• I am an Assistant Professor in the Department of Computer Science at Stony Brook University, leading the SeeMoRe research group. Before joining Stony Brook, I was a postdoctoral researcher in the Computer and Information Science department at the University of Pennsylvania. I received my Ph.D. in Computer Science at the University of California, Santa Barbara and my M.S. and B.S. in Computer Engineering at the Iran University of Science and Technology. My research mainly lies at the intersection of data management and distributed systems, focusing on distributed transaction processing, consensus protocols, and blockchains.

Our research aims to bridge large-scale data management and distributed fault-tolerant systems in the presence of untrustworthy infrastructures. Our long-term goal is to build a complete ecosystem that efficiently manages large-scale data on distributed untrusted infrastructures. Since the current data management systems are mainly built for trusted infrastructures, a significant redesign and reconsideration of the fundamentals and principles of distributed data management are needed. To realize this vision, we study the fundamental distributed data management functionalities, such as transaction processing and consensus. Specifically, the focus of our research, both in my dissertation research [5] and subsequent work, has been on four main directions and associated challenges as follows.
• First, understanding the role of consneuss protoocls and designing effienct consneuss protocols suitable for large-scale data management processing systems [6][17][21][22][23][30] (Thrust 1).
• Second, designing database-enabled techniques to address performance and scalability requirements of managing large-scale data in untrusted infrastructures [2][3][10][12][19][20] (Thrust 2).
• Third, leveraging privacy and cryptography techniques to support confidentiality and verifiability in the context of cooperative data management [1][9][13][14][31] (Thrust 3).
• Fourth, addressing the adaptivity requirement of large-scale systems in all infrastructure, transaction processing, and consensus layers by relying on resource desegregation and machine learning approaches [15][16][18][24][26][28][29] (Thrust 4).

The Figure presents a summary of our research. Next, we discuss the four directions and show how our research addresses them in different systems. Other than the main research papers and software systems, the figure also categorizes our conference tutorials [7][11][8][21][25], and published book [27].