Alexey Tregubov

• Ph.D.
• University of Southern California

As part of the DARPA SocialSim challenge, we address the problem of predicting behavioral phenomena including information spread involving hundreds of thousands of users across three major linked social networks: Twitter, Reddit and GitHub. Our approach develops a framework for data-driven agent simulation that begins with a discrete-event simulati...

Agent-based simulations of social media platforms often need to be run for many repetitions at large scale. Often, researchers must compromise between available computational resources (memory, run-time), the scale of the simulation, and the quality of its predictions.

Simulating and predicting planetary-scale techno-social systems poses heavy computational and modeling challenges. The DARPA SocialSim program set the challenge to model the evolution of GitHub, a large collaborative software-development ecosystem, using massive multi-agent simulations. We describe our best performing models and our agent-based sim...

Simulating and predicting planetary-scale techno-social systems poses heavy computational and modeling challenges. The DARPA SocialSim program set the challenge to model the evolution of GitHub, a large collaborative software-development ecosystem, using massive multi-agent simulations. We describe our best performing models and our agent-based sim...

In many domains, high-resolution agent-based simulations require experiments with a large number (tens or hundreds of millions) of computationally complex agents. Such large-scale experiments are usually run for efficiency on high-performance computers or clusters, and therefore agent-based simulation frameworks must support parallel distributed co...

In many domains, high-resolution agent-based simulations require experiments with a large number (tens or hundreds of millions) of computationally complex agents. Such large-scale experiments are usually run for efficiency on high-performance computers or clusters, and therefore agent-based simulation frameworks must support parallel distributed co...

It has been observed that multitasking can cause inefficient (or unproductive) work. Modern lean and agile practices in software engineering processes also acknowledge the problem and attempt to eliminate waste by limiting work in progress and using better team organization and work scheduling techniques. Existing research has studied multitasking...

Software developers often work on multiple projects and tasks throughout a work day, which may affect their productivity and quality of work. Knowing how working on several projects at a time affects productivity can improve cost and schedule estimations. It also can provide additional insights for better work scheduling and the development process...

While Lean practices are common across many fields and domains today, adaptation of Lean in system engineering began not so long ago. Value-driven processes with minimum waste are especially important in system of systems environments. In this paper, we discuss how system of systems engineering (SoSE) processes differ from single system development...

Systems engineering processes for evolving systems of systems (SoS) are often software-driven and software-intensive. At the same time, SoS have multiple levels of abstraction that correspond to the various levels in the SoS hierarchy where these SoS engineering processes take place. Multiple levels of management make it difficult to capture the ac...

Managing the evolution of independent or loosely coupled systems of systems (SoS) is difficult. Much of the difficulty resides in the ways that elements are combined to make up the SoS and how those elements interface. The Systems Engineering Research Center has been studying how new governance mechanisms drawn from agile, lean and other adaptive a...