Washington DC-Baltimore Area
Experienced Data Scientist/Machine Learning Engineer leader, with an MSc in Computer Science and 10+ years of experience. Led end-to-end ML-based projects from design, through R&D, to deployment. Passionate about AI applications that do good for the world.
Built AIRegRetrieve (multilingual RAG); cut compliance-research time; unanimously approved as corporate bounty. Launched IntelliSCALE via RAPID; reduced EDD report cycle time. Authored 3 position papers on LLMOps AI governance
Leading the development of a scalable serverless application on AWS GovCloud. Designing and developing an AI/NLP system to streamline the FDA submission process, enhancing premarket review, approval, surveillance, and recall procedures. Managing a 10-person full-stack engineering department. Overseeing the PDF Ingestion processing pipeline, including layout analysis, table structure recognition, and OCR.
- Currently work as a ML Engineer at SAIVA AI, developing healthcare insights over Electronic Health Records (EHR) data for patients at Skilled Nursing Facilities (SNFs). ML solutions include gradient boosting models over the featurized EHR information, leading to early detection of: - unplanned hospitalization transfers - patient falls - patient wounds.
- Worked as a Lead ML Engineer at Rekor Systems, developing Computer Vision / AI solutions based on our roadway video data. - Responsible authority for all ML-based software solutions - Management of a team of three Machine Learning Engineers and Data Scientists. - Responsibilities include the entire ML project lifecycle, including data collection & annotation, AI algorithm R&D, agent backend development, through deployment, monitoring, and customer support. - Research projects include (but are not limited to): o Improvement of our core OCR-based Automated License Plate Reading (ALPR) through data, modeling, and optimization dynamic improvements. o Multitask & Multiclass model for predicting vehicle attributes from images (make, model, body type, color, orientation, and model-year) o Improvements of our edge detection algorithm (for cropping vehicles and license plates) o Object tracking in video for roadway analytics.
- Worked as Machine Learning Engineer at Elminda Ltd’s Deep Learning team. Elminda is a healthcare start up involved in brain health and provide health-related insights to facilitate treatment of a wide variety of brain disorders, based on big-data analytics leveraging patient Event Related Potential (ERP) EEG signals. - Designed and implemented Machine Learning solutions for a variety of projects such as detection of depression and assessment of memory loss in seniors. - The responsibility included ownership across the data science process, from querying unstructured signals, through preprocessing, analysis, modelling, and deployment. - Spearheaded the product’s statistical validation through its 510(k) submission to the FDA.