My interests lay the intersection of machine learning and disaster response. Specifically, how to improve robustness and usability of automated systems in the disaster setting.
I grew up in Las Vegas and I enjoy running, hiking, spending time outdoors and in my spare time I am also an Instrument Rated Private Pilot, Advanced EMT, and a Firefighter.
I graduated with my Masters from Carnegie Mellon's Language Technologies Insitutute and my Bachelors from Rensselaer Polytechnic Institute. My educational background is in NLP and ML and my graduate research included collaborations with Bosch GmbH, DARPA, and Boeing.
After graduate school I joined the Microsoft AI Development Acceleration Program (MAIDAP) and I currently split my time between the Microsoft Office DocsML Team and collaborations with groups like the CDC and the WHO in development of machine learning and data management systems to respond to disasters like the COVID-19 pandemic.
Download CVExamination and Extension of Strategies for Improving Personalized Language Modeling via Interpolation
Shao, Mantravadi, Manzini, Buendia, Knoertzer, Srinivasan, Quirk
Workshop on Natural Language Interfaces, Association for Computational Linguistics 2020
Seattle, Washington, USA
Black is to Criminal as Caucasian is to Police: Detecting and Removing Multiclass Bias in Word Embeddings
Manzini, Lim, Tsvetkov, Black
NAACL-HLT ’19. The Proceedings of the 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Minneapolis, Minnesota, USA
Found in Translation: Learning Robust Joint Representations by Cyclic Translations Between Modalities
Pham, Liang, Manzini, Morency, Póczos
AAAI ’19. Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence
Honolulu, Hawaii, USA
Paper Presentation Poster Repository
