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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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Statistics PhD student
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Posts
Blog Post number 4
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
publications
Regularised B-splines projected Gaussian Process priors to estimate time-trends of age-specific COVID-19 deaths related to vaccine roll-out
Appeared in Bayesian Analysis, 2021
In this paper we fit beta splines to COVID-19 mortality data for each US state and use the fitted curves to estimate future deaths.
Recommended citation: Monod, M., Blenkinsop, A., Brizzi, A., Chen, Y., Perello, C. C. C., Jogarah, V., Wang, Y., Flaxman, S., Bhatt, S., & Ratmann, O. (2021). Regularised B-splines projected Gaussian Process priors to estimate time-trends of age-specific COVID-19 deaths related to vaccine roll-out. https://arxiv.org/abs/2106.12360
Adaptively Optimised Adaptive Importance Samplers
Preprint (submitted for publication), 2023
This paper, which stemmed out of my BSc project, introduces a new adaptive importance sampling algorithm that used adaptive optimisation to adapt the proposal distribution.
Recommended citation: C. C. Perello, C. A., Akyildiz, Ö. D. (2023). Adaptively Optimised Adaptive Importance Samplers. https://arxiv.org/abs/2307.09341
Graph-based mutually exciting point processes for modelling event times in docked bike-sharing systems
Appeared in Stat, 2023
This paper is an extension of my 2nd year group project, which consisted on fitting Hawkes processes to the London Santander Cycle bike-sharing system. In this paper we employ a spatial component in the model to take in account distances between docking stations when predicting bike usage.
Recommended citation: F. Sanna Passino, Y. Che, C. C. Perello, C. A. (2023). Graph-based mutually exciting point processes for modelling event times in docked bike-sharing systems. https://arxiv.org/abs/2311.00595
Non-existence of the 2D quadratic Poisson optimal matching
MSc Thesis, 2024
This is my MSc thesis, where I analysed a recent proof of the fact that a stationary, non-ergodic, quadratic and locally-optimal 2D Poisson matching does not exist.
Recommended citation: C. C. Perello, C. A. (2024), Non-existence of the 2D quadratic Poisson optimal matching.
talks
Guest lectures for APMA1650: Statistical Inference I
Published:
I gave four guest lectures for APMA1650: Statistical Inference I at Brown University, on Feb 10th, 12th ,14th and on Apr 14th. In the February lectures, I covered discrete random variables, probability mass functions as well as expectation and variance for this class of random variables. In my upcoming lecture, I will cover more advanced topics such as hypothesis testing and confidence intervals.
On the non-existence of 2D, locally optimal ergodic and stationary matchings
Published:
I gave a short talk at Brown’s Graduate Lecture Series in Analysis and PDEs (GLESPA) on the work I conducted when writing my MSc thesis, which is available here.
teaching
Peer Tutoring
Peer Tutoring, Imperial College London, Department of Mathematics, 2022
I was a peer tutor for the first year mathematics course at Imperial College London. I was responsible for leading weekly tutorials for a group of 5-6 students, helping them develop their problem solving skills and understanding of the course material. I also prepared challenging problems for the students to work on in their own time.
UTA for MATH50003 Numerical Analysis
Undergraduate Teaching Assistant, Imperial College London, Department of Mathematics, 2023
I was an Undergraduate Teaching Assistant (UTA) for MATH50003 Numerical Analysis at Imperial College London, a 2nd year undergraduate course led by Prof Sheehan Olver. I attended the weekly problems classes and helped students with problems, especially with the Julia programming exercises. I also marked the mock exam for said course. More information can be found on the course’s GitHub page.
Guest lectures
Lecturing, Brown University, 2025
I gave four guest lectures for APMA1650: Statistical Inference I at Brown University.