I am a software engineer at Airbnb working on
machine learning infrastructure. I am primarily
interested in the machine learning spaces,
focusing on infrastructure to support the
machine learning use-cases across the company.
Prior to joining Airbnb I was a Sotware
Engineer working in various companies in the
San Francisco Bay Area, and before the US,
Postdoctoral Fellow at the University of
Waterloo in Canada.
Employment
Software Engineer | Airbnb
Developing and building out the machine
learning infrastructure tooling to support
machine learning engineers in the copmany in
their day to day duties.
Building out the infrastructure to power the
machine learning at Instacart. Instacart is
built within the AWS ecosystem, so I gained a
lot of experience with AWS tools and
management/monitoring tools such as Terraform,
Datadog etc. During my time at Instacart, I
identified many areas for cost saving,
including multi-million dollar savings by
removing redundant logging.
Software Engineer | Meta (fka Facebook)
My time in Facebook was spent in the Ads
& Business Platform organization. I
focused on solving advertiser facing issues
within the delivery system, including
diagnosing systemic inefficiencies in ranking
and delivery systems, large scale back-end
migrations to unblock scaling of products, and
development of new products. Served as an
internal hiring point of contact for the team,
as well as managing and mentoring interns and
being a ramp-up buddy for new engineers, both
senior and junior, to both the team and org.
Postdoctoral Fellow | University of Waterloo
Developed a novel anytime, score-safe, document scoring algorithm.
Conducted research on reproducibility, and replicability, of
information retrieval and machine learning NLP systems. This included
software and library versioning, hyper parameter tuning, and hardware
level details.
Included instructing the following courses:
CS241: Foundations of Sequential Programming (aka Introduction to Compilers)
Assistant Research Fellow | University of Otago
Investigating the areas within the indexing process that the rest of the system were waiting on, and analysing these areas for potential speed-ups.
Lab Demonstrator | University of Otago
A lab demonstrator has similar responsibilities to a teaching-assistant, helping students with their practical lab work. This demonstrating was undertaken while studying for both MSc (COMP150) and PhD (COSC241, COSC242, COSC244).
COSC244: Data Communications, Networks and the Internet
Research Assistant | University of Otago
A research assistant is typically employed on a short-term contract in order to assist staff members with an ongoing research project. I have been involved in two of these:
Relevance and Readability
Working on incorporating readability metrics into a search engine to re-rank results in order to return readable as well as relevant results. Involved working on a large C++ codebase (ATIRE) worked on by multiple people. Undertaken simultaneously with MSc study.
Collaborative Filtering Improvement
Working on improving the predictions made by implementing high level algorithms for my collaborative filtering system I developed as part of my honours degree project.
Investigating various ways to make the process of indexing, and searching, web-scale collections more efficient without impacting the effectiveness of the system. For instance, we can choose to not index certain documents, but if we chose the wrong documents then this could have a significant impact on the effectiveness. My research was performed using the ATIRE open source search engine, this search engine was developed at Otago and I remain involved in its development.
MSc (Thesis Only) with Distinction | Computer Science, University of Otago
The new user problem is a problem that all collaborative filtering systems must face. How can the system make recommendations for a user when it does not know what that user likes?
BSc(Hons) First Class | Computer Science, University of Otago
Information Processing and Management (Elsevier) Reviewer
Information Processing Letters (Elsevier) Reviewer
Information Retrieval Journal (Springer) Reviewer
Transactions on Information Systems (ACM) Reviewer
Transactions on Knowledge and Data Engineering (IEEE) Reviewer
SIGIR2021 — 44th International ACM SIGIR Conference on Research and Development in Information Retrieval Senior Program Committee [Long Papers]
SIGIR2020 — 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval Senior Program Committee [Long Papers] Program Committee [Short Papers]
ADCS2019 — 24th Australasian Document Computing Symposium Program Committee
CIKM2019 — 28th ACM Conference on Information and Knowledge Management Program Committee
SIGIR2019 — 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval Program Committee
ADCS2018 — 23rd Australasian Document Computing Symposium Program Committee
SIGIR2018 — 41st International ACM SIGIR Conference on Research and Development in Information Retrieval Program Committee (CoreIR/Search and Ranking Track)
ADCS2017 — 22nd Australasian Document Computing Symposium Program Committee
ICTIR2017 — 3rd ACM International Conference on the Theory of Information Retrieval Program Committee
ADCS2016 — 21st Australasian Document Computing Symposium Program Committee
ADCS2015 — 20th Australasian Document Computing Symposium Program Committee
RIGOR Workshop @ SIGIR2016 — Reproducibility, Inexplicability, and Generalizability of Results Background Machinations – Open-Source IR Reproducibility Challenge
Presentations
Questionable Answers in Question Answering Presentation for UWaterloo Data System Group Meeting (extended version of NAACL2018) Presentation for NAACL2018
Query Processing Strategies in Information Retrieval Presentation for UWaterloo Data System Group Meeting
Rank-at-a-Time Query Processing Presentation for ICTIR2016
Toward Reproducible Baselines: The Open-Source IR Reproducibility Challenge Presentation for ECIR2016
Collision Resolution in Hash Tables for Vocabulary Accumulation During Parallel Indexing Presentation for ADCS2015
Improving Throughput of a Pipeline Model Indexer Presentation for ADCS2015
The Reproducibility Challenge Overview Presentation for the RIGOR Workshop @ SIGIR2015
Designing a Hash Function for Information Retrieval Presentation for the Computer Science and Information Science Seminars
Pipes, Trees and Hash Presentation for the Otago Computer Science Systems Group Seminar
Diversified Relevance Feedback Presentation for the SIGIR2013 Doctoral Consortium Re-presented for the Otago Computer Science Postgraduate Symposium
Effects of Spam Removal on Search Engine Efficiency and Effectiveness Presentation for ADCS2012
Diversification in Information Retrieval Presentation for Otago Computer Science Postgraduate Symposium
The Cold-Start Problem in Collaborative Filtering Presentation for Otago Computer Science Postgraduate Symposium
Awards
University of Otago Computer Science Department Postgraduate Publishing Prize
ACM SIGIR Student Travel Grant
ADCS Student Travel Grant
Projects
I have been heavily involved in the development of the ATIRE search engine. ATIRE is a research search engine written in C++ and has been demonstrated to be fast at both indexing and searching.
I wrote the memcached exporter for the Prometheus monitoring system. This has since been incorporated as a project under the Prometheus Github organization.
I did the majority of the background running and checking of scripts for the Reproducibility Challenge.
As mainly a learning exercise, I designed and built a community site for the game Hearthstone. The site allowed players to install a client which would upload game logs to a server. These logs would then be parsed to provide an accurate play-by-play web-viewable version of the game. During this exercise I learnt a lot about the Docker and Amazon AWS eco-systems, as well as modern front-end development suites such as React.js.
