • PhD Candidate in Computer Science, 2018-2025 (expected)

    Institute of Interactive Systems and Data Science at the Graz University of Technology

  • MSc in Software Engineering and Information Systems, 2013-2015

    Faculty of Electrical Engineering and Computing at the University of Zagreb

  • Erasmus+ Exchange Program, 2012-2013

    Department of Informatics at the Karlsruhe Institute of Technology

  • BSc in Software Engineering and Information Systems, 2009-2013

    Faculty of Electrical Engineering and Computing at the University of Zagreb

Skills

Research & Problem-solving

Research design, experimental methodology, data interpretation, and statistical analysis. Grant proposal writing, project management, and funding acquisition. Literature synthesis, critical evaluation, and identification of research gaps. Scientific writing and presentation for academic conferences and industry audiences. Interdisciplinary collaboration across academic and industry settings. Translating complex research findings into practical applications.

ML & Data Science

Deep learning with PyTorch and graph neural networks (PyG). LLM integration, evaluation, and fine-tuning for industrial applications. Recommendation systems design and evaluation (Scikit-surprise, Elliot, ScaR). Natural language processing with transformers and embeddings. Data manipulation and visualization (Pandas, NumPy, Matplotlib, Seaborn). Time-series forecasting, anomaly detection, and dimensionality reduction. User behavior modeling and network analysis (NetworkX).

Software Engineering

Python and Java development with object-oriented design patterns. AR/VR development with Unity for industrial digital twins and immersive analytics. Microservices architecture and RESTful API design. Database systems (SQL, NoSQL) including PostgreSQL, Apache Solr, and MongoDB. Web application development with Spring Boot and related frameworks. Containerization with Docker and deployment on cloud platforms (AWS, GCP). CI/CD pipelines and version control with Git.

Experience

 
 
 
 
 
Know Center Research
Senior Machine Learning Researcher
Know Center Research
January 2024 – Present Graz, Austria

Conducting advanced research in:

  • Immersive analytics and AI assistants for industrial digital twins
  • Graph neural networks with focus on beyond-accuracy metrics
  • Large language model integration in AR/VR environments
  • Contributing to scientific publications and research proposals
 
 
 
 
 
Graz University of Technology
University Assistant (PhD Researcher)
Graz University of Technology
October 2018 – December 2023 Graz, Austria

Conducted doctoral research and academic activities including:

  • Research on graph neural networks, recommender systems, and user behavior
  • Contributing to successful research proposals worth over €600,000
  • Co-advising bachelor and master thesis students in ML and data science
  • Teaching courses and leading lab exercises in data science topics
  • Automotive diagnostic systems utilizing sequential recommendation (AVL Research Project)
  • Publishing in top-tier conferences (RecSys, ASONAM, HT) and journals
  • Presenting research at international conferences and workshops
 
 
 
 
 
Know Center Research
Project Manager & ML Engineer
Know Center Research
June 2017 – December 2023 Graz, Austria

Led strategic projects while advancing technical implementation:

  • Project manager for the Studo/Talto job matchmaking project (2017-2019, team of 5)
  • Project manager for the COGSTEPS ERASMUS+ project (2020-2023)
  • Project manager for the VHDD platform development (2018-2019)
  • Securing €150,000 FFG funding for the Studo project follow-up (“FAT”)
  • Designing and implementing recommender systems across multiple domains
  • Authoring scientific publications on recommender systems and ML applications
  • Bridging academic research and practical industry applications
 
 
 
 
 
Know Center Research
Machine Learning Engineer & Data Scientist
Know Center Research
March 2016 – May 2017 Graz, Austria

Developed advanced ML solutions for industry partners:

  • Designing real-time data pipelines for retail analytics (Detego Fashion)
  • Creating time-series prediction dashboard for Porsche Holding Salzburg
  • Implementing image analysis systems for photo calendar recommendations
  • Contributing to the ScaR recommender framework development
  • Applying machine learning techniques to various industry problems
  • Transforming research concepts into production-ready systems
 
 
 
 
 
Know Center Research
ERASMUS+ internship
Know Center Research
March 2015 – August 2015 Graz, Austria
Conducted research on real-time and trust-based recommender systems, culminating in my master’s thesis “Real-Time Recommendations Based on Social Trust” supervised by Prof. Dr. Sc. Vedran Podobnik, Assoc.-Prof. Dr. Elisabeth Lex, and Dr. Emanuel Lacić. My research findings and implementation were successfully integrated into the ScaR (Scalable Recommendation-as-a-service) framework, contributing to the organization’s recommender system capabilities.
 
 
 
 
 
FZI Research Center for Information Technology
Junior Android Developer
FZI Research Center for Information Technology
January 2013 – October 2013 Karlsruhe, Germany
As part of the Erasmus+ student exchange program, I developed a mobile application for real-time student feedback in collaboration with the Informatics Institute and FZI Research Center. This work formed the basis of my Bachelor’s thesis “Mobile Live Interest Meter Application,” supervised by Prof. Dr. Rudi Studer and Dr. Verónica Rivera Pelayo, providing a digital solution for capturing and analyzing immediate student engagement data.
 
