The above figure outlines my recent research endeavors, where I concentrate on leveraging technologies such as blockchains, access control, and machine learning to address an array of challenges necessitating data sharing, privacy, compliance, and smart contract engineering. My primary focus lies in applying these technologies to domains including supply chains; decentralized finance (DeFi); environmental, social, governance (ESG); and responsible AI. I am starting to expand my technology focus to emerging ones like retrieval-augmented generation (RAG) for large-language models (LLMs), fully homomorphic encryption (FHE), zero-knowledge proof (ZKP), multi-party computation (MPC), verifiable credentials (VCs), and decentralized identifiers (DID), particularly to enhance trust in software systems.
The following diagram is an overview of my research up to the end of 2018, where I worked on large-scale data generation, transmission, and processing. I worked on Data Engineering, IoT, Cloud and Distributed Computing, Complex Event Processing, and Data Integration and Assimilation. As a graduate student I worked on Peer-to-Peer (P2P) computing, Content Discovery, Wired and Wireless Sensor Networks, Virtual Sensor Networks, and Secure Communication. My research was centered on the characterization of real-world resources, application, and user behavior in those domains, and use of those characteristics to develop novel solutions that are more efficient, scalable, secure, and apt to real-world systems. I focused on interdisciplinary problems in weather prediction, fleet management, and smart cities.
See my Statement of Research.