I am working as a Data Scientist for the University of Illinois System organisation, Administrative Information Technology Services (AITS). I assist the Advanced Analytics team in handling various projects concerning the university. Some of the key techniques I learned as NLP algorithms to process data, like TF/IDF, applying BERT LLM, and using Azure OpenAI.
In the past, I have worked as a Junior Research Fellow at DA-IICT. My project involved monitoring various parameters of plants using an IoT-based sensor system and applying techniques of Machine Learning to predict the chances of diseases in the plants. Based on the collected data, I built novel neural networks to predict fungal growth in plants and create an early warning system to secure livelihoods.
One of the key learnings I received while working on these projects is that the quality of data is the most important part of generating valuable and accurate insights. I realize that for any machine learning engineer, it is important to know how to deal with the inconsistencies in the raw data gathered from the real world before progressing towards the assessment part.