Research software engineering

I am currently a research software engineer at King’s College London within the e-Research team. In this role, I write software that is more reproducible, shareable, and scalable, and allows to more easily build upon existing research. Currently, I am involved in co-building a genAI-based, to-be-commercialised app to enable the collection of rich but narrowly scoped qualitative data at scale. This work operates across human-computer interaction research and product development where we build production-ready software while requirements are still being discovered through research.

Beyond this project, I’ve developed software in ML-based research initiatives, working in a dual role as both engineer and researcher by establishing scientifically rigorous analysis pipelines from inception. My role also involves bridging technical and non-technical worlds: communicating technical content to researchers and stakeholders, and contributing to broader conversations such as AI’s impact on research software engineering.

Research in computational neuroscience, complex systems and technical AI safety

I have completed a PhD in computational neuroscience and complex systems at the Sussex Centre for Consciousness Science. My doctoral research (comprising three to-be-published studies) addresses both conceptual/philosophical and empirical questions about multi-scale relationships in complex systems, focusing on formal, information-theoretic approaches to emergence and complexity. Conceptually, I co-developed a framework that rethinks emergence as a non-binary, multi-dimensional construct. Empirically, I systematically validated a broad range of emergence and complexity measures across multiple simulated time-series models and micro/macro-scales to inform empirical research on time-evolving systems. I also examined multi-scale measures in learning systems employing Approximate Bayesian Inference, a method from machine learning.

Beyond this, I’ve leveraged complexity science/emergence research for AI safety within a PIBBSS fellowship. I synthesized philosophical, mathematical, and empirical research on emergence to advance AI capability assessment, exploring how measures of emergence could be used for AI evaluations. I progressed on technical feasibility and outlined next steps toward a deployable emergence assessment pipeline. Here’s a talk on my AI safety research project.

AI/ML and datascience

Beyond the technical AI safety and LLM-based software development work mentioned above, I applied unsupervised ML techniques to derive candidate emergent macro-scales in simulated time-series models during my doctoral research. Prior to my PhD, I investigated robotic hand control via motor imagery and experiences of embodiment in an EEG-based brain-computer interface study. I then investigated the dynamics of integrated information (a complexity measure) in black-box variational inference, a foundational technique used in ML for approximating intractable posterior distributions in Bayesian inference. This work formed the basis for my doctoral research on multi-scale measures in learning systems employing Approximate Bayesian Inference. Across these projects, I have worked extensively with information theory, time-series modelling, and Bayesian methods. As a research data scientist in medical education research, I conducted data science work that informed the development of assessment procedures in medical education, which directly informed regional educational policy and resulted in a co-authored publication.

Open science and research software advocacy

As a 2023/2024 Software Sustainability Institute (SSI) Fellow, I delivered research software enginnering workshops in Python for different research communities. I have also generalized and shared research code from my own work, e. g., I developed ComplexPy – a Python library (still WIP) designed to make different complexity and emergence measures easily applicable and comparable across datasets in an intuitive, comprehensive way. I’ve been an active contributor to the open science ecosystem through regular participation in Brainhacks and other hackathons, some of which have resulted in open-source software contributions. All code from my past and ongoing research is published and documented on GitHub.

Education and mentoring

I’ve been engaged in knowledge sharing across educational contexts and audiences. In my current role as a research software engineer, I have provided support for HPC training, Git/GitHub and Python for students and staff. During my academic research, I’ve taught courses spanning ML fundamentals, Algorithmic Data Science, Practical Philosophy, and EEG methods, and supervised machine learning theses. I’ve delivered research software engineering tutorials and served as a mentor multiple times in the Open Seeds mentoring and training program, helping participants (from marginalised groups) to open-source their software projects. I’ve also taught German to refugees.

Interdisciplinarity and seeing the big picture

Most of my research has been hugely interdisciplinary, intersecting mathematics, machine learning, neuroscience, as well as philosophy. My doctoral work in particular required extensive bridge-building between abstract mathematical measures and their conceptual meanings.

I have been the main organiser of a symposium titled Rethinking Computational Approaches to the Mind - Fundamental Challenges & Future Perspectives, which brought together researchers to examine questions about computational approaches in the mind sciences. Have a look at the recorded talks and panel discussion which included, amongst others, Melanie Mitchell, Konrad Kording, and Gaël Varoquaux.

I thought much about metascientific questions, one outcome of which is an extensive article-like post on collaboration in science, arguing that shifting from individualistic to more collaborative work in academia is needed to improve scientific progress and increase well-being. This is particularly crucial in the mind sciences where research methodology is especially challenging.

Psychology and policy advocacy

I have a background in psychology and worked as a psychologist for unaccompanied refugee minors at Bahia. I also engaged in pedagogical psychology work at Children for Tomorrow, supporting vulnerable refugee children and adolescents. At Equality California, I worked as a policy advocate on public education projects.

Volunteering

I regularly engage in volunteer work. Most recently, I was part of a peace-building project providing non-violent protective accompaniment during the olive harvest for Palestinian communities. I worked alongside Israeli and international volunteers in the West Bank to ensure safe agricultural access for Palestinian farmers facing movement restrictions and settler violence, and engaged in dialogue and witness-bearing with local peace organizations.

Art, the outdoors, and other endeavours

I engage in photography and share my work on Instagram. I also post about (ultra mountain and sky)running, the outdoors more generally & music/culture in the UK/around the world in another account. In this blog/personal website, I share writings on various topics.