Usama Ahmad

Led the improvement of an AI assistant, leveraging GPT-4 Turbo, GPT-4, and GPT-3.5-Turbo from OpenAI, along with Google's speech-to-text technology, to generate potential diagnoses based on patient symptoms. Conducted extensive Research and Development (R&D) on Transformer models and Large Language Models (LLM), exploring Hugging Face repositories and optimizing pipelines for local testing and fin

Performed data mining and extracted usable data from valuable sources, utilizing machine learning tools for feature selection and classifier optimization. Conducted preprocessing of structured and unstructured data, enhancing data collection procedures for analytic system development.

Collected and analyzed large volumes of structured and unstructured data, identifying data sources and developing solutions and strategies for business problems. Combined various algorithms and modules to discover trends and patterns, presenting data using diverse visualization techniques and tools.

Responsible for Feature Engineering, Exploratory Data Analysis (EDA), and Data Wrangling, working on numerous projects including Titanic Prediction and Credit Card Fraud Detection. Developed and trained various Machine Learning Models, and worked with Transformers, Hugging Face, and LLMs to build small models for diverse applications.

Developed projects related to Python for Web Scraping. Created web applications using Flask and Django frameworks for backend development.

Analyzed large volumes of structured and unstructured data from various sources, applying statistical and machine learning techniques to extract meaningful insights. Developed predictive maintenance models using sensor data to identify potential equipment failures and optimize production processes by analyzing well production and reservoir characteristics.

Completed a Bachelor's degree in Computer Science, gaining foundational knowledge in various computing principles. The curriculum covered essential topics relevant to the field.