❖ Led data management, governance, data curation, preprocessing, and quality assurance for large-scale microscopy images, integrating Napari API for image annotation and using active learning for improved mask correction.❖ Developed multimodal deep learning AI models with multiple encoders and decoder(s) for multiclass segmentation of Two-Photon Excitation Fluorescence (TPEF) 5D images, achieving high recall, specificity, and F1 scores.❖ Independently implemented and deployed SAM, Cellpose, CNNs, ResNet, YOLO, UNET, and GANs for single-cell analysis. Utilized data augmentation and transfer learning with pre-trained weights to improve model performance.❖ Calibrated TPEF images and co-registered with NADH channel to ensure pixel-level alignment of metabolic channels. Utilized sparsity-based methods in UNET to select relevant TPEF images thereby improving image acquisition rates.❖ Fine-tuned LLMs, leveraging OpenAI's ChatGPT API via LangChain to implement an autonomous agent capable of performing image and text generation tasks interactively.❖ Utilized NLP to summarize lab notes, extracting key insights to streamline documentation. Conducted sentiment analysis on electron microscope ratings, providing a nuanced understanding of user feedback and identifying areas for improvement.❖ Provided weekly progress reports with actionable insights to collaborators, participated in writing grants, maintained GitHub repositories, and contributed to an open-source Python library (TRIPs-Py) for image processing.❖ Mentored engineers on ML algorithm development and benchmarking, covering topics from NLP to advanced deep learning models like RNN, LSTMs, GRU, GAN, Transformers, NLP, VAEs, Diffusion models, and Graph Neural Networks.

❖ Developed and applied ML algorithms to detect transcriptional patterns of the host immune response to infection. ❖ Utilized GPUs to optimize custom deep Convolutional Neural Networks (CNN) for the binary classification of histopathology images, aimed at classifying bacterial strains associated with Tularemia (rabbit fever).❖ Performed data cleaning and pre-processing of raw hospital data, addressing nuances such as missing entries, identifying artifacts, and reconciling variations in patients' records to enhance data quality and integrity.❖ Analyzed high-dimensional biological data sets to identify novel biomarkers responsible for (zoonotic) disease progression and performed pathway analysis.❖ Developed transfer learning algorithms with XGBoost, GBM, Naive Bayes, SVM, KNN, Decision Tree, Random Forest, Logistic Regression, and Artificial Neural Network (ANN) to classify bacterial strains.❖ Mentored upcoming computer scientists and engineers on linear algebra for data science.❖ Worked closely with biomedical scientists and virologists to investigate Zoonotic Disease Risk Mitigation Strategies for Pandemic Preparedness.

❖ Investigated tensor-based stochastic optimization frameworks for large-scale ptychographic images.❖ Exploited embedded natural data formats to speed up the process of data discovery in image retrieval problems.

❖ Developed optimization and iterative learning-based algorithms for dimensionality reduction of large-scale problems. ❖ Performed 3D image data analyses to reconstruct/restore degraded color images, MRI scans, and videos with high precision.❖ Developed and applied tensor-based optimization algorithms to encode multi-dimensional data and elicit feature extraction. This includes preserving and leveraging data structures when data is high-dimensional.

❖ Recitation Leader, proctor, and grader for pre-calculus, calculus I & II.❖ Managed computer lab helpdesk sessions.❖ Mentored a group of 9th – 12th graders (with special needs) for PARCC exams in the Trio-Upward Bound Program.❖ Tutored math and physics to first-generation high-school students in the Educational Opportunity Program (EOP).

❖ Developed and validated learning-based models to predict radiation intensity from pool fire data.❖ Utilized PHAST 7.2 to simulate data for view factor calculations from different scenarios.❖ Performed safety and hazard analysis of large pool fires for near and far afield observers.❖ Conducted sensitivity analyses, hyperparameter tuning, and benchmarking exercises to refine the precision and performance of pool fire models.

❖ Mentored 100+ undergrads in calculus, and advanced math using active learning and collaborative group work.