Angeliki Metallinou

I am currently working as a senior machine learning scientist at Amazon Alexa. I am working on developing speech and language technologies for Amazon Alexa and products including the Amazon Echo and others. My research interests include natural language understanding, machine learning, deep learning, dialog systems, affective computing, automatic speech recognition, education and healthcare applications. Recent published work includes context aware natural language understanding for devices with screen (AAAI18), and topic-based conversational bot evaluation (NIPS18 conversational AI workshop).

Earlier, I was a research scientist at Pearson Knowledge Technologies, part of Pearson, where I worked on automatically evaluating speaking proficiency (fluency, pronunciation, vocabulary, etc) using machine learning and deep learning. I also worked on automatic grading of essays and short answer questions, using machine learning and natural language processing.

I am also interested in the area of affective computing, that was the focus of my PhD research at University of Southern California (USC), at the Signal Analysis and Interpretation Lab (SAIL). During my PhD, I worked on emotion recognition from speech and facial/body expressions during dyadic interactions. I also explored methodologies for making use of context and modeling emotion evolution in conversations. My work was also applied in healthcare, including autism research, for studying non-typical emotional expressions. 

During my PhD, I interned at Microsoft Research, where I focused on machine learning approaches, particularly discriminative models, for dialog state tracking for spoken dialog systems.

For more information about my work, please see my publications page. You can also contact me at