CV

General Information

Full Name Kuntal Pal
Date of Birth 10th March 1995
Languages English, Bengali, Hindi

Education

  • 2017 - Present
    PhD
    University of California, Riverside
    • Data analysis and predictive modeling in high-energy physics using statistical and ML-based techniques.
    • Neural architecture search using tensor completion.
    • Relevant Coursework.
      • Data Mining Techniques
      • Database Management Systems
      • Probabilistic Models for AI
      • Optimization in Machine Learning
      • Introduction to Deep Learning
      • Advanced Computer Vision.
  • 2012 - 2017
    BS-MS Dual Degree
    Indian Institute of Science Education and Research, Kolkata
    • Master’s Thesis - Automated Quantum Field theory calculations using SciPy.

Experience

  • 2017 - Present
    Graduate Student Researcher
    University of California, Riverside
    • Examine Tensor-Train decomposition with EM-algorithm for low-rank tensor completion in efficient hyperparameter search for neural networks.
    • Developed search strategies and engineered features for applying the XGBoost decision tree algorithm. Achieved 80% accuracy in separating rare signal events from background noise.
    • Constrained model parameters using hypothesis testing and confidence interval estimation.
  • 2020 - Present
    Kaggle Competitor
    kaggle.com
    • Forecasted sub-seasonal temperatures for multiple US locations using autoML library PyCaret for tuning CatBoost and TabNet regressors, achieving a top 30% ranking out of 709 teams.
    • Deployed a large protein language model(ESM-2) and 3DCNN architecture (ThermoNet) for predicting enzyme variant stability based on melting temperature data, incorporating protein structure analysis with Rosetta and HTMD, placing in the top 40% among 2482 teams.
  • June, 2022 - July, 2022
    Team Lead - Data Science Challenge
    Lawrence Livermore National Laboratory
    • Mentored four undergraduate students in ML techniques, including data preprocessing, hyperparameter tuning, and Neural Networks, tailored to each team member's prior experience.
    • Achieved the highest AUC scoreof 0.89 among six teams with a pretrained transformer model for classifying ligand molecules via SMILES strings.
    • Trained 3DCNNs based on voxel representation of ligand structures, achieving an accuracy of 71%.

Open Source Projects

  • 2015-now
    al-folio
    • A beautiful, simple, clean, and responsive Jekyll theme for academics.

Certifications

  • 2023
    • TensorFlow Developer Certificate - TensorFlow Certification Program
    • IT Automation with Python Professional Certificate - Google
  • 2021
    • Deep Learning Specialization - DeepLearning.AI

Academic Interests

  • Deep Learning
    • Large language models.
    • Neural architecture search.
  • Particle Physics.
    • Dark Matter.
    • Effective Field Theory.

Other Interests

  • Hobbies: Photography, Traveling and cooking.