“How can I do that?”

# Who am I?

In March of 2020, a year out of university, I built this website while trying to figure out out who I wanted to be when I grew up. The way I had put it was:

Not so much in the career way as in the what-kind-of-values-are-important-to-me-and-how-do-I-want-my-work-to-reflect-them kind of way.

By 2022, with a bit more grasp on my values, the question I was asking was:

“What do I want to build in my life and what skills do I need to get there?”. By “my life” I mean my career, my community, and my art.

Shortly after, I moved to Amsterdam to do a Master’s degree in AI. I was frustrated by the carelessness of the industry, the bro-y hype, the lust for money, and an uneasy sense of inevitability - inevitability of the ubiquity of this technology, and the accelerating march towards climate disaster. But seemingly inevitable futures are built by people. And I am people. So I went back to study the math, in hopes of giving legitimacy and power to my voice.

Today? The societal impacts of widespread AI adoption, and the consequences we are actively facing due climate change are not waiting for me to be perfectly ready. I’m done asking questions; I’m looking for action.

# What drives me?

The question that drives me is, “How can I do that?”
The projects I pursue and the skills I seek out are very much driven by a curiosity “to see if I can”.

The thread that weaves my quilt of interests together is an interest in patterns. I look for the common shape of ideas to draw creative inferences across disciplines.

# Contact

You can find me on: GitHub and LinkedIn

# Education

Master of Science - Artificial Intelligence
University of Amsterdam | Sept 2023 - Jan 2026

  • Courses: Machine learning; Deep Learning; Causality; Complex systems (theory & simulations), ML Engineering; Climate Change; NLP, Computer Vision; Reinforcement Learning; Information Retrieval; Fairness, Accountability, Confidentiality, & Transparency (FACT); Explainability & Interpretability; Knowledge, Representation, & Reasoning

Bachelors of Arts and Science - Cognitive Science (Psychology & Computer Science streams)
McGill University | Sept 2013 - Apr 2019

  • Courses: Cell & Molecular Biology, Organic Chemistry, Neuroscience, Physics, Calculus, Linear Algebra, Discrete Structures, Statistics, Computer Science, Software Systems, Deductive Logic, Linguistics, Cognition, Cognitive Anthropology, Computational Psychology, Cognitive Science, A few philosophy classes (Merleau-Ponty, Aesthetics), Minor in Art History

# Experience

Machine Learning Researcher - Mila Quebec AI Institute (Montreal, QC) | Feb - Aug 2025

  • Worked with the Rolnick Lab team behind PICABU, a causal climate emulator. My work focused on improving evaluation methods, which formed the basis of my MSc thesis.

AI4Good Lab Project Manager - Mila Quebec AI Institute | Jan 2023 - Aug 2023

  • Ran end-to-end delivery of a 7‑week ML bootcamp started by Prof. Doina Precup for 100 women and gender-diverse participants. Managed team of academics and industry partners to deliver workshops and project development instruction, with emphasis on inclusive pedagogical practices and teaching critical thinking when using & building AI.

Operations & Research Associate - AI4Good Lab | May 2020 - Dec 2022

  • Managed operations, data-driven curriculum improvements, program execution, marketing, design, and communications with sponsors, grant committees, and students for a 2-person team, prior to the Lab’s 2023 integration into Mila’s operations.

Front-End Development Intern - IBM | May 2015 - May 2016

  • Implemented new features on proof of concept dashboarding framework (IBM Cloud Insights) using JavaScript and frontend libraries

Publications

Ghasemi, H., Isaicu, C., Wonnink, J., Berentzen, A. (2024) [Re] Reproducibility Study of “Explaining Temporal Graph Models Through an Explorer-Navigator Framework” - Transactions on Machine Learning Research (TMLR), NeurIPS 2024 Journal Track Poster, ML Reproducibility Challenge 2023

  • Reproduced and extended T-GNNExplainer, a framework for explaining temporal graph networks. Tested generalization by running experiments on a new dataset.
  • Evaluated robustness of the original claims across multiple metrics and baselines, finding weaker effect sizes and cases where simpler, less computationally-intensive explainers are competitive.

# Research

Causal Metrics for Evaluating Deep Learning Climate Emulators (MSc Thesis)
Mila & University of Amsterdam | Feb 2025 - Sept 2025

  • GitHub. Applied the causal metric Parent-AID (gadjid) to evaluate whether DL climate emulators learn correct underlying causal dynamics, aiming to improve upon standard F1-based structural graph comparisons. Validated the metric against RMSE (fidelity), intervention RMSE (robustness), and physical fidelity to spectral frequencies. Supervisors: Prof. Sara Magliacane, Dr. Julien Boussard.

