Research Assistant Professor of Industrial and Systems Engineering
- 2016, Doctoral Degree, Computer Science, University of Texas - Austin
- Master's Degree, Computer Science, University of Texas - Austin
- Bachelor's Degree, Computer Engineering, University of Illinois at Urbana-Champaign
Mayank Kejriwal is a Research Assistant Professor in the Department of Industrial and Systems Engineering, and a Research Lead at the USC Information Sciences Institute. His research has been, or is currently, funded by programs such as DARPA LORELEI, CauseEx, MEMEX (covered in the press by 60 minutes, Forbes, Scientific American, WSJ, BBC, Wired and several others for its success in spawning real-world systems for tackling human trafficking), AIDA and D3M projects. Prior to joining ISI in 2016, he obtained his Ph.D. from the University of Texas at Austin. His dissertation, titled "Populating a Linked Data Entity Name System", was awarded the Best Dissertation Award by the Semantic Web Science Association in 2017. He is also the author of "Domain-specific Knowledge Graph Construction" (Springer), and has published across various sub-areas of Artificial Intelligence, including Semantic Web, social media analytics, knowledge graphs and natural language processing. He is a passionate advocate of using Artificial Intelligence technology for social good, and regularly collaborates with domain-experts to build such systems. He has given talks and tutorials in international academic and industrial venues, most recently serving as a roundtable speaker and participant (on using AI for fighting child trafficking) at the Concordia Summit that was co-held with the UN General Assembly in New York City in September, 2019. The myDIG system, which he co-built and co-authored and that was a product of the MEMEX program, was nominated for a Best Demonstration award at the prestigious AAAI conference in 2018.
Dr. Kejriwal's research focuses on knowledge graphs (KG), an exciting area of Artificial Intelligence and data analytics research that has found widespread applications in industry (including in e-commerce giants like Amazon, and search providers like Google), academia (health informatics and social sciences) and for social causes (fighting human trafficking and mobilizing resources in the aftermath of crises). Simply put, knowledge graphs are a means to getting a machine to retain and 'understand' knowledge, rather than just raw data. Today, we live in an era when the World Wide Web provides us with an ever-expanding repository of data, yet we are still far from building machines that can process and understand this data in the way that domain experts (or in many cases, ordinary humans) can. Dr. Kejriwal has built and deployed knowledge graph-based systems that have been used by law enforcement and other subject matter experts to fight human trafficking, in addition to tackling other important domains like e-commerce and natural disaster response. Dr. Kejriwal draws on interdisciplinary research inspired by multiple communities in AI and data science, including human-computer interaction, social media, computational social science and Web sciences. His work has been funded both by DARPA and by private endowments. His research has been published in top AI venues such as AAAI (nominated for Best Demo), the International Semantic Web Conference (ISWC), ASONAM, ICDM, IEEE Computer and IEEE Intelligent Systems. He is also the co-author of an upcoming graduate-level textbook on knowledge graphs, to be published later this year by MIT Press. Currently, he is a Principal Investigator on ISI's funded effort under the DARPA SAIL-ON (Science of Artificial Intelligence and Learning for Open-world Novelty) program and a co-PI on ISI's funded effort under the DARPA Machine Common Sense program.