RESEARCH INTERN: ANTIBACTERIAL PEPTIDE DESIGN FOR LTAS INHIBITION June 2023 – June 2024
- Utilized Machine Learning (ML) to engineer highly specialized AMPs to effectively neutralize LtaS, a crucial enzyme found in gram-positive bacteria responsible for severe diseases, including bacterial meningitis and pneumonia.
RESEARCH INTERN: INTRACTABLE SEIZURE PREDICTION USING DEEP LEARNING
June 2022 – May 2023
- Developed a comprehensive framework for scalable seizure prediction that predicted seizures hours before seizure onset, while previous research’s prediction time was at most 15 min. Utilized MNE library for signal processing techniques, including bandpass filtering and independent component analysis (ICA). Applied deep learning models using TensorFlow, including CNNs, RNNs, and LSTMs, to enhance prediction accuracy by 90% within 2 hours.
RESEARCH INTERN: UNIVERSITY OF WASHINGTON, ECE
June 2022 – Sept. 2022
- Conducted advanced research in clustering and visualization of DNA electrical signals with UW Electrical and Computer Science Engineering faculty, using AI to analyze complex datasets. Implemented and visualized machine learning clustering algorithms, including HDBSCAN, DBSCAN, agglomerative clustering, K-means clustering, and DMODX, to effectively separate representative data from noise.
RESEARCH INTERN – METASTATIC CANCER DETECTION
June 2021 – Feb. 2022
- Developed a novel metastatic cancer detection system using the genetic algorithm, decision trees, PCA, logistic regression, and k-nearest neighbors with a 70% accuracy over manual detection for robust predictive modeling. Employed Python libraries such as Pandas, Numpy, Matplotlib, Seaborn, Sklearn, Poetry, and Imageio for efficient data processing and visualization.