Emotional experiences during breastfeeding: time of day, family support and mental health
McGill Neurophilosophy Lab | Sept 2018 - Sept 2020
Sofia Hempelmann Perez, Sophie Smith, Christina Isaicu, Natasha Binder, Ian Gold, Suparna Choudhury, Radhika Raturi, Charlotte Little, Marie-Helene Pennestri, Elizaveta Solomonova.PsyArXiv

  • Research coordinator: Conceptualization, Data curation, Investigation, Methodology

Expectations About Gender and Predictive Factors for Social Beliefs
McGill University | Sept 2019 - Sept 2020
Samuel Veissière, Christina Isaicu

  • Research coordinator: Conceptualization, Data curation, Investigation, Methodology

Temporal Processing of Facial Expressions of Mental States
McGill Neurophilosophy Lab | May - Aug 2018
Gunnar Schmidtmann, Andrew Logan, Claus-Christian Carbon, Joshua T. Loong, Ian Gold. I-Perception doi: 10.1177/20416695209611

Projects

Simulating Coral Reef Growth - Complex Systems Simulations course, UvA | Jan 2026

  • GitHub. Extended a baseline diffusion-limited aggregation (DLA) model with parameters for preferential vertical/horizontal growth, adapted from a biological coral growth model. Wrote the analysis confirming multifractal scaling behavior across the parameter space.
  • Led team of 4, establishing code structure and testing practices for reproducible research.

ML Production Pipeline for Real-Time Sensor Data - ML Engineering course, UvA | Dec 2025

  • GitHub. Built end-to-end system classifying gym exercises from sensor data in real time. Pipeline includes data streaming, cleaning, feature engineering with PySpark, unit tests, CNN model training, online inference, front-end displaying sensor data and activity classification.
  • Deployed the model with a FastAPI service in Docker, scheduled iterative retraining with Airflow, and monitored model and app performance via Prometheus and Grafana.

Indexing a Space Filling Curve - Personal project | 2019 (Deployed 2022)

  • Link to project page. Designed and implemented an algorithm to compute coordinate positions on an arbitrary-dimension space-filling Hilbert curve from orthant-label sequences, originating from a McGill Physics Hackathon. Deployed as an interactive web app.

Simulating Neanderthal Replacement - Computational Psychology course, McGill | 2018

# Fellowships & Awards

Learning Community Fellow - Montreal AI Ethics Institute| March - May 2021

  • Inaugural interdisciplinary cohort discussing AI ethics. Co-authored chapter “Design & Techno-Isolationism“ for the MAIEI Community Insights Report, examining how siloed AI development produces consequences that interdisciplinary collaboration could prevent.

BLUE Research Fellow - Building 21 | June - July 2019

  • Project exploring community building with particular focus on the aesthetic richness of complex dynamical systems. View report here.

Arts Research Internship Award (ARIA) - Neurophilosophy Lab, McGill University | July - Aug 2018

# Skills

Programming Languages: Python, Bash
ML & Data Science: PyTorch, NumPy, Matplotlib
Data Engineering: PySpark, Airflow
Backend & Deployment: FastAPI, Docker
Monitoring & Experiment Tracking: W&B, Prometheus, Grafana
Testing & Version Control: pytest, Git
Web & Frontend: HTML, CSS, EJS
Documentation: LaTeX
Causal Inference: Tigramite, gadjid, NetworkX
Design: Adobe Illustrator, InDesign, Photoshop
Coursework: Java, C, R, Lisp
Languages: English (native), French (intermediate), Romanian (native)

# Design

Graphic Designer - Freelance
Sept 2016 - Dec 2021

Head of Design - Fridge Door Gallery
Montreal, QC | Sept 2017 - May 2019

# Volunteer & Leadership

Swim instructor | Jan 2017 - March 2020
Teaching kids with disabilities as an instructor for Swimming with a Mission Canada & independent.

Guest lecturer | July 2019
Presented Building 21 research at Shad Canada, a STEAM and Entrepreneurship program for High School students.

K-12 tutor | Sept 2015- Sept 2016
Chemistry, Math, English.

IBM Future Blue Exec | Sept 2015 - May 2016
Co-lead of Web Team for IBM intern community.

Camp Activity Lead | Aug 2015
Lead workshops at IBM’s EXITE camp (Exploring Interests in Technology & Engineering) on the topic of big data & analytics, lego robotics.

Front-End Developer for charity | Aug 2015 - Oct 2015
Worked on team of 4 interns with CIRCA (Citizen IBM Responding through Action), to develop a check-in app for the CIBC Run for the Cure Marathon.

# Athletics

Competitive Rower | Sep 2013 - Aug 2014
Row to Podium, a Canadian Olympic Development Program

Competitive Swimmer | Sep 2006 - Jun 2013
Markham Aquatic Club, nationally ranked