About

Hassan Chughtai is a passionate Machine Learning Research Engineer who strives to bring meaningful change to the world through the synthesis of technology, innovation, and design. Currently working as a Machine Learning Engineer at ExxonMobil, he is part of a cross-disciplinary team of researchers developing machine learning models to automate seismic interpretation, reducing cycle time for upstream exploration. Hassan has also developed a production-ready NLP engine trained on a dataset of 20 million geoscience documents to perform neural machine translation tasks, i.e., question answering and summarization, which is hosted in Azure cloud and provides exploration geoscientists with highly accurate results. His technical expertise includes Bidirectional Transformers (BERT), PyTorch, HuggingFace, Elasticsearch, FAISS, and Azure. Before joining ExxonMobil, Hassan worked as Head of Education at Texas Blockchain Foundation, where he led a collaboration between the foundation and the Cockrell School of Engineering to offer an undergraduate and graduate blockchain course. He also worked as a Software Engineer Intern at IBM, where he developed a Case Escalation Prediction and Resolution model using SciKit Learn, Keras, Watson NLU, and achieved high Recall and Mathews Correlation Coefficient scores. Hassan holds a Master of Science in Computer Science from Columbia University and a Bachelor of Science in Electrical and Computer Engineering from The University of Texas at Austin. He is also a graduate of Bridgewater Raritan High School. His technical skills include ML, Research Scientist, NLP, Azure, BERT, NLU, Software Engineer, Scikit, Elastic Search, Pytorch, Keras, Salesforce, Supervised Learning, and ETL. With 3.20 years of relevant experience, Hassan is a highly skilled and motivated individual who is passionate about using technology to improve people's lives.