Mackenzie Jorgensen

Seattle Villanova Kassel Oxford Münster Villanova London
PhD Student in Computer Science · King's College London

I am a Computer Science PhD Student funded by the UKRI Centre for Doctoral Training in Safe and Trusted Artificial Intelligence at King’s College London. My research focus is on mitigating the harms that can result from algorithmic decision making.

I graduated Phi Beta Kappa and Magna Cum Laude from Villanova University with a Bachelor of Science in May 2020. I studied Computer Science and Philosophy as a Presidential Scholar. As an undergraduate, I completed research projects in the U.S. and Germany in the fields of big data analytics, multi-agent communication and coordination, and hate speech moderation through machine learning.

| November 2021: I was accepted for a PhD internship at the UK Govt's Center for Data Ethics & Innovation in the spring!
| November 2021: My Phi Beta Kappa London blog post was published.
| August & September 2021: My interview with Eli Lee about her novel, "A Strange and Brilliant Light," was published in the British Science Fiction Association's Vector Journal: part 1 and part 2.
| June 2021: I was selected to provide feedback during the Alan Turing Institute's AI Ethics & Governance Scoping Workshop.
| June 2021: HURIDOCS won the Peace & Justice Strong Institutions Award at the CogX celebration, where I represented them in London!
| March 2021: Presented Liu et al.'s Delayed Impact of Fair Machine Learning paper at the STAI CDT's Journal Club [Slides] [Video].
| Feb 2021: My blog post went live on KCL's Utopia Now project website.
| Jan 2021: Began my position as a GTA for the Informatics Department at King's. :D
| Oct 2020: PhD begins!

Email: mackenzie(dot)jorgensen(at)kcl(dot)ac(dot)uk


King's College London

PhD Student in Computer Science

I am working to mitigate the harms that AI decision-making systems have on people under the supervision of Dr. Elizabeth Black, Dr. Jose M. Such, and Dr. Natalia Criado Pacheco. I am funded by the UKRI Centre for Doctoral Training (CDT) in Safe and Trusted AI (STAI) and a member of the Distributed AI Research Group. I am a Student Representative on the STAI CDT Staff-Student Liaison Committee representing my 2020 STAI cohort. I am also a visiting postgraduate student at Imperial College London through the STAI CDT.

October 2020 - September 2024

Villanova University

Bachelor of Science, Magna Cum Laude, Phi Beta Kappa

I completed a Computer Science Major with a Philosophy Minor. I am incredibly grateful to my amazing mentors from Villanova, including Dr. Robert Beck (now retired), the late Dr. Anany Levitin, Associate Computer Science Professor Edward Kim (now at Drexel University), and Computer Science Lecturer Kristin Obermyer. Some of my most informative and fascinating liberal arts courses were taught by Peace & Justice (P&J) Lecturer Carol Anthony, Associate History Professor Hibba Abugideiri, and P&J Professor Timothy Horner. These mentors and professors instilled in me a passion to develop technology that makes our world more socially just.

August 2016 - May 2020

St. Annes College, University of Oxford

Visiting Student

I studied Computer Science & Philosophy during my junior year abroad. I am thankful for Dr. Wendelin Böhmer who was my Personal Tutor at the time; he is now working at TU Delft.

October 2018 - June 2019



Graduate Teaching Assitant

As a Graduate Teaching Assistant (GTA) for Artificial Intelligence, I ran two weekly online live tutorials where I made sure the students were confident with the material and the tutorial sheet answers. I also ran four virtual live labs each week where students worked on developing a successful pacman agent during the Autumn 2021 term.

September 2021 - December 2021

AI Robustness Researcher/Developer

Ernst & Young UK and STAI CDT Group Project Collaboration

Alongside three other PhD Student colleagues, I completed a literature review of AI Robustness methods, zoning in on NLP, weight-poisoning attacks, and poisoning detection methods. We developed a project combining state of the art AI Robustness and NLP research. I was the lead point person for communicating with our stakeholder, EY, every week over the 10 week project. To learn more about what we developed, check out our GitHub repository here: RobuSTAI.

January 2021 - April 2021

Graduate Teaching Assitant

As a Graduate Teaching Assitant for Machine Learning, I ran two small group live sessions weekly for undergraduates covering the tutorial sheet for that week and any questions the students had. I also was a GTA for the Big Data Technologies course. I ran three online live lab sessions weekly for masters students, helped answer any questions they had, and marked coursework.

January 2021 - April 2021

Machine Learning Engineer Intern

While at HURIDOCS, I used state of the art ML explainability techniques to learn about a topic classification model. I improved the topic classification model performance for the Office of the UN High Commissioner for Human Rights. In addition, I documented software and processes for future ML Engineers and I was mentored by the Software Engineer, Gabriel Piles.

May 2020 - August 2020

Undergraduate Researcher on ML and Natural Language Processing (NLP)

While in Münster, I developed a successful ML/NLP framework to detect abusive language in English and German on Twitter at the the European Research Center for Information Systems with another undergraduate researcher. We implemented the steps of the ML pipeline alongside H2O Auto-Machine Learning in Python. I was mentored by PhD student Marco Niemann.

June 2019 - August 2019

Undergraduate Researcher on Artificial Intelligence (AI)

I worked in the Distributed Systems Laboratory and collaborated with PhD Candidate Marie Ossenkopf who does great research on multi-agents. We built a deep learning framework that learned communication and coordination for a lever game. More specifically, we implemented a hierarchical deep reinforcement learning framework for a multi-agent system in Lua.

June 2018 - August 2018

Undergraduate Researcher on ML and Big Data

During my first summer of research in Boston, I analyzed Big Data by contributing to the Northeastern Interactive Clustering Engine (NICE) framework. I worked in the Northeastern University Computer Architecture Research Lab, where I programmed a Python interface and Machine Learning algorithms in C++ for NICE data analysis. I was mentored by Computer Science Professor David Kaeli, Computer Engineer Dr. Shi Dong, & PhD Candidate Zulqarnain Khan.

June 2017 - August 2017


Awards & Recognition

Leadership & Outreach

King's College London

Villanova University


Apart from my research, I enjoy most of my time outdoors whether that's rowing, running, and biking in London or hiking and kayaking in Seattle. I enjoy traveling within the US and abroad. I absolutely love food so you will typically find me at coffeeshops, bookshops, and independent restaurants. When I'm not out and about, I'm making pescatarian food, reading, listening to podcasts and music, watching tv and films, or meditating. As Villanova basketball's head coach, Jay Wright, says, once a Wildcat, always a wildcat--go cats! \\//