{
  "generated_at": "2026-10-13T07:37:25Z",
  "source": "cv.yml",
  "summary": "Associate Research Professor and computational social scientist based in Novi Sad, Serbia. Current roles: Associate Research Professor, Scientific Computing Laboratory at Institute of Physics Belgrade; Assistant Professor / Research Associate at University of Novi Sad. Primary topics: computational social science, online-community analysis, machine learning, natural language processing, network analysis, LLM-agent simulation, and multimodal emotion analysis.",
  "person": {
    "name": "Aleksandar Tomašević",
    "alternate_name": "Aleksandar Tomasevic",
    "email": "atomashevic@gmail.com",
    "phone": "(+381) 69 1196392",
    "url": "https://atomasevic.xyz",
    "titles": [
      "Associate Research Professor",
      "Computational Social Scientist",
      "Applied AI Researcher"
    ],
    "location": {
      "city": "Novi Sad",
      "postal_code": 21000,
      "country": "Serbia"
    },
    "profiles": [
      {
        "network": "ORCID",
        "username": "0000-0003-4863-6051",
        "url": "https://orcid.org/0000-0003-4863-6051"
      },
      {
        "network": "Google Scholar",
        "username": "nPTApsYAAAAJ",
        "url": "https://scholar.google.com/citations?user=nPTApsYAAAAJ"
      },
      {
        "network": "GitHub",
        "username": "atomashevic",
        "url": "https://github.com/atomashevic"
      },
      {
        "network": "LinkedIn",
        "username": "atomasevic",
        "url": "https://www.linkedin.com/in/atomasevic/"
      },
      {
        "network": "X",
        "username": "atomasevic",
        "url": "https://x.com/atomasevic"
      }
    ]
  },
  "current_roles": [
    {
      "organization": "Institute of Physics Belgrade",
      "organization_url": "https://www.ipb.ac.rs/",
      "location": "Belgrade / Serbia",
      "position": "Associate Research Professor, Scientific Computing Laboratory",
      "start_date": "2025-07-01",
      "end_date": "present",
      "current": true,
      "highlights": [
        "Built computational workflows for large-scale data analysis, simulation, and model evaluation in Python and R.",
        "Developed and validated machine learning, NLP, and network-analysis pipelines for behavioral and online-community data.",
        "Worked on AI-system evaluation problems involving trust, toxicity, conversation quality, agent behavior, and online-community dynamics.",
        "Contributed to technically complex platforms using PostgreSQL, Dockerized services, Linux, and reproducible experiment workflows."
      ]
    },
    {
      "organization": "University of Novi Sad",
      "organization_url": "https://www.uns.ac.rs/",
      "location": "Novi Sad / Serbia",
      "position": "Assistant Professor / Research Associate",
      "start_date": "2016-02-01",
      "end_date": "present",
      "current": true,
      "highlights": [
        "Led data-intensive projects using Python and R to analyze large behavioral, textual, and network datasets.",
        "Designed machine learning and NLP workflows for online-community research, including text classification, sentiment analysis, toxicity-related analysis, and simulation support.",
        "Built automation scripts and reproducible pipelines for data cleaning, modeling, visualization, reporting, and experimental analysis.",
        "Collaborated with physicists, psychologists, and sociologists on technically demanding computational research."
      ]
    }
  ],
  "focus_topics": [
    "Online-community analysis",
    "Machine learning",
    "Natural language processing",
    "Text classification",
    "Sentiment analysis",
    "Toxicity analysis",
    "Emotion recognition",
    "LLM systems",
    "Agent simulation",
    "Python",
    "R",
    "PostgreSQL",
    "Docker",
    "Transformer models",
    "Scientific computing",
    "Reproducible workflows"
  ],
  "work_history": [
    {
      "organization": "Institute of Physics Belgrade",
      "organization_url": "https://www.ipb.ac.rs/",
      "location": "Belgrade / Serbia",
      "position": "Associate Research Professor, Scientific Computing Laboratory",
      "start_date": "2025-07-01",
      "end_date": "present",
      "current": true,
      "highlights": [
        "Built computational workflows for large-scale data analysis, simulation, and model evaluation in Python and R.",
        "Developed and validated machine learning, NLP, and network-analysis pipelines for behavioral and online-community data.",
        "Worked on AI-system evaluation problems involving trust, toxicity, conversation quality, agent behavior, and online-community dynamics.",
        "Contributed to technically complex platforms using PostgreSQL, Dockerized services, Linux, and reproducible experiment workflows."
