Photo Credit: Thomas Angus, Imperial College London

Hi there!

I am a PhD candidate at Imperial College London's Safe AI Lab (SAIL), supervised by Prof. Alessio Lomuscio and funded by the UKRI CDT in Safe and Trusted AI. My research focuses on out-of-distribution (OOD) detection and runtime monitoring of deep neural networks, developing methods to identify when a model is operating outside its training distribution, with the goal of making neural networks safer and more trustworthy in deployment.

Before Imperial, I completed my BA in computer science at Harvard, spent four years in quantitative roles in commodities and FX markets, and completed an MSc in advanced computer science at Oxford, where I explored fairness and bias in financial machine learning. During my PhD I have interned at Meta, building LLM tools for data infrastructure, and at Citadel, working on quantitative model risk research.

Publications

A Robust Out-of-Distribution Detection Framework via Synergistic Smoothing

CVPR Findings 2026

M Stoica, A Hekal, A Lomuscio

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Findings

Out-of-Distribution Detection using Counterfactual Distance

Preprint 2025

M Stoica, F Leofante, A Lomuscio

arXiv preprint arXiv:2508.10148

Wanted: Personalised Bias Warnings for Gender Bias in Language Models

GeBNLP Workshop 2025

C Di Bonaventura, M Nwachukwu, M Stoica

Proceedings of the 6th Workshop on Gender Bias in Natural Language Processing (GeBNLP)

View full profile on Google Scholar →

CV

Education

PhD Candidate in Computing

Oct 2022 - Jun 2027 (expected)

Imperial College London

  • Research focus: OOD detection and monitoring of neural networks
  • Supervisor: Prof. Alessio Lomuscio, Safe Artificial Intelligence Lab
  • UKRI CDT in Safe and Trusted AI

MSc in Advanced Computer Science

Oct 2021 - Sep 2022

University of Oxford

  • Masters Dissertation: Exploration of Fairness Metrics in Financial Machine Learning
  • Supervisor: Prof. Marta Kwiatkowska
  • Google DeepMind Scholar

BA in Computer Science

Sep 2013 - May 2017

Harvard College, MIT

Professional Experience

Quantitative Research Intern, Model Risk Research

May 2026 - Nov 2026

Citadel

  • Designing and implementing independent benchmark models to enhance firm-wide risk management and ensure robust model governance.

PhD Intern, Systems and Infrastructure Software Engineering

Jun 2025 - Sep 2025

Meta

  • Developed LLM Model Context Protocol tools to integrate internal data infrastructure knowledge into large language models.
  • Built systems enabling LLMs to assist engineers with debugging, querying, and reducing workload on data infrastructure teams.

Foreign Exchange Options Quantitative Developer, Associate

Sep 2019 - Jul 2021

NatWest Markets

  • Designed and developed pricing libraries and risk systems for FX Options, working with front and middle office to translate business strategy into technical solutions.

Commodities Sales Strats, Analyst

Jul 2017 - Aug 2019

Goldman Sachs

  • Worked with sales and trading to structure and price transactions for clients, and built tools to automate analytical workflows.

Summer Analyst, Strats

Jun 2016 - Aug 2016

Goldman Sachs

Teaching Assistant: Discrete Mathematics

Spring 2017

Harvard College, Department of Computer Science

Leadership

Diversity and Inclusion Committee Member

Jan 2023 - Present

UKRI CDT in Safe and Trusted AI

  • Member of the STAI CDT Diversity and Inclusion committee tasked with organizing events to promote diversity and inclusion in the CDT.

Outreach Officer

Sep 2023 - Present

Women and Non-binary Individuals in Computing, Imperial College London

  • Member of the WNBiC committee tasked with organizing outreach events such as school visits and hackathons for girls.

Social Events Co-Chair

Oct 2021 - Sep 2022

University of Oxford Women in Computer Science

  • Organized events to promote networking with students and faculty.