Sergio Paulo Caetano

Sergio Paulo Caetano

Ph.D. Student in Artificial Intelligence

Ajou University, South Korea

I am a Ph.D. student in Artificial Intelligence at Ajou University, South Korea. My research focuses on Requirements Engineering for AI-based sociotechnical systems, with emphasis on fairness, explainability, responsible AI, and robust AI software systems. My broader background includes machine learning, deep learning, computer vision, natural language processing, cloud computing, big data, distributed systems, and high-performance computing.

EmailGitHubGoogle ScholarORCIDLinkedInCV (PDF)Lab Profile
Sergio Paulo Caetano profile photo

News

  • 2026-07Personal Ph.D. website launched.
  • 2026-06Continued research progress on MIFF (Multidimensional Iterative Fairness Framework).
  • 2026-05Systematic literature review on fairness requirements engineering in progress.

Education

  • Ph.D. in Artificial Intelligence

    Ajou University, South Korea

    Expected completion: 2027

  • Master's in Industrial Engineering

    Ajou University, South Korea

    Graduated: 2023

    Thesis: Design Knowledge Discovery and Extractor Analytical Pipeline System for COVID-19 Research Based on Hadoop-Spark Big Data Frameworks.

  • Bachelor's in Marine Geology

    Eduardo Mondlane University, Mozambique

    Graduated: 2017

    Thesis: Morphodynamics and Sedimentary Facies of Bons Sinais Estuary in the Gazela River.

Research

Fairness Requirements Engineering for AI Systems

Investigating how fairness concerns can be elicited, specified, and validated as first-class requirements throughout the AI system lifecycle.

MIFF: Multidimensional Iterative Fairness Framework

A framework for iteratively addressing fairness across multiple dimensions — from elicitation and specification to operationalization, monitoring, and revision.

Fairness-Context Representation and Traceability

Developing representations that connect fairness requirements to their sociotechnical context and maintain traceability across development artifacts.

Lifecycle-Oriented Fairness: Elicitation to Monitoring and Revision

Studying how fairness requirements evolve across the full engineering lifecycle, including post-deployment monitoring and requirement revision.

Case Studies: Lending and Hiring AI Systems

Applying fairness requirements engineering methods to real-world sociotechnical domains, including loan approval and hiring decision systems.

Previous Research: Distributed Systems, Big Data, and HPC

Previous work on cloud computing, Hadoop-Spark big data frameworks, graph partitioning, Apache Flink checkpointing, and HPC task execution optimization.

Publications

  • Conference paper2024

    Surrogate Model of Autotuning Techniques for Optimizing HPC Task Execution

    Sergio Paulo Caetano

    KCC 2024, Korea Information Science Society

  • Conference paper2024

    Dynamic Programming-Based Multilevel Graph Partitioning for Large-Scale Graph Data

    Sergio Paulo Caetano

    Winter Conference of the Korean Telecommunications Society

  • Conference paper2023

    Analysis of the In-Memory Checkpointing Approach in Apache Flink

    Sergio Paulo Caetano

    Summer Conference of the Korean Telecommunications Society

  • Under review2026

    Fairness Requirements Engineering for AI-Based Sociotechnical Systems: A Systematic Literature Review

    Sergio Paulo Caetano, Seok-Won Lee

    Manuscript under review

  • Manuscript in preparation2026

    Fairness-Relevant Context Mining for ML-Enabled Systems

    Sergio Paulo Caetano, Seok-Won Lee

    Manuscript in preparation

Teaching

  • Teaching Assistant

    2023.03 – 2024.12

    Department of Software and Computer Engineering, Ajou University, South Korea

    • Artificial Intelligence
    • Computer Networks
    • Object-Oriented Programming in Java: lab sessions and grading

  • Teaching Assistant

    2016.02 – 2017.12

    Department of Marine Geology, Eduardo Mondlane University, Mozambique

    • Mathematics: Differential Equations and Integral Calculus
    • Statistics and Probability

Additional Teaching Experience

  • Middle School AI

    Introductory AI concepts taught to middle school students.

  • High School AI

    AI fundamentals and applied concepts taught to high school students.

  • Algebra / Math Tutoring

    Tutoring in algebra and general mathematics.

  • Spanish A1 Teaching

    Beginner-level (A1) Spanish language instruction.

Projects

MIFF Framework

Ongoing development of the Multidimensional Iterative Fairness Framework for fairness requirements engineering.

Fairness Requirements SLR

A systematic literature review mapping the state of the art in fairness requirements engineering for AI systems.

FairCredit / Fairness Readiness Assistant (Planned)

Planned fairness readiness assistant applied to credit/lending decision systems.

AI Education Materials (Planned)

Planned teaching materials for AI education across middle school, high school, and tutoring contexts.

Technical Skills

Programming
C, C++, Python, SQL, Java, JavaScript, R, MATLAB, Scala
Machine Learning / AI
Scikit-learn, PyTorch, TensorFlow, Keras, computer vision, natural language processing
Big Data / Distributed Systems
Hadoop, Spark, MapReduce, CUDA, MPI, multithread programming
Tools / Platforms
MySQL Workbench, Tableau, MS Office, Ubuntu, Windows, macOS

Awards and Scholarships

  • BK Graduate Student Research Scholarship, Ajou University2023–Present
  • Exemplary Academic Performance Award, K-TOPIK Program, Konyang University2020
  • Korean Government Scholarship Program (GKS), South Korea2019–2023
  • Eduardo Mondlane University Full Scholarship, Mozambique2014–2017

Languages

  • English
  • Korean
  • Portuguese
  • Spanish

Service

  • Korean Researcher Information (KRI)

    Registered researcher profile under the Korean Researcher Information system.

  • Seminar and Conference Presentations

    Presentations delivered at lab seminars and academic conferences.

  • Lab Responsibilities

    Ongoing responsibilities within the research lab.

  • Academic Service and Peer Review

    Peer review and broader academic service activity, updated as engagements are confirmed.

Contact

EmailGitHubGoogle ScholarORCIDLinkedInCV (PDF)NISE Lab / Lab Profile

Location: Department of Artificial Intelligence, Ajou University, Suwon, South Korea