Resume-aware faculty matching

Find professors who actually fit you

Upload your resume. Four AI agents analyze your background, rank the faculty who fit, inspect their recent research, and help you draft outreach — grounded in their actual work, not templates.

Free to startNo credit cardCancel anytime
Top matches Balanced preset
Dr. Sarah Chen
Stanford · Interpretability · NLP
91
Dr. Marcus Holloway
MIT · Robotics · RL
84
Dr. Aisha Okonkwo
CMU · Fairness · HCI
82
Nova · Professor Researcher · re-ranking top 20…
Saman Zonouz

Saman Zonouz

Verified

Georgia Institute of Technology · Computer Science

Active 2006–2024

h-index27
Citations3.6k
Papers14649 last 5y
Funding$2.3M1 active
See your match with Saman Zonouz — sign in to PhdFit.Sign in

Research topics

  • Computer Science
  • Computer Security
  • Engineering
  • Electrical engineering
  • Computer network

Selected publications

  • Man‐in‐the‐middle attacks and defence in a power system cyber‐physical testbed

    IET Cyber-Physical Systems Theory & Applications · 2021 · 116 citations

    Senior authorCorresponding
    • Computer Security
    • Computer Science
    • Computer Security

    Abstract Man‐in‐The‐Middle (MiTM) attacks present numerous threats to a smart grid. In a MiTM attack, an intruder embeds itself within a conversation between two devices to either eavesdrop or impersonate one of the devices, making it appear to be a normal exchange of information. Thus, the intruder can perform false data injection (FDI) and false command injection (FCI) attacks that can compromise power system operations, such as state estimation, economic dispatch, and automatic generation control (AGC). Very few researchers have focused on MiTM methods that are difficult to detect within a smart grid. To address this, we are designing and implementing multi‐stage MiTM intrusions in an emulation‐based cyber‐physical power system testbed against a large‐scale synthetic grid model to demonstrate how such attacks can cause physical contingencies such as misguided operation and false measurements. MiTM intrusions create FCI, FDI, and replay attacks in this synthetic power grid. This work enables stakeholders to defend against these stealthy attacks, and we present detection mechanisms that are developed using multiple alerts from intrusion detection systems and network monitoring tools. Our contribution will enable other smart grid security researchers and industry to develop further detection mechanisms for inconspicuous MiTM attacks.

Recent grants

Frequent coauthors

  • Resume-aware match score
  • Save to shortlist
  • AI-drafted outreach

See your match with Saman Zonouz

PhdFit ranks faculty by your research interests, methods, and publications — grounded in their actual work, not templates.

  • Free to start
  • No credit card
  • 30-second signup