      ]
    },
    {
      "organization": "University of Novi Sad",
      "organization_url": "https://www.uns.ac.rs/",
      "location": "Novi Sad / Serbia",
      "position": "Assistant Professor / Research Associate",
      "start_date": "2016-02-01",
      "end_date": "present",
      "current": true,
      "highlights": [
        "Led data-intensive projects using Python and R to analyze large behavioral, textual, and network datasets.",
        "Designed machine learning and NLP workflows for online-community research, including text classification, sentiment analysis, toxicity-related analysis, and simulation support.",
        "Built automation scripts and reproducible pipelines for data cleaning, modeling, visualization, reporting, and experimental analysis.",
        "Collaborated with physicists, psychologists, and sociologists on technically demanding computational research."
      ]
    },
    {
      "organization": "University of Virginia, School of Data Science",
      "organization_url": "https://www.virginia.edu/",
      "location": "Charlottesville, VA / USA",
      "position": "Fulbright Visiting Researcher",
      "start_date": "2023-10-15",
      "end_date": "2024-01-31",
      "current": false,
      "highlights": [
        "Developed `transforEmotion`, an R package with Python backend for multimodal emotion recognition across text, image, and video data.",
        "Built reproducible machine learning workflows connecting transformer-based models, statistical analysis, and large-scale media data processing."
      ]
    },
    {
      "organization": "Eipix Entertainment",
      "organization_url": "https://www.eipix.com/",
      "location": "Novi Sad, Serbia",
      "position": "Medior Game Designer",
      "start_date": "2014-05-01",
      "end_date": "2016-02-01",
      "current": false,
      "highlights": [
        "Worked with cross-functional production teams on game systems, content design, and delivery across 10+ shipped titles."
      ]
    }
  ],
  "education": [
    {
      "institution": "University of Novi Sad",
      "institution_url": "https://www.uns.ac.rs/",
      "study_type": "PhD",
      "area": "Quantitative Methods",
      "location": "Novi Sad, Serbia",
      "start_date": "2012-10-01",
      "end_date": "2019-03-08",
      "highlights": [
        "Research and training centered on statistics, computational methods, network analysis, and large-scale behavioral data in social sciences."
      ]
    },
    {
      "institution": "University of Novi Sad",
      "institution_url": "https://www.uns.ac.rs/",
      "study_type": "Master",
      "area": "Social Sciences",
      "location": "Novi Sad, Serbia",
      "start_date": "2011-10-01",
      "end_date": "2012-10-01"
    },
    {
      "institution": "University of Novi Sad",
      "institution_url": "https://www.uns.ac.rs/",
      "study_type": "Bachelor",
      "area": "Social Sciences",
      "location": "Novi Sad, Serbia",
      "start_date": "2007-10-01",
      "end_date": "2011-06-30"
    }
  ],
  "projects": [
    {
      "name": "YSocial Multi-Agent Social Platform Simulation",
      "affiliation": "Institute of Physics Belgrade / Research collaboration",
      "start_date": "2025-09-01",
      "end_date": "present",
      "current": true,
      "highlights": [
        "Built and evaluated components of an LLM-powered social media twin spanning microblogging and forum-style simulations for trust, toxicity, and conversation-quality research.",
        "Worked on agent memory, retrieval, and behavioral parameterization to improve reply selection, interaction pacing, and coherence in multi-agent threads.",
        "Contributed to a Python/Flask/SQLAlchemy stack with SQLite and PostgreSQL backends, covering experiment metadata, agent populations, recommendations, posts, reactions, and agent-opinion tracking.",
        "Used Dockerized PostgreSQL services and OpenAI-compatible backends including Ollama and vLLM to support simulation runs, annotation workflows, and system evaluation.",
        "Investigated concrete failure modes such as repetitive outputs, thread-structure breaks, and parent-child mismatches, then used real community data to guide validation and calibration."
