PhD Candidate in Computer Science
Specializing in NLP for Drone Flight Log Analysis
I am a PhD candidate in Computer Science with a strong focus on Natural Language Processing (NLP). My research is centered on developing domain-specific NLP models specifically tailored for the analysis of drone flight log messages. This work is crucial for forensic investigations, enabling the extraction of critical information from unstructured text data.
My goal is to create robust and interpretable NLP solutions that meet the stringent requirements of forensic settings, ensuring both accuracy and transparency in the analysis of complex flight data.
I fine-tune pre-trained NLP models to perform named entity recognition, specifically for extracting relevant terms from drone flight log messages. This allows for precise identification of key entities and events within the logs, aiding in forensic analysis.
Utilizing a similar NER-based modeling approach, I segment log messages into meaningful sentences and classify them into 'Event' and 'Non-Event'. This provides a structured understanding of the log content and the relationship between the log events occurences.
I develop simple yet effective and interpretable text classification models to flag log messages as either 'Normal' or 'Problem'. This serves as a rapid problem identification approach, allowing investigators to quickly pinpoint potential issues within vast amounts of log data.
A core aspect of my research is ensuring the interpretability and managing the complexity of the developed models. This is paramount in forensic settings, where understanding *why* a model makes a certain prediction is as important as the prediction itself.
Feel free to connect with me to discuss research, collaborations, or anything related to domain-specific NLP and log analysis.