Mehrdad Nojoumian's Research
Invited Talk


Selected Projects
1. Human-Inspired Trust Controller: Real-Time Trust Measurement in Human-Autonomous Vehicle Interactions. Most of the recent studies indicate that people have negative attitudes to utilize autonomous systems. These interesting discoveries highlight the necessity and urgency of conducting research to better understand the evolution of trust between humans and growing autonomous technologies such as self-driving cars and care-giving robots. In this project, we explore how to establish, sustain and rebuild - in the case of incidental failures - trust between humans and autonomous systems. Furthermore, we utilize human-inspired trust modeling to understand human perception of (un)trustworthy actions in autonomous systems so that adversarial activities of intelligent adversaries can be detected as early as possible. IRBNET ID #: 1187756-1.
2. Human-Robot Teaming: Trust, Satisfaction and Frustration Measurements in Human-Robot Interaction. In this project, we investigate the impacts of assistant-robot operation on human trust, satisfaction, and frustration through self-reported human metrics. We study how proper operations lead to human trust escalation, and consequently, satisfiable interactions with robotic systems. We also explore how the task performance of the human-robot team varies as human level of trust, satisfaction, and frustration fluctuate. We are mainly interested in care-giving robotic assistants that help veterans, disabled and elderly people in their daily life tasks. IRBNET ID #: 1187761-1.
3. Secure Multiparty Computation: Fast Implementation of Secure MPC and Its Applications. In this project, we focus on design and fast implementation of secure distributed computing protocols in resource-constrained devices that are utilized by humans or autonomous systems. We efficiently utilize devices such as cell phones, smart watches or tablets, and design innovative implementation solutions that process private input data securely, quickly and accurately. Parallel processing, partial machine-language implementation, dynamic programming, and self-healing techniques are utilized to implement secure multiparty computation protocols, and consequently, produce software techniques as well as libraries for efficient execution of constant-round MPC protocols on these resource-constrained platforms.
4. Privacy-Preserving Market Mechanisms: From Sealed-Bid Auctions to Strategic Negotiations. The growth of e-technology and intense competition in markets and economic contexts have created a remarkable opportunity to remodel some of the existing market mechanisms and, as a result, define a new set of fascinating applications for cryptographic tools. As privacy, lack of transparency and the resulting risk of economic fraud are major concerns in many markets, in this project, we transform a specific class of market mechanisms into a new privacy-preserving framework under the following two conditions: these protocols can be better utilized in the financial sectors if the privacy of certain parameters are preserved, and the elements and structures of these protocols are aligned with the characteristics of the utilized cryptographic tools.
5. Reputation-Based Cryptocurrency Mining Paradigm and Its Game-Theoretical Analysis. Verification of transactions in digital currencies is very resource intensive, therefore, miners form mining pools to verify each block of transactions in return of a reward where only the first mining pool that accomplishes the process will be rewarded. This leads to intense competitions among miners, and consequently, dishonest mining strategies, e.g., block withholding attack or selfish mining. As such, it is necessary to regulate the mining process to make the miners accountable for dishonest behaviors. We therefore design a new reputation-based mining paradigm in which the miners not only are incentivized to conduct honest mining but also disincentivized to commit to any malicious activities against other mining pools.

Current Students

Arash Golchubian (PhD), 2018-Now.

Mohammad Ghaseminejad (PhD), 2017-Now.

Corey Park (MSc), 2017-Now.

Iker Gonzalez Moya (MSc), 2017-Now.

Ramiro Alvarez (MSc), 2016-Now.

Ahsan Sanaullah (UG), 2018-Now.

Luiza Menezes (UG), 2017.

Former Students

Shervin Shahrdar (MSc), 2018.
Currently at JDI Data Corporation.

Arash Golchubian (MSc), 2017.
Currently at Motorola and a PhD Student.

Sriram Krishnamachari (MSc), 2013.
Currently at Visteon Corporation.

  • My Erdös number is 2 through (M. Nojoumian -> D. R. Stinson -> P. Erdös).
  • You can see an incomplete list of my publications from the Google Scholar.