CV
General Information
| Full Name | Kuntal Pal |
| Date of Birth | 10th March 1995 |
| Languages | English, Bengali, Hindi |
Education
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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.
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Relevant Coursework.
- Data Mining Techniques
- Database Management Systems
- Probabilistic Models for AI
- Optimization in Machine Learning
- Introduction to Deep Learning
- Advanced Computer Vision.
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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
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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.
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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.
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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
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2015-now
al-folio
- A beautiful, simple, clean, and responsive Jekyll theme for academics.
Certifications
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2023
- TensorFlow Developer Certificate - TensorFlow Certification Program
- IT Automation with Python Professional Certificate - Google
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2021
- Deep Learning Specialization - DeepLearning.AI
Academic Interests
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Deep Learning
- Large language models.
- Neural architecture search.
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Particle Physics.
- Dark Matter.
- Effective Field Theory.
Other Interests
- Hobbies: Photography, Traveling and cooking.