Education

• M.S. in Computer Science, North Carolina State University, 2023
• B.Tech in Electronics and Communication Engineering, PES University, 2020

Work Experience

• January 2023 - May 2023: Research Assistant
  • Social AI Lab, North Carolina State University
  • Duties included:
    • Scraped around 26000 reddit posts from r/Asianparents pushshiftio API.
    • Labelling ~5000 sentences (belonging to -600 posts) for prejudice, type of prejudice and prejudice topic.
    • Planning to leverage multiple transformer-based models like RoBERTa, DistilBERT for identifying prejudiced sentences.
      
      
• September 2022 - May 2023 : Research Assistant
  • IEC Lab, North Carolina State University
  • Duties included:
    • Utilized interactive learner to teach AI agents on how to solve algebra equations.
    • Conducted 15+ sessions and spearheaded data collection procedures to understand learning patterns.
    • Assisted in data wrangling and data labeling to improve its performance.
      
      
• May 2022 - August 2022 (Summer Internship): Summer Intern
  • HPCC Systems, LexisNexis Risk Solutions
  • Duties included:
    • Discovered causal relations using Bayesian networks, conditionalization and drew causal models with 9+ variables.
    • Leveraged discretization technique to increased speed of probabilistic dependence tests by 10-fold.
    • Analyzed behavior of the HPCC_Causality toolkit on synthetic and real-world datasets for causal discovery.
  • CAUSALITY PROJECT Summer 2022 internship blog.

Skills

• Languages: Python, Java, C/C++, R, NodeJS, Shell Scripting
• Web Technologies: HTML, JavaScript, CSS, REST, Express, Apache, Jenkins, Ansible, Chai, Mocha
• Databases: MySQL, SQL, PostgreSQL, MongoDB, AWS DynamoDB, PowerBI, Tableau
• Tools: Keras, TensorFlow, PyTorch, Git, GitHub, VS Code, Jupyter Notebook
• Domain Knowledges: Data Structures & Algorithms, Database and Management Systems, Operating Systems
• ML & NLP Models: CNN, RNN, LSTM, BERT, Word2Vec, GLoVe, ELMo, Tf-Idf
• Data Science: Pandas, NumPy, NLTK, SpaCy, Scikit-Learn, Causality

Domain Expertise

• Dataset Curation: Building my own dataset by webscraping
• Data Wrangling: Cleaning and transforming data using pandas, numpy, regex
• Data Visualization: Creating amazing visualization to convey data results using Matplotlib, Seaborn, Plotly, Tableau, PowerBI
• Data Modeling: Building Machine Learning models using Keras, TensorFlow, PyTorch, Scikit-Learn for various applications such as NLP, Computer Vision, Time Series, etc.
• Model Evaluation: Evaluating model performance using metrics such as accuracy, precision, recall, F1-score, AUC, etc.
• Model Optimization: Optimizing model performance by tuning hyperparameters, feature engineering, etc.

Extra-Curricular

• Awards:
  • Prof. CNR Rao award for being a consistent top 10% performer in PES University
• Certificates:
  • CITI Conflicts of Interest
  • CITI Responsible Conduct of Research
  • Group 2: Social-Behavioral-Educational Researchers - HSR Basic

Download PDF version of my Resume here.