      ]
    },
    {
      "name": "MADOC Dataset and Tools",
      "url": "https://zenodo.org/records/14637314",
      "affiliation": "Institute of Physics Belgrade",
      "start_date": "2025-01-01",
      "end_date": "present",
      "current": true,
      "highlights": [
        "Built a research dataset and tooling stack for large-scale online-community analysis, with emphasis on reproducible ingestion, cleaning, and downstream modeling workflows.",
        "Implemented NLP pipelines for text classification, toxicity detection, and sentiment analysis over cross-platform community text.",
        "Developed `pyMADOC`, a Python package for dataset access and text processing using pandas, NumPy, and scikit-learn."
      ]
    },
    {
      "name": "transforEmotion R package",
      "url": "https://github.com/atomashevic/transforEmotion",
      "affiliation": "Personal collaboration",
      "start_date": "2023-10-01",
      "end_date": "present",
      "current": true,
      "highlights": [
        "Built an R package with a Python backend for multimodal emotion recognition across text, image, and video, with more than 9k CRAN installs.",
        "Integrated transformer-based models into reproducible data-processing workflows for large-scale media analysis.",
        "Maintained the package as production-quality open-source software with GitHub Actions CI/CD and cross-language tooling."
      ]
    },
    {
      "name": "COVID-19 Data Analysis and Visualization Platform",
      "url": "https://scienceversuscorona.shinyapps.io/covid-overview/",
      "affiliation": "Data Versus Corona initiative",
      "start_date": "2020-04-01",
      "end_date": "2020-06-30",
      "current": false,
      "highlights": [
        "Engineered R data pipelines to clean, analyze, and visualize epidemiological data from multiple sources.",
        "Built a real-time data fetching and processing API for automated updates and reproducible reporting.",
        "Created interactive visualizations for communicating complex health data clearly to broad audiences."
      ]
    }
  ],
  "skills": [
    {
      "category": "Data Science & Machine Learning",
      "items": [
        "Python: pandas, NumPy, scikit-learn, transformers, PyTorch, Flask, SQLAlchemy",
        "Machine Learning: feature engineering, fine-tuning, benchmarking, evaluation",
        "NLP: text classification, sentiment analysis, embeddings, topic extraction, toxicity detection",
        "Data Visualization: Plotly, matplotlib",
        "R: statistical analysis, package development",
        "SQL: PostgreSQL, SQLite, MySQL"
      ]
    },
    {
      "category": "Cloud & Tools",
      "items": [
        "Linux and CLI-first workflows",
        "Scientific Computing: HPC environments, remote compute, reproducible pipelines",
        "Ops: Docker, GitHub Actions CI/CD",
        "LLM Systems: Ollama, vLLM, OpenAI-compatible APIs",
        "Version Control: Git and GitHub workflows",
        "Development Environments: JupyterLab, VSCode, Neovim"
      ]
    },
    {
      "category": "Research & Communication",
      "items": [
        "Experimental design and validation",
        "Communication in interdisciplinary technical teams",
        "Technical writing and documentation",
        "Problem-solving and analytical thinking"
      ]
    }
  ],
  "languages": [
    {
      "language": "English",
      "fluency": "C1"
    },
    {
      "language": "French",
      "fluency": "B1"
    },
    {
      "language": "Serbian",
      "fluency": "Native"
    }
  ],
  "interests": [
    "Linux geek",
    "Football statistics and analytics: xG analysis, passing networks, player tracking data",
    "Video games: console (PS4, Switch), retro gaming",
    "Board games: Everdell, The Isle of Cats, Cartographers"
  ],
  "site_pages": [
    {
      "name": "Home",
      "url": "https://atomasevic.xyz/"
    },
    {
      "name": "Publications",
      "url": "https://atomasevic.xyz/publications.html"
    },
    {
      "name": "Software",
      "url": "https://atomasevic.xyz/software.html"
    },
    {
      "name": "Talks",
      "url": "https://atomasevic.xyz/talks.html"
    },
    {
      "name": "Updates",
      "url": "https://atomasevic.xyz/updates.html"
    },
    {
      "name": "CV PDF",
      "url": "https://atomasevic.xyz/cv.pdf"
    }
  ]
}