I lead the Apple Knowledge Platform ML team.Previously, I was a Principal Researcher in the Data Systems Group at Microsoft Research (MSR). I specialize in the systems aspects of database management and big data analytics platforms. My current research interests include: Knowledge Graphs, ML-based (or learned) indexing techniques in database systems, cloud-based big data analytics services, next-gen virtualization (Docker & Kubernetes), and performance benchmarking. I led several collaborations with the Azure SQL Hyperscale & Synapse Analytics teams to bring research ideas to production focusing on specific price/performance improvements.I am also leading MSR's collaborative efforts, with MIT and Intel, on applications of ML to enhance systems, including database systems. We envision future systems would be able to "learn" from the query workloads and data distributions to adapt their behavior to that specific workload and data set, thus better meeting the changing demands of customers. We call such systems, Instance Optimized Systems. I am leading fundamental research in this area, starting with the design of ML-enhanced algorithms and data structures that can be used in practical scenarios. One of my recent projects has been the design and implementation of ALEX which is an ML-enhanced range index, similar in functionality to a B+Tree, but is up to 4X faster and 2000X more compact than a B+Tree. Our implementation is also a near drop-in replacement for C++ Standard Template Library’s ordered indexes (std::map or std::multimap). You can learn more about ALEX in our SIGMOD 2020 paper (https://lnkd.in/gEGXXri) and our extended technical report (https://lnkd.in/gwp7WRu). We have made the ALEX source code available on Github (https://lnkd.in/gSQte_7). Before MSR, I was a Research Staff Member at the IBM Almaden Research Center. I was co-leading various efforts focused on resource provisioning, scheduling, cognitive computing, big data storage, and next generation platforms. My research ideas have been commercialized in IBM Big SQL, a SQL-on-Hadoop platform, and in IBM General Parallel File System (GPFS), a highly scalable, distributed file system.Before IBM, I was a member of the Database Research Group at the University of Waterloo, Canada, where I received a PhD and a Masters in Computer Science. My past research focused on improving the performance, availability, and fault tolerance of database systems using virtual machines. Google Scholar Profile: https://scholar.google.com/citations?user=NKYtfsYAAAAJ&hl=en