I am deeply fascinated by how machines can be programmed to simulate human intelligence, assist domain experts in solving complex problems, and uncover meaningful patterns in vast 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 various manual and mental jobs, and I have learned that no matter the task, excellence comes naturally if you are passionate about it. Research, however, has proven to be the most challenging endeavor I have faced. It is multifaceted, demanding a combination of hard and soft skills that can only be honed through continuous growth and learning.
Despite its challenges, research is incredibly stimulating. Since embarking on this journey, Mondays have never felt exhausting—perhaps because, in research, you never truly disconnect!
In my humble opinion, to do good research you should:
❤️ 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: Research starts here; without it, you're not really doing research.
🎯 Choose the right topic: Academia can be competitive, often relying on quantitative measures like publications and citations... A "hot" topic might help you publish more and gain visibility, but niche topics can still 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 quality articles 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 and may inspire open questions to tackle in future work.
🔗 Tackle open problems: Communities often face challenges that are crucial to solving in order to advance the state of the art. In machine learning research, adapt an existing method to a new problem or propose a novel approach that outperforms the current state of the art.
📚 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 certain level of expertise from readers. Avoid being overly didactic.
⏳ Structure your article like an hourglass: Begin with broad abstractions, narrow down to specifics, then expand again in your conclusions.
✍️ Write with care: Use LaTeX for precision and focus on structure, grammar, punctuation, formulas, figures, and formatting. If you don't care about your paper, why should reviewers care about it for you?
🚫 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 is valuable but just one piece of the puzzle, subject to improvement or even falsification. Remember, even Einstein approached his theories with caution.
I firmly believe that life is shaped by key moments—sometimes 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 has taken a new direction, and I am confident that the best is yet to come!