About

Gustavo A. Lujan is a highly experienced Data Scientist with over 10 years of experience in executing data-driven solutions. Currently working as a Deep Learning Data Scientist at Intel Corporation, Gustavo has a proven track record of translating real-world problems into models that perform as expected in new and never seen data. Gustavo's modeling skills are extensive and include Deep Learning, NLP, text mining, topic modeling, anomaly detection, time series, predictive analytics, DOE, response surface, random forest, XGBoost, linear and ridge regression, lasso, SVM, PCA, and ICA. He is also proficient in software skills such as Python, R, Scala, Spark, Hadoop, SQL, Docker, JMP, Azure, AWS, Keras, Pytorch, and TensorFlow. In his current role at Intel, Gustavo is responsible for developing state-of-the-art machine learning techniques that can be integrated into Intel’s processes. He is also using Keras and Pytorch to develop state-of-the-art NLP models based on Deep Learning architectures. Gustavo has facilitated the implementation of Blockchain in the supply chain (research done with UC-Berkley) and implemented a web app tool using machine learning and NLP to facilitate the auditing process of contracts. He also provides guidance to the group of data scientists on Hadoop and ML solutions with Spark-Scala and PySpark. Prior to his current role, Gustavo worked as a Senior Machine Learning Engineer and Data Scientist at Intel. In these roles, he implemented ML algorithms to detect cybersecurity threats on Big Data (Apache-Spot project) and applied data mining tools in large scale databases using HDFS, Hive, Scala, and Spark. Gustavo holds a Doctor of Philosophy (Ph.D.) in Industrial Engineering from Arizona State University, a Master of Science (M.S.) in Industrial Engineering from Arizona State University, a Master of Engineering (M.Eng.) in Quality Systems and Productivity from Tecnológico de Monterrey, and a Bachelor's degree in Industrial Engineering from the Institute of Technology of Sonora. Gustavo's tech stack includes Deep Learning, Research Scientist, Data Scientist, ML, NLP, Keras, Spark, SQL, AWS, SVM, XGBoost, Random Forest, Scala, Hadoop, Pytorch, Blockchain, Docker, TensorFlow, Azure, Senior Software Engineer, Python, Web, HDFS, Big Data, and Apache Hive. With 11.29 years of relevant