 
 
 
 
Ericsson Nikola Tesla d.d.
Student Developer
Ericsson Nikola Tesla d.d.
July 2014 – September 2014 Zagreb, Croatia / Budapest, Hungary
Selected for Ericsson’s competitive Summer Camp internship program, where I integrated a code plagiarism detection toolkit into the company’s internal IDE using JavaScript, HTML, CSS, and the Dojo toolkit. The international program spanned 5 weeks across Zagreb and Budapest locations, providing hands-on development experience and insights into enterprise software development in the telecommunications industry.

Publications

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Tomislav Đuričić, Peter Müllner, Nicole Weidinger, Neven ElSayed, Dominik Kowald, Eduardo Veas (2024). AI-Powered Immersive Assistance for Interactive Task Execution in Industrial Environments. ECAI'24.

PDF Cite Project Video DOI

Tomislav Đuričić, Dominik Kowald, Emanuel Lacić, Elisabeth Lex (2023). Beyond-Accuracy: A Review on Diversity, Serendipity, and Fairness in Recommender Systems Based on Graph Neural Networks. Front. Big Data.

PDF Cite Project DOI

Mario Lovrić, Tomislav Đuričić, Hussain Hussain, Bono Lucić, Roman Kern (2023). PyChemFlow: an automated pre-processing pipeline in Python for reproducible machine learning on chemical data. ChemRxiv.

PDF Cite DOI

Emanuel Lacić, Tomislav Đuričić, Leon Fadljević, Dieter Theiler, Dominik Kowald (2023). Uptrendz: API-Centric Real-time Recommendations in Multi-Domain Settings. ECIR'23.

PDF Cite Project DOI

Tomislav Đuričić, Dominik Kowald, Markus Schedl, Elisabeth Lex (2022). My friends also prefer diverse music: homophily and link prediction with user preferences for mainstream, novelty, and diversity in music. ASONAM'21.

PDF Cite Project DOI

See all publications

Selected Projects

*
All Recommender Systems Project Management Graph Neural Networks Time-Series Analysis User Modeling
DDIA - Data Driven Immersive Analytics
Research project enhancing digital twin interactions and immersive analytics using personalized AI, AR/VR interfaces, and physiological sensing for improved remote collaboration, support, and training in industry.
DDIA - Data Driven Immersive Analytics
AVL Research Project: Intelligent Fault Tree Construction for Automotive Diagnostics
Research collaboration between Graz University of Technology and AVL List GmbH focused on applying sequential recommendation methods and text embeddings to automate and enhance automotive diagnostic fault tree construction.
AVL Research Project: Intelligent Fault Tree Construction for Automotive Diagnostics
COGSTEPS - Crossing the Gap: Startup Education and Support for Researchers
ERASMUS+ project designed to bridge academia and the startup ecosystem, developing a platform and educational programs to foster innovation and entrepreneurial skills among researchers and scientists.
COGSTEPS - Crossing the Gap: Startup Education and Support for Researchers
DDAI - Explainable, Verifiable, and Privacy-Preserving Data-Driven AI
Research module developing privacy-preserving, verifiable, and explainable AI solutions, combining cryptography, explainable AI, and machine learning, contributing to both academic knowledge and practical industry applications.
DDAI - Explainable, Verifiable, and Privacy-Preserving Data-Driven AI
Virtuelles Haus der Digitalisierung (VHDD)
Successfully developed and deployed multiple personalized content recommendation use cases using the ScaR recommender framework for the Virtual House of Digitalization, enhancing content discovery and user engagement.
Virtuelles Haus der Digitalisierung (VHDD)
Studo/Talto Job Matchmaking Platform
Developed and deployed a personalized job matchmaking recommender system for Studo, later spun off into the standalone platform Talto, significantly enhancing student engagement and job application rates.
Studo/Talto Job Matchmaking Platform
Porsche Holding Demand Prediction Dashboard
Developed a data-driven time-series prediction dashboard for Porsche Holding Salzburg, optimizing monthly car order volumes using Python, R, Plotly, ARIMA, SARIMA, and LSTM (Keras).
Porsche Holding Demand Prediction Dashboard
Detego Fashion Outlier Detection
Developed a real-time data pipeline and integrated an outlier detection system to optimize garment placement in retail stores, improving sales performance. Built with Java, Spring Boot, RabbitMQ, Apache Solr, Python, and sklearn.
Detego Fashion Outlier Detection
Photo Calendar Recommendation System
Developed an end-to-end machine learning pipeline that analyzes image metadata to intelligently assign photos to calendar months. Built with Java 8, Spring Boot, RabbitMQ, Apache Solr, Maven, and Jenkins CI/CD. Implemented data processing with PySpark, HDFS, and Hadoop. Created machine learning models using Weka with JUnit and integration testing for quality assurance.
Photo Calendar Recommendation System
ScaR: Real-Time Recommender Framework
Core contributor to ScaR, an in-house scalable recommender framework following the microservices architecture, supporting real-time recommendations and streaming data processing using Java, Apache Solr, Spring Boot, Docker, and Jenkins.
ScaR: Real-Time Recommender Framework

