Dr. Omid Sadjadi is a Computer Scientist at NIST, where he serves as Technical Lead for NIST Speech Technology Evaluations including the OpenSAT, SRE and LRE. He has been a recipient of the NIST ITL Outstanding Associate of the Year Award for “outstanding contributions based on his expert knowledge of speaker recognition systems that improved the NIST Speaker Recognition Evaluation”, as well as several Exceptional Performance Awards (Systems Plus, Inc) for his work at NIST. He is a Senior Member of the IEEE and has served as a voting member of the NIST OSAC speaker recognition sub-committee since 2018. Prior to joining NIST, he was a Research Staff Member at IBM where he researched and developed audio analytics technologies for IBM Watson®. He was a recipient of a best paper award as well as the IBM Research Travel Grant at IEEE ICASSP-2013, Vancouver, BC. He has authored/co-authored more than 60 papers in the fields of machine learning and human language technology, and is the developer of the Microsoft Research (MSR) Identity Toolbox for speaker recognition.
In 2020, he was the technical lead for the NIST Too-Close for Too-Long (TC4TL) challenge which was organized in collaboration with the MIT PACT in response to the COVID-19 pandemic. Dr. Sadjadi has served on the technical committee of several top-tier speech and machine learning conferences and journal publications in various capacities (area chair, session chair, reviewer, editor). He was a guest editor for the Computer Speech & Language special issue on speaker recognition evaluations, and currently serves as an Associate Editor for the IEEE/ACM Transactions on Audio, Speech, and Language Processing.
He completed his PhD in Electrical Engineering at The University of Texas at Dallas, where he received a Certificate of Academic Achievement in recognition of his outstanding academic performance.