My name is Andriy Mulyar and I am undergraduate passionate in mathematics and computer science. My research interests reside in the intersection of machine learning, statistical learning and natural language processing. I particularly enjoy tackling interesting problems in text mining and information extraction.

I am currently applying to graduate schools (to start in Fall 2021) and would like to focus on transfer learning, few-shot learning and weak/self-supervision in any signal domain (text, vision, audio, etc.).


Current Projects

Things i'm doing.
Multitasking Transformers
Training Transformers to perform multiple tasks with the same set of representations.
January 2020
Multi-label Document Classification with BERT
Language model powered long document classification architectures. (NeurIPS ML4Health 2019).
September 2019
Clinical Semantic Similarity
Training language models (BERT) towards associating semantic equivalence in clinical notes.
July 2019
medaCy: Medical Text Mining and NLP Framework
medaCy is a highly predictive text processing and NLP research framework built over spaCy that leverages cutting-edge tools for mining medical text.
August 2018

Updates

Things I've been up to.
June 2020 Software Engineering (ML/NLP) intern at Costar Group.
February 2020 CRA put up a write-up about me.
December 2019 Attended NeurIPS 2019 and presented a poster at ML4Health!
November 2019 Presented posters at the N2C2 2019 workshop (AMIA) and VCU Undergraduate Research Symposium.
Summer 2019 Internship at Johns Hopkins CLSP supervised by Mark Dredze.
Spring 2019 Led a team of undergraduate students to improve software experience of medaCy. Supervised by Bridget McInnes.
Fall 2018 Co-developed a software framework, medaCy , for building and sharing statistical information extraction models. Supervised by Bridget McInnes.
Summer 2018 VCU DURI Fellowship supervised by Bartosz Krawczyk to study theoretical properties of decision trees.

Inactive Projects

Things i've done.
Clinical Concept Normalization and Extraction
Applying neural ranking to map unstructured text in clinical notes and electronic health records to structured medical ontologies. Work accepted at ACL 2020.
June 2019
Automatic Graph Conjecturing
A service auto-conjecturing over graphs to empirically discover novel relations between graph theoretic properties and invariants. A project under Dr. Craig Larson.
May 2019
Decision Trees: Exploiting Local Data Properties and Nested Ensembles
Trees are excellent learners: simplistic, interpretable and versatile. This project explores their interaction with local data characteristics to improve predictive performance and interpretability.
March 2018
Gateway Math
A software for mathematics educators to generate dynamic worksheets.
January 2017
Reproducible Machine Learning
Effective methods to maintain replicable and reproducible research environments in computational science domains.
November 2018