[ About ]
I'm the Founder and CEO of Enhansys Labs, Inc., where we’re building the intelligence layer that will power the first AI-native energy company.
I am currently a Runway Postdoc at Cornell Tech — the place where Enhansys is taking shape, working at the intersection of research and deep-tech venture building.
Previously, I earned my PhD in Energy Engineering from Politecnico di Milano, where I developed hybrid optimization algorithms that combined Combinatorial Optimization and Machine Learning to make large-scale energy optimization problems computationally tractable.
I was born and raised in Taranto, in southern Italy, and later moved to Milan to complete my BS and MS in Energy Engineering at Politecnico di Milano. After five years immersed in energy modeling, my interests shifted suddenly toward Operations Research and Computer Science-related topics. During my PhD I had the chance to dive deep into these fields, which gave me a completely new perspective on energy systems and how to approach their complexity.
Outside of work, I’m the proud cat-dad of Kiki and Mina. You'll hear me talk endlessly about Enhansys, but at the end of the day, they're always where my heart goes.
[ Enhansys ]
Enhansys is the intelligence layer for the energy industry.
We believe the next inflection point in the energy systems industry (design, control, manufacturing) won't emerge from incremental tooling, but from unprecedented modeling capabilities that seamlessly adapt to meet the rapidly evolving energy landscape.
In a rapidly shifting energy landscape, the gap between what engineers must evaluate and what existing workflows can handle keeps widening with the growing complexity and pace of change. Most of the industry still relies on complex but non-intelligent calculators, forcing engineers to stitch assumptions together, iterate manually, and carry the end-to-end cognitive load. That’s why we’re building the first augmented intelligence model that simultaneously accounts for every conceivable specification to deliver robust, error-free end-to-end solutions, from component selection and sizing to manufacturing constraints and real-time control.
We want to empower practitioners with next-generation intelligence that co-engineers with them, achieving unprecedented fidelity and velocity. We're compressing years of iteration into days. Soon, doing it the old way will feel as antiquated as spending three days debugging before generative AI.
[ Research ]
For what scientific research has always meant to me, I hope to be remembered not as a good researcher, but as a great artist. And for the simple, quiet joy of pursuing questions, free of the obligation to produce answers.
Deep down, I am a researcher. But not only in the narrow academic sense, I approach everything with the mindset of a researcher. That constant drive to question, test, and explore is what ultimately led me to found Enhansys.
My expertise lies at the intersection of stochastic optimization, machine learning, and energy modeling, with a focus on decision-making under uncertainty and large-scale optimization problems. More precisely, I'm a decision scientist. I am obsessed with how we make choices, how we build models to support them, and how we adjust those choices over time as uncertainty reveals itself.
During my PhD, my research evolved from decision-making in the niche of the energy sector to more fundamental work in Operations Research and Combinatorial Optimization. My focus increasingly turned to the challenge of making decisions under severe time constraints while solving very large-scale models — pushing the limits of what is computationally feasible. In this space, I explored how hybrid ML-CO algorithms can make large-scale optimization tractable and reshape how we model and navigate complex, uncertain environments.
Along the way, I developed a passion for the broad field of artificial intelligence — from Gen AI to RL, passing through Control Systems and Game Theory. During my PhD and the early part of my Postdoc, I spent as much time in classrooms as in the lab, taking more CS-related courses and exams than in the final years of my formal academic career. This exploration allowed me to reframe all my research on decision-making within a much broader intellectual context. I’m deeply fascinated by the intrinsic nature of intelligence itself. I believe that building systems that can reason, decide, and create far beyond today’s limits — with ethics at the core — is one of the most exciting challenges of our time, and aligning part of my work with this quest is what makes it truly impactful.
[ Beyond Work ]
Despite my technical background, off-duty I remain a generalist at heart.
You may find me reading politics and economics books, or immersed in technical solo projects with the sole aim to explore new tools, sharpen my development skills, or simply dive into technical domains that spark my curiosity beyond work's immediate scope. I've also tried learning Chinese in the past — something I'll definitely pick up again once they invent 48-hour days to properly balance work, leisure, family, and friends.
All jokes aside, there's also something I've been quietly developing since my univesity years. It's something personal that goes way beyond just a hobby. Maybe someday it'll make its way out into the world, but for now, it's just mine and of the closest people in my life.
I love immersive traveling, I'm the anti-sport type when it comes to using a ball, and I'm definitely more of a beach person (especially if it's in my hometown).
[ Contacts ]
I do not post very often, but these are the few digital spaces I actively check: