cv
This is my long resume in digital form, click on the icon for the .pdf 1-page version.
Table of contents
- General Info
- Education
- Experience
- Portfolio and Talks
- Other self study / extracurriculars
- Academic Interests in Keywords
- Skills
- Awards
- Interests
General Info
Full Name | Simone Maria Giancola |
Date of Birth | 6th September 1999 |
simonegiancola09 dot gmail dot com | |
summary | Research intern. Passionate about using theoretical methodologies to solve real world problems. |
Languages | English (proficient), Italian (mothertongue), Spanish (basic) |
Education
-
Aug 2021- Apr 2024 Master of Science in Data Science, Data Science major
Bocconi University, Milan, Italy - Grade
- GPA 29/30, Final grade 110 cum Laude/ 110
- Thesis "A roadmap to Message Passing methods for inference on Mixed Generalized Linear Models, with emphasis on Mixed Noiseless Phase Retrieval"
- Advisor Prof. Carlo Lucibello
- relevant coursework
- Ph.D. Real Analysis (Optimal Transport), Graph Theory, Statistical Physics
- Advanced Machine Learning, Optimization, Stochastic Processes
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Jan 2021 - May 2021 Undergraduate Exchange Program
Arizona State University, Tempe, AZ, USA - GPA 4.17/4.00
- Graduate relevant coursework Quantum Computation, Modeling with Game Theory
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Aug 2018- Jul 2021 Bachelor of Science in Economics and Computer Science
Bocconi University, Milan, Italy - Grade 110 Cum Laude / 110
- Thesis “Value of Information in a Support Vector Machine, an exploration”
- GPA 29.18 / 30 , STEM GPA 30.14 / 30
- Relevant coursework Advanced Statistical Methods, Applied Mathematics, Machine Learning
Experience
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Feb 2024 - May 2024 Research Intern
King Abdullah University of Science and Technology (KAUST), KSA - Advisor: Prof. Peter Richtárik
- Convex Optimization, Conditioned Gradient Descent methods
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Oct 2023 - Dec 2023 Research Intern
Ecole Normale Superieure (ENS), Paris, FRA - Advisor: Bruno Loureiro
- Theory of Neural Networks, Stochastic Gradient Descent
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Jun 2023 - Aug 2023 Research Intern
Institute of Science and Technology Austria (ISTA) Wien, AUT - Advisor: Prof. Marco Mondelli
- Statistical to Computational Gaps, Information Theory, Algorithms, Message Passing
- ISTernship Summer Programme, ref. num. MPC-2023-01128, financed by ISTA, awarded by the OeAD
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Mar 2022 - Jun 2023 Visiting Student
Bocconi Institute for Data Science, Milan, ITA - Advisors Prof. Carlo Lucibello and Prof. Luca Saglietti, Computing Sciences Department
- Reading, self-study, writing
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Jan 2022 - Mar 2022 Data Science Intern
Santagostino Clinic Milan, ITA -
Jan 2021 - May 2021 Research Assistant
Bocconi University, Milan, ITA - Advisor Prof. Emanuele Borgonovo
- Value of Information, Support Vector Machines
Portfolio and Talks
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Mar 2023 Compositional RBMs, a Birds Eye view
- Restricted Boltzmann Machines, Statistical Physics, Unsupervised Learning
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Mar 2023 A view on Percolation and Spin Systems
- Percolation, Potts Model, Spin Systems, Random Cluster Model
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Jan 2023 Notes on the Neural Tangent Kernel
- Deep Learning Theory, Neural Networks, Kernel Methods
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Jan 2023 Notions in Optimal Transport for Sigmoid Neural Networks
- Deep Learning Theory, Optimal Transport, Neural Networks
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Jun 2022 Bipartite Matching & extensions
- Linear Algebra, Graph Theory, Duality, Hungarian Algorithm, admissible transformation theory, Pfaffian orientations
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Jan 2022 Advanced Session, Harvard mini-course on Computation
- Simulated Annealing, Statistical Mechanics, TSP
Other self study / extracurriculars
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Summer 2023 Lectures on linearized Neural Networks
- Kernels, Ridge Regression, High Dimensional Probability
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Sep 2022 - Jan 2023 Probability Theory
- Measure Theory, Stochastic Processes
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Jun 2022 - Ongoing Statistical Physics
- Machine Learning, Optimization, Physics, Neural Networks
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Jun 2022 - Dec 2022 Geometric Deep Learning
- Group Theory, Statistical Learning, Neural Networks, Topology
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Dec 2021 Bayesian MCMC probit analysis | co-authored
- Gibbs Instrumental Algorithm, Metropolis Random Walk Algorithm
Academic Interests in Keywords
- Mathematics, Statistics, Computer Science
- Information Theory, Statistical Physics, Machine Learning
- theoretical results, theory of learning, neural networks
Skills
- Advanced Python, Latex, Sklearn, Numpy, Matplotlib, Scipy;
- Certifications Deep Learning and AI for Medicine by DeepLearning.AI;
- Intermediate Julia, Git, Unix, R, SQL, Matlab, C++, Keras, Tensorflow
Awards
- First Italian School in Geometric Deep Learning, Funded MS student.
- OeAD Scholarship, ref. num. MPC-2023-01128, financed by ISTA, awarded by the OeAD
Interests
- rugby
- podcasts
- running
- motorbike trips