My name is Andriy. I'm currently building a company called Nomic with the goal of making AI systems more accessible
and explainable to all humans.
Before Nomic I was a machine learning Ph.D. student at NYU Courant focused on interpretability of deep nets. Teaching computers do things that only humans should be able to do has dominated my mind-space since about 2017.
The set of topics I am easily distracted by if brought up in conversation include: self-supervised representation learning, pre-transformers NLP, clinical informatics, long-winded discussions about data cleaning, building infrastructure for software that involves ML models and why you should care about helping fight for democracy in Ukraine.
Before Nomic I was a machine learning Ph.D. student at NYU Courant focused on interpretability of deep nets. Teaching computers do things that only humans should be able to do has dominated my mind-space since about 2017.
The set of topics I am easily distracted by if brought up in conversation include: self-supervised representation learning, pre-transformers NLP, clinical informatics, long-winded discussions about data cleaning, building infrastructure for software that involves ML models and why you should care about helping fight for democracy in Ukraine.
Projects I am Proud of
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Nomic Embed: Training a Reproducible Long Context Text Embedder Zach Nussbaum, John X. Morris, Brandon Duderstadt, Andriy Mulyar technical report [code] [report] |
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MT-Clinical BERT: Scaling Clinical Information Extraction with Multitask Learning. Andriy Mulyar, Ozlem Uzuner, Bridget McInnes Journal of the American Medical Informatics Association [code] [paper] |
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Clinical Concept Linking with Contextualized Neural Representations. Elliot Schumacher, Andriy Mulyar, Mark Dredze ACL 2020 [paper] |
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Phenotyping of clinical notes with improved document classification models using contextualized neural language models. Andriy Mulyar, Elliot Schumacher, Masoud Rouhizadeh, Mark Dredze NeurIPS 2019 ML4H Workshop Extended Abstract [code] [paper] [blog] |
Updates
Things I've been up to.| April 2023 | Raised 17M in venture funding to continue building Nomic. |
| April 2022 | Left my Ph.D. to work to co-found Nomic - a company dedicated to building explainable and accessible AI systems. |
| September 2021 | Started a Ph.D. in Machine Learning at NYU Courant. |
| September 2020 | Worked as a machine learning engineer at Rad AI digging through millions of radiology reports and training LLMs on them. |
| June 2020 | Software Engineering (ML/NLP) intern at Costar Group. |
| February 2020 | CRA published 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.|
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Multitasking Transformers Training Transformers to perform multiple tasks with the same set of representations. |
January 2020 |
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Multi-label Document Classification with BERT Language model powered long document classification architectures. (NeurIPS ML4Health 2019). |
September 2019 |
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Clinical Semantic Similarity Training language models (BERT) towards associating semantic equivalence in clinical notes. |
July 2019 |
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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 |
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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 |
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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 |
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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 |
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Gateway Math A software for mathematics educators to generate dynamic worksheets. |
January 2017 |
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Reproducible Machine Learning Effective methods to maintain replicable and reproducible research environments in computational science domains. |
November 2018 |