Luca Scimeca is currently a Postdoctoral Research Fellow in Yoshua Bengio's group, at the Mila AI Institute. His current work focuses on learning representations, domain understanding, and generalization in deep learning, as well as applications in drug discovery and robotics.

Luca received his First Class Bachelor of Engineering in Artificial Intelligence and Software Engineering in 2017 from the University of Edinburgh, where he graduated summa cum laude, obtaining the Class award and Howe Prize for the best performance in Artificial Intelligence. During his studies, Luca has won over 13 awards, 9 of which paid scholarships for academic performance.

During his Ph.D. and Postdoctoral research at the University of Cambridge's Biologically Inspired Robotics Laboratory (BIRL), Luca worked on the application of machine learning models for the purpose of sensory perception and action in robotics systems. From 2019, his research has led to applying these technologies to robotics clinical settings, where, with the help of clinicians, they investigated the possibility of robotic systems to perform physical examinations. This was reflected in two major European EPSRC grants, MOTION and ROBOTPATIENT, for a combined worth of over $1,500,000. As both a Ph.D. and Postdoctoral researcher, under the supervision of Dr. Fumiya Iida, Luca has led several of the major investigations related to both grants, which, in the course of three years, have led to the publication of over 15 peer-reviewed articles on high impact journals or international conference proceedings.

In 2021 Luca joined Never Corp. as a visiting AI Research Scientist to research in the area of learning representations, domain understanding, robustness, and generalization for Deep Neural Networks (NeurIPS 2021, ICLR 2022).

Luca is a former Postdoctoral Fellow at Harvard University and Dana Farber, where he worked closely with Dr. Ming-Ru Wu to boost computational biomedical research, and to use machine learning to answer basic questions in tumor biology and immunotherapy, with the ultimate goal of improving cancer treatment quality and efficiency.