About Me

I am a senior researcher at Microsoft Research, in the AI4Science team. My website is a bit out of date, I will fix it soon :)

Before joining Microsoft, I worked as a postdoc at UCL where I also did my PhD in Machine Learning. In summer 2021 I took part in the research sprint with Frontier Development Lab , an applied AI research accelerator that works in partnership with NASA.

Education

• Research Associate at UCL and Imperial College
• PhD student at UCL, Computer Science department
  • Apr. 2019-July 2019 I worked at CREST , ENSAE ParisTech , under the supervision of Marco Cuturi and Gabriel Peyre’
• MSc. Mathematics, University of Pavia, 2014-2016
  • MSc dissertation: Contraction and regularizing effects for Markov semigroups in Hellinger-Kantorovich spaces
  • Advisor: Giuseppe Savare’
• Exchange Program (Mar. 2015- Aug. 2015) at Humboldt University, Berlin
• BSc. Mathematics, University of Pavia , 2011-2014

You can find my full CV here .

Publications

• GL, M. Pontil, C. Ciliberto, Generalization Properties of Optimal Transport GANs with Latent Distribution Learning , submitted

• S. Cohen, GL , A. Terenin, B. Amos, M. Deisenroth, Aligning Time Series on Incomparable Spaces , AISTATS 2021

• A. Salim, A. Korba, GL, Wasserstein Proximal Gradient , NeurIPS 2020

• L. Oneto, M. Donini, GL, C. Ciliberto, A. Maurer and M. Pontil, Exploiting MMD and Sinkhorn Divergences for Learning Fair and Transferable Representations , NeurIPS 2020

• A. Korba, A. Salim, M. Arbel, GL, A. Gretton A Non-Asymptotic Analysis for Stein Variational Gradient Descent , NeurIPS 2020

• GL, S. Salzo, M. Pontil, C.Ciliberto, Sinkhorn Barycenter with Free Support via Frank-Wolfe Algorithm , NeurIPS 2019 (spotlight)

• GL, G. Savare’, Contraction and regularizing properties of heat flows in metric measure spaces , DCDS-Series S, doi: 10.3934/dcdss.2020327

• GL, D. Stamos, M. Pontil, C. Ciliberto, Leveraging Low-Rank Relations Between Surrogate Tasks in Structured Prediction, ICML 2019.

• GL, A. Rudi, M. Pontil, C. Ciliberto, Differential Properties of Sinkhorn Approximations for Learning with Wasserstein Loss , NeurIPS 2018.

News (conferences/workshops I have attended)

• MalGA Seminars , 16 March 2021
• DeepMind CSML Seminar Series , 28 Nov 2019, London, (slides)
• MAGA days 20-21 Nov 2019, Paris (slides)
• POTA workshop Jun. 2019, Cortona (Italy)
• ICML Jun. 2019, Long Beach (poster)
• NeurIPS Dec. 2018, Montreal (poster)
• Optimal Transportation and Applications 2018, Pisa, Italy
• MLSS 2018 , Buenos Aires