AI's powers of translation should not be restricted to widely-spoken languages. Natural language processing and deep learning can be used to solve model bias and more in low-resource dialects.

– John Ortega, Postdoctoral Research Fellow, EAI

John E. Ortega is a postdoctoral fellow studying natural language processing, machine translation, and low-resource languagges at Northeastern University. He obtained a Ph.D. in Computer Science from the Universitat d’Alacant in Spain in 2021 and has recently  completed postgraduate research in Applied Linguistics at the University of Santiago de Compostela (also in Spain).

Prior to his arrival at NU, Ortega was a visiting scholar and lecturer at New York University and Columbia University. His research interests are in natural language processing, machine translation, and low-resource languages such Quechua, an indigenous language spoken in Peru by around eight million people.

Ortega also brings private sector experience to his research work. He has held consultancy positions in multiple companies in both the United States and Europe for the last 21 years, with a client list that includes but is not limited to healthcare, tech, finance and accounting, leisure and entertainment. In addition, Ortega has been a senior NLP research scientist for AIG and Nuance Communications, and an Executive Director for Artificial Intelligence and Machine Learning at JPMorgan Chase. 

He is an enthusiastic volunteer in his free time, organizing kids basketball tournaments, maintaining park grounds and rescuing elephants.