I am deeply fascinated by how machines can be programmed to simulate human intelligence, support domain experts in tackling complex problems, and uncover meaningful patterns within large-scale datasets.
Here is a selection of my publications, sorted by year. For a comprehensive list, please visit my scholar profiles, accessible from the home page.
Throughout my life, I have undertaken a variety of manual and intellectual jobs, and I have learned that—regardless of the task—excellence comes naturally when you are truly passionate about what you do. Research, however, has proven to be the most challenging endeavor I have ever faced. It is inherently multifaceted, and requires a combination of hard and soft skills that can only be developed through continuous growth and learning.
Despite these challenges, research is extraordinarily stimulating. Since embarking on this journey, Mondays have never felt exhausting—perhaps because, in research, you never fully disconnect!
❤️ Be passionate: Without passion, surviving in the academic world is nearly impossible.
💪 Work hard: I firmly believe that if you put in the effort, something good will eventually happen.
❓ Embrace doubt and uncertainty: This is where research truly begins; without them, you are not really doing research.
🎯 Choose the right topic: Academia can be highly competitive and often driven by quantitative metrics such as publications and citations. A "hot" topic may help increase visibility, but niche topics can also thrive with the right strategy.
🌍 Know the community: Build relationships—they should know you, and you should know them. Moreover, communities often have research "paradigms" (benchmarks, venues, standards) that you should follow.
👩🔬 Intuition vs. experience: A new idea stems from intuition, but conducting technically sound experiments and writing high-quality papers comes with experience. Early on, work with an experienced researcher to learn the culture of work.
🛠️ Start small: New ideas don't come out of nowhere. Begin by replicating a recent study from a top conference or journal. This provides a baseline for comparison and may inspire open questions to tackle in future work.
🔗 Tackle open problems: Every community faces challenges that must be addressed to advance the state of the art. In machine learning, this may involve adapting existing methods to new problems or proposing novel approaches that outperform current solutions.
📚 Choose the right venue: Identify where the authors you frequently cite publish their work; this may help you find the best venue for your paper. Besides, avoid predatory journals—one good article is far better for your career than many poor-quality ones.
👥 Know your audience: Assume a reasonable level of expertise from your readers and avoid being overly didactic.
⏳ Structure your article like an hourglass: Start with broad concepts, narrow down to technical specifics, and then widen again in the conclusions.
✍️ Write with care: Use LaTeX for precision and pay attention to structure, grammar, punctuation, formulas, figures, and formatting. If you do not care about your paper, why should reviewers?
🚫 Avoid overdoing self-citations: Be selective and balanced.
🙏 Respect reviewers: Acknowledge their voluntary work and carefully consider their feedback.
🌟 Be humble: Soften over-enthusiastic claims. Your work matters, but it is only one piece of a larger puzzle and is always open to improvement—or even falsification. Even Einstein approached his theories with caution.
I firmly believe that life is shaped by key moments—sometimes driven by unconscious choices—that can significantly alter our path. One such moment for me is captured in this photo: receiving an award for the best presentation at SFLA 2018, presented by Prof. Giovanna Castellano. The prize? A book on Fuzzy Logic by Zadeh (which my pug later found delicious!).
Since that moment, my journey took a new direction, and I am confident that the best is yet to come!