Teaching

Data Science in Business 2
Graz University of Technology and University of Graz Oct 2022 – Mar 2025

Lecturer for this graduate-level course in the joint Computational Social Systems Master’s program. My responsibilities included:

  • Leading practical lab sessions focused on natural language processing techniques
  • Teaching text preprocessing, feature engineering, and modern NLP approaches
  • Introducing students to transformer architectures and their applications
  • Creating and evaluating a final project using financial textual data
  • Providing guidance on Python libraries including NLTK, spaCy, and Hugging Face Transformers
  • Fostering critical thinking and practical problem-solving skills
Complexity Science
Graz University of Technology Oct 2018 – Feb 2019

Lecturer for this course in the Information and Computer Engineering Master’s program, focusing on:

  • Advanced topics from “Complexity - A Guided Tour” by Melanie Mitchell
  • Creating and grading student assignments on complexity principles
  • Teaching concepts including fitness landscapes and evolution of cooperation
  • Guiding students through computational models of complex systems
  • Supporting students in developing mathematical and computational understanding of complexity

Services

Session Chairing, Mentoring, and Workshop Organization
Mar 2016 – Apr 2025
Program Committee Membership and Reviewing
Mar 2016 – Apr 2025

Conferences and Workshops:

  • ACM RecSys (2018, 2021, 2022, 2023)
  • ACM SIGIR (2022, 2023, 2024, 2025)
  • ACM IUI (2022, 2023, 2024, 2025)
  • ACM WebConf (2022, 2023)
  • ACM WSDM (2022)
  • ACM Hypertext (2019, 2020)
  • ACM UMAP (2021, 2022)
  • ECIR (2023)
  • SIAM SDM (2023)
  • MSM Workshop (2019)
  • RS-BDA (2016)

Journals:

  • Frontiers in Big Data | Recommender Systems
  • Social Network Analysis and Mining (SNAM)
  • Complexity
  • Information Sciences

Awards & Grants

Best Presentation Award
Know Center Research and Institute of Interactive Systems and Data Science Sep 2022
Received the Best Presentation Award at the institute’s PhD retreat for my presentation on beyond-accuracy optimization in social-based recommender systems.
Travel Grant - Euro CSS Symposium
European Symposium on Societal Challenges in Computational Social Science Sep 2019
Received a competitive travel grant to attend the European Symposium in Zurich focused on “Polarization and Radicalization,” where I presented my research on cross-platform content diffusion.
Travel Grant - Euro CSS Summer School
European Summer School in Computational Social Science Jun 2019
Awarded a travel grant to participate in the third Summer School on analyzing multimedia data in Berlin, focusing on computer vision, spatial analysis of urban spaces, and multimedia content modeling.
Erasmus+ Traineeship Scholarship
Erasmus+ Programme Feb 2015 – Aug 2015
Secured an Erasmus+ traineeship scholarship to complete a 6-month research internship at Know Center Research in Graz, Austria, where I developed my master’s thesis on social trust-based recommendations that was later integrated into their production systems.
Erasmus+ Student Exchange Scholarship
Erasmus+ Programme Sep 2011 – Aug 2012
Received a full-year Erasmus+ scholarship to study at the prestigious Karlsruhe Institute of Technology in Germany, where I completed specialized coursework in software engineering and mobile application development.

Supervised Theses

Improving the Accuracy-Diversity Trade-off in Recommender Systems with Reranking Strategies
Sep 2023
Master’s Thesis, Stefan Russman (Co-advisor) Research on optimizing recommender systems to balance accuracy with diversity through post-processing reranking techniques. In progress
Analysis of Cross-Platform User Behavior on the Example of Reddit and YouTube Comments
Sep 2020 – Mar 2021
Bachelor’s Thesis, Volker Seiser (Co-advisor) Investigated how user language in YouTube comments changes after videos are shared on Reddit’s conspiracy forums, finding measurable linguistic convergence between platforms. Completed

Invited Talks

Presentation at the EBDVF 2021
I gave a presentation on the topic of “Big Data and AI for the Financial Sector - challenges and opportunities” at the EBDVF 2021
Dec 1, 2021 12:30 PM — 2:00 PM Online
Video EBDVF 2021
Panel Discussion at Zagreb Connect 2021
I participated in a panel discussion at Zagreb Connect, where we discussed building successful and sustainable startup ecosystems.
Nov 23, 2021 10:00 AM — 2:15 PM ZICER
Video Zagreb Connect

Popular Topics

AI Assistants Automotive Chemical Informatics Cold-Start Problem Collaborative Filtering Community Structure Data Pipeline Digital Twins Diversity Embeddings Graph Neural Networks Machine Learning Matchmaking Project Management Real-Time Analytics Real-Time Recommendations Recommender Systems Trust Networks User Behavior User Modeling

Contact

Have a question or want to work together? I’d love to hear from you! Please use the form below to send me a message, and I will get back to you as soon as possible.