– Advised small businesses on the strategic implementation of AI solutions towards business problems.– Researched and developed 2D & 3D Pose Estimation algorithms for accurately tracking humans and animals.– Developed a large scale internet web-scraping pipeline utilizing LLMs, GenAI, and RAG methodologies.- Implemented prototype machine learning models for proof of concept applications

– Researched and applied machine learning methods to formal verification software products.– Led a team to curate a specialized dataset and engineer useful predictive features.– Developed a Random Forest model to predict optimal proof-engine usage, improving run-times by 30%.– Led effort to upgrade documentation search engine functionality using Deep Learning approaches.– Collected relevant documentation and interviewed product experts to create a search engine dataset.– Fine-tuned BERT models for Semantic Search and other Natural Language Processing (NLP) tasks.– Improved top-5 accuracy of search engine by 20% over classical baseline.

– Researched and applied state-of-the-art Computer Vision and deep learning algorithms for short-term weather forecasting.– Pioneered data-driven forecasting efforts within a predominantly meteorological team as the sole ML engineer.– Developed intuitive data visualizations and performance metrics, providing actionable insights to optimize modelperformance and guide decision-making processes.– Implemented and trained deep learning models such as CNNs, LSTMs, and UNet.– Architected deployment of the end-to-end solution onto a production server, now utilized by customers for real-time cloud position forecasts.– Engineered a user-friendly Graphical User Interface (GUI) to facilitate manual correction of data anomalies,streamlining the data validation process and enhancing overall model accuracy.– Continuously monitored and fine-tuned model performance in real-world scenarios.

– Led the efforts within the Algorithms Team to predict munition flight times.– Applied neural networks towards flight time regression-based problem, achieving exceptional accuracy and precision.– Managed a massive TeraByte scale dataset used for training and verifying machine learning models.– Engineered an AutoML system, streamlining the model generation process. This system autonomously generated and trained models on subsets of the dataset, providing extrapolated estimates of performance when scaled to the full dataset.– Collaborated with multidisciplinary teams to deploy Neural Network and KNN models on military aircraft.

- Researched methods of compressing deep learning architectures such as pruning and distillation- Formulated methods of combining the features of compressed models to enhance the accuracy of supervised neural network models- Implemented models and methods proposed in research papers

• Tutor students of all ages from elementary to college in various subjects• Assisted students with Calculus, Physics, and Chemistry homework• Met with parents to create tailored learning plan

- Independently developed image processing methods to distinguish between weeds and crops.

- Developed a prototype PCB board for a micro satellite in coalition with NASA.