Mackenzie Jorgensen

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

I am a Computer Science PhD Candidate 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 systems. I am also interested in the intersection of AI, ethics, and technology policy.

Previously, 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.

News
| May 2023: The MD4SG blog post I co-wrote about Ed Lada's Colloquium is published on Medium.
| May 2023: My research paper was accepted to the AAAI/ACM Conference on AI, Ethics, and Society, so I'll be heading to Montreal in August!
| March 2023: I was accepted to the ACM FAccT 2023 Doctoral Colloquium, so I'll be heading to Chicago in June!
| February 2023: I interviewed the Head of Amnesty Tech's Algorithmic Accountability Lab, Damini Satija, for the Conversations with Practitioners working group.
| January 2023: My KCL Careers in Your Ears podcast episode that I hosted alongside Luis Pizarro was released!
| August 2022: I welcomed my DAAD RISE Worldwide undergraduate researcher to London for her 8 week internship with me.
| July 2022: I presented at the AIofAI'22 Workshop at IJCAI in Vienna, Austria!
| June 2022: A blog post I co-authored for the CDEI was published on responsible demographic data collection for bias detection.

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

Education

King's College London

PhD Candidate 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

Publications

Experience

Graduate Teaching Assistant

Informatics Department, King's College London, London, UK

As a Graduate Teaching Assistant (GTA) for Machine Learning, I ran two weekly labs tutorials. In addition, I was the GTA for the AI Impact Accelerator module. I also led two tutorials and two labs for Data Structures every three weeks.

January 2023 - March 2023

PhD Mentor for DAAD Rise Worldwide Recipient

Informatics Department, King's College London, London, UK

I hosted a German undergraduate student researcher over 8 weeks while she worked alongside me on my PhD research project. She was funded by the DAAD RISE Worldwide program. We collaborated with one another and wrote papers on the work we completed.

August 2022 - September 2022

PhD Intern

Centre for Data Ethics & Innovation, UK Civil Service, London, UK

I completed a 5 month (~two days a week) PhD Placement at the CDEI which is a part of the UK's Civil Service, enabling the trustworthy use of data and AI. I worked on two different projects: the Responsible Demographic Data and the Bias Review projects. I collaborated with colleagues on both projects, reached out to stakeholders and contributed to those discussions, and lead work in the Bias Review project. For London Tech Week 2022, I co-authored a blog post about demographic data collection and bias detection. I learned a great deal about the intersection of the technology, policy, and data ethics fields and am eager to stay involved with the tech policy space.

February 2022 - July 2022

Graduate Teaching Assistant

Informatics Department, King's College London, London, UK

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, London, UK

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 Assistant

Informatics Department, King's College London, London, UK

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

Human Rights Information & Documentation Systems (HURIDOCS) NGO, Geneva, Switzerland

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 and I worked remotely from Seattle, USA.

May 2020 - August 2020

Undergraduate Researcher on ML and Natural Language Processing (NLP)

Research Internships in Science & Engineering (RISE) Germany at Westfälische Wilhelms-Universität Münster, Münster, Germany

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)

RISE Germany at Universität Kassel, Kassel, Germany

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

National Science Foundation (NSF) Research Experience for Undergraduates (REU) at Northeastern University, Boston, USA

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

Presentations

Awards & Recognition

Leadership & Outreach

King's College London

Villanova University

Seattle Community

Interests

I enjoy most of my time outdoors whether that's running or walking neighborhood dogs along the Thames and in green spaces. You will typically find me out and about at coffeeshops, bookshops, queer spaces, and food markets. When I'm not out and about, I'm probably reading, listening to podcasts and music, watching shows, or meditating.