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Blog

Upgrading OpenAI's Moderation API with a new multimodal moderation model

Sep. 2024

Core research contributor for OpenAI's new SOTA multimodal moderation model. Powers moderation for OpenAI's products (ChatGPT+API) and is available for free to developers. Blog post link.

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NLP

👨‍⚕️

Session

Safety2Vec: An Introduction to Text Embeddings and their Applications in T&S

Jul. 2023

TrustCon2023 presentation on how embeddings models can enable Trust & Safety teams to better understand user behaviour on their platforms.

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Politics

📞

Paper

Automated vs. manual case investigation and contact tracing for pandemic surveillance

Nov. 2022

Lead author on the first randomized control trial of COVID-19 contact tracing – accepted to The Lancet's subsidiary, eClinicalMedicine.

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Politics

🗻

OpenAI

My Next Phase

Aug. 2022

Life update: I’m joining OpenAI's Trust & Safety team!

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🤖

Paper

Measuring Alignment of Grassroots Political Communities with Political Campaigns

May 2022

Lead author on this study, accepted to ICWSM 2022, that uses neural embedding techniques to analyze how grassroots political communities on Reddit align with their respective political campaigns.

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Politics

🔋

Blog

Simulating Statistical Power in R

Mar. 2022

A tutorial (with code!) explaining the important concept underpinning the design of vaccine trials, the validity of A/B tests, and driving the “reproducibility crisis” in the social sciences.

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Article

Break Them up? The Case for Interoperability Among Direct Messaging Platforms

Feb. 2022

Despite the dire need for regulation, direct messaging is the overlooked middle child of social media. While structural break ups of technology platforms is en vogue, it is unlikely to have meaningful impacts in this market, relative to interoperability among messaging platforms.

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Github

Managing Online Rumour Proportions During Offline Protests

Aug. 2021

Master's thesis at the University of Oxford. An experimental analysis of misinformation and rumour sharing during ambiguous contexts. Awarded distinction and one of 4 'Highly Commended' thesis prizes.

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👓

Github

Bitmoji Facial Segmentation

Jul. 2021

Utilized PyTorch for transfer learning (U-NET architecture/ImageNet base weights) to develop computer vision models for facial semantic segmentation of Bitmojis at Princeton University's Department of Psychology.

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🕺

Blog

How COVID-19 has Changed our Music Listening Habits

Mar. 2021

COVID-19 has brought enormous amounts of anxiety and uncertainty. This article shows how the pandemic has affected popular music listening habits.

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🧫

Blog

Understanding Word2Vec through Cultural Dimensions

Jul. 2020

Understanding the decisions AI make is critical in mitigating its downsides. This article explains what cultural dimensions are, and demonstrates how they can increase interpretability and quantify bias in word embeddings.

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Blog

Anything2Vec: Mapping Reddit into Vector Spaces

Jul. 2020

Word2Vec is a powerful machine learning technique for embedding text corpus' into vector spaces. While useful for NLP problems, this blog post shows how it can also be used to represent and better understand communities on Reddit.

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🍿

Blog

Classifying Shakespeare with Networks

Jun. 2020

What distinguishes Shakespeare's comedies from his tragedies? Without looking at a single line of dialogue, this article shows that it is possible to use networks to classify Shakespeare's plays. Posted on Towards Data Science.

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🧠

Blog

Do Neural Networks Ever Forget?

Jun. 2020

How machine learning throws a wrench in the 'right to be forgotten.' Bringing in some of the latest computational research on privacy, this post examines how the principles of GDPR collide with the realities of neural networks.

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Blog

Analyzing Political Polarization: Topic Centrality

May 2020

Extending graph centrality to show how different political messages affect the flow of information. The final part in a series posted on the popular blog Towards Data Science.

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Blog

Analyzing Political Polarization: Topic Modelling

May 2020

Part two of three in a series that analyzes political polarization through network science. Modelling and extracting topics from political tweets. Posted on the popular blog Towards Data Science.

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Blog

Analyzing Political Polarization: Engagement Graphs

May 2020

Part one of a three in a series that breaks down my undergraduate thesis in an accessible and engaging format. Posted on the popular blog Towards Data Science.

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Paper

Topic Centrality for Political Messaging

Apr. 2020

Using network science and unsupervised machine learning to quantify the "bridging" and "bonding" nature political messages.

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NLP

🧶

Paper

Modelling Axes of Political Engagement

Mar. 2020

Do people care more about policy or politicians when choosing to retweet political content online? Undergraduate thesis developing random graph models to model drivers of political engagement.

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🚙

Repo

Reinforcement Learning for Traffic Flow

Dec. 2019

A reinforcement learning agent that helps control the flow of traffic. Through this simple RL algorithm, we were able to reduce carbon emissions by a third, and cut time waiting at red lights in half.

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