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Education

  • 2022-Present
    PhD in Computer Science
    University of Illinois at Chicago
    • GPA: 4.0/4.0
  • 2020-2022
    MSE in Computer Science
    Johns Hopkins University
    • GPA: 3.5/4.0
  • 2017-2020
    BS in Computer Science
    University of Massachusetts Amherst
    • GPA: 3.7/4.0
    • Honors College Scholar with Great Distinction

Experience

  • 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
  • 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
  • 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
  • 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
  • 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
  • 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

Skills

Programming Languages Python, Java, C++, C, JavaScript
Libraries & Frameworks PyTorch, SciPy, Sci-kit Learn, NumPy, Latex