Check out my work 👨🔧
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Blog Posts
About
Machine Learning
NLP
Politics
Causal Inference
Graph Theory
Reinforcement Learning
👁️
BlogUpgrading OpenAI's Moderation API with a new multimodal moderation model
Sep. 2024Core 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.
Research
Machine Learning
NLP
👨⚕️
SessionSafety2Vec: An Introduction to Text Embeddings and their Applications in T&S
Jul. 2023TrustCon2023 presentation on how embeddings models can enable Trust & Safety teams to better understand user behaviour on their platforms.
Research
Machine Learning
Politics
📞
PaperAutomated vs. manual case investigation and contact tracing for pandemic surveillance
Nov. 2022Lead author on the first randomized control trial of COVID-19 contact tracing – accepted to The Lancet's subsidiary, eClinicalMedicine.
Research
Causal Inference
Politics
🗻
OpenAIMy Next Phase
Aug. 2022Life update: I’m joining OpenAI's Trust & Safety team!
Blog Post
Machine Learning
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PaperMeasuring Alignment of Grassroots Political Communities with Political Campaigns
May 2022Lead 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.
Research
Machine Learning
Politics
🔋
BlogSimulating Statistical Power in R
Mar. 2022A 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.
Blog Post
Causal Inference
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ArticleBreak Them up? The Case for Interoperability Among Direct Messaging Platforms
Feb. 2022Despite 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.
Blog Post
Politics
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GithubManaging Online Rumour Proportions During Offline Protests
Aug. 2021Master'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.
Research
Causal Inference
Politics
👓
GithubBitmoji Facial Segmentation
Jul. 2021Utilized 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.
Research
Machine Learning
🕺
BlogHow COVID-19 has Changed our Music Listening Habits
Mar. 2021COVID-19 has brought enormous amounts of anxiety and uncertainty. This article shows how the pandemic has affected popular music listening habits.
Blog Post
Machine Learning
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BlogUnderstanding Word2Vec through Cultural Dimensions
Jul. 2020Understanding 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.
Blog Post
Machine Learning
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BlogAnything2Vec: Mapping Reddit into Vector Spaces
Jul. 2020Word2Vec 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.
Blog Post
Machine Learning
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BlogClassifying Shakespeare with Networks
Jun. 2020What 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.
Blog Post
Graph Theory
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BlogDo Neural Networks Ever Forget?
Jun. 2020How 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.
Blog Post
Politics
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BlogAnalyzing Political Polarization: Topic Centrality
May 2020Extending 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.
Blog Post
Graph Theory
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BlogAnalyzing Political Polarization: Topic Modelling
May 2020Part 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.
Blog Post
NLP
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BlogAnalyzing Political Polarization: Engagement Graphs
May 2020Part 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.
Blog Post
Graph Theory
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PaperTopic Centrality for Political Messaging
Apr. 2020Using network science and unsupervised machine learning to quantify the "bridging" and "bonding" nature political messages.
Research
Graph Theory
NLP
🧶
PaperModelling Axes of Political Engagement
Mar. 2020Do 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.
Research
Graph Theory
NLP
Machine Learning
🚙
RepoReinforcement Learning for Traffic Flow
Dec. 2019A 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.
Blog Post
Reinforcement Learning
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