cv
Education
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2022-Present PhD in Computer Science
University of Illinois at Chicago - GPA: 3.5/4.0
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2020-2022 MSE in Computer Science
Johns Hopkins University - GPA: 3.5/4.0
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2017-2020 BS in Computer Science
University of Massachusetts Amherst - GPA: 3.7/4.0
- Honors College Scholar with Great Distinction
Skills
| Programming Languages | Python, Java, C++, C, JavaScript |
| Libraries & Frameworks | PyTorch, DeepSpeed, FAISS, SciPy, Latex |
Awards
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2023 ACL Area Chair Award
- Awarded for second-author paper (ParaAMR) in semantics
Experience
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2022-Present Research Assistant
University of Illinois at Chicago - Working with Professor Cornelia Caragea on science-focused natural language processing
- Developing approaches to deeply understand scientific facts and documents
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2021 Applied Scientist Intern
Amazon - Worked with Dr. Anoop Kumar on unsupervised paraphrase-based data augmentation
- Leveraged Abstract Meaning Representations (AMRs) to generate syntactically diverse paraphrases
- Achieved SOTA performance on unsupervised paraphrase generation task on multiple datasets
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2020-2021 Research Assistant
Johns Hopkins University - Worked with Professor Benjamin van Durme on semantically grounded image classification
- Improved ResNet architecture for few-shot learning with geometric hierarchical embeddings
- Extended neural entity typing pipeline to new datasets in a distributed training setting
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2018-2020 Undergraduate Research Assistant
University of Massachusetts Amherst - Worked with Professor Andrew McCallum on fine-grained entity typing using PyTorch
- Developed a stacked BiLSTM with embedding-based loss functions and hierarchical type constraints
- Record-linked datasets including Amazon-GoogleProducts using a compound LSTM + CNN model
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2018-2020 Undergraduate Course Assistant
University of Massachusetts Amherst - Graded theory-intensive problem sets and exams in Artificial Intelligence and Algorithms
- Helped students in Computer Systems complete programming assignments written in C and assembly
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2019 Visiting Undergraduate Researcher
University of Southern California - Worked with Professor Xiang Ren on reinforcement learning-based knowledge graph (KG) reasoning
- Formulated contextual text-structure embedding to augment inference paths with with non-KG entities
- Trained a PCNN with attention to perform distantly supervised relation extraction on inference paths
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2018 Undergraduate Research Intern
Information Sciences Institute - Worked with Professor Craig Knoblock to build and link entities in a KG of space-related objects
- Implemented level-based access control for data across multiple Elasticsearch indices
- Extracted information on 1000s of satellites and incorporated data into Elastic workflow