I’m driven by a deep curiosity. I channel this into research that matters to academics and addresses real-world challenges.

Agile Transformation

Agile methods are popular in software development. But, they have challenges. My research is based on facts, not just opinions. I study:

  • Agile Dynamics: I explore Agile processes. I look at technical, organizational, and psychological aspects. I aim to understand these elements in real settings.
  • Tailored Agile: A single approach doesn’t always work. I guide businesses to adjust Agile methods to fit them. This approach aims to get the most from Agile and avoid problems.
  • Team Work: I study what makes Agile teams work well. I look at team dynamics and communication. My research gives insights to build effective Agile teams.

Future of Work & Digital Resilience

The COVID-19 pandemic changed how we work. It highlighted the need for digital strength. I study:

  • Work Dynamics: I look at the “Future of Work”. I focus on remote and hybrid work models. These models bring challenges and opportunities, especially for software engineers. I aim to give insights to improve work in this new era.
  • Well-being & Productivity: The pandemic affected software engineers’ well-being. I study its impact on their mood, work output, and how they adjust to new work settings. My goal is to find best practices to support a balanced work-life.
  • Business Resilience: Many businesses sped up their digital changes. I study their strategies and outcomes. I aim to give insights to help businesses be digitally strong against disruptions.

Advanced Data Analysis

Navigating the complexities of software engineering research requires innovative and robust analytical methods. My dedication to evidence-based insights and empirical standards has led to explore and advocate for the following:

  • Soft Theory Advocacy: In scenarios where controlled experiments aren’t feasible, we advocate for the use of soft theory, particularly soft modeling techniques. These approaches, grounded in scientific research, offer pragmatic solutions without compromising on data integrity or research quality.
  • SEM: SEM is a tool to study complex relationships. My work in ACM Computing Surveys talks about the use of PLS-SEM in software engineering.
  • Publication Standards: Peer-review has challenges. I support the idea of Empirical Standards in Software Engineering. This gives clear guidelines for authors and reviewers.
  • Soft Theory: When we can’t do controlled experiments, we use soft theory. These methods are based on research. They give practical solutions without losing data quality.

There is no end. There is no beginning. There is only the infinite passion of life.

– Federico Fellini