Baki Berkay Yilmaz

"Our true mentor in life is science."

— Mustafa Kemal Atatürk

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Portfolio

Baki Berkay
Yilmaz

Assistant Professor · Wayne State University · ECE

I received my Ph.D. in Electrical and Computer Engineering from the Georgia Institute of Technology. I joined Aether Argus Inc. in 2020 as a Lead Signal Processing Engineer and Researcher, and currently serve as an Assistant Professor of Electrical and Computer Engineering at Wayne State University.

My research interests span electromagnetic side-channel analysis, signal processing, hardware security, communications, and machine learning. Our team focuses on enhancing supply chain security through non-intrusive methodologies leveraging EM side-channels.

Education

Georgia Institute of Technology
PhD in Electrical and Computer Engineering
Atlanta, GA
Georgia Institute of Technology
MS in Electrical and Computer Engineering
Atlanta, GA
Koç University
MS in Electrical and Electronics Engineering
Istanbul, Türkiye
Koç University
BS in Electrical and Electronics Engineering
Istanbul, Türkiye
Koç University
BS in Industrial Engineering
Istanbul, Türkiye
Academic Output

Research & Publications

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Best Paper Award, IEEE International Symposium on Hardware Oriented Security and Trust (HOST), 2020.
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Best Paper Nominee, 26th IEEE International Symposium on High-Performance Computer Architecture (HPCA-26), 2020.
★
Recipient of the Scientific and Technological Research Council of Turkey (TUBITAK) Graduate Scholarship.
★
Received the Koç University Graduate Scholarship for Master's studies.
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Awarded a Full Undergraduate Scholarship from Koç University for academic excellence.
Patent · US App. 18/027,517
Method and System to Identify Fabricated Electrical Circuits with Hidden Hardware Modifications
Alenka Zajic, Milos Prvulovic, Baki Berkay Yilmaz, and Ngoc Luong Nguyen
Grant 01
PI
Electromagnetic Side Channel Monitoring Study for Requisition 235390
Fluor Marine Propulsion Corporation — June 2021 – October 2021
Grant 02
co-PI
EMSCALe: Component Decomposition by Leveraging Electromagnetic Side-channels
DARPA, W912CG-23-C-0015 — March 2023 – September 2024
Grant 03
PI
ArEMGuard: Mobile Infrastructure Authentication in Expeditionary Regions via Unintended Electromagnetic Emission Monitoring
DARPA, N66001-23-C-4035 — March 2023 – March 2025
Grant 04
PI
EMAth: ECU Authentication via Electromagnetic Side Channels
DARPA, 140D04-24-C-0026 — January 2024 – January 2026
Grant 05
co-PI
EMSentry — Making Mobile Infrastructure Secure in Expeditionary Regions: An Air-gapped Monitoring Approach Leveraging EM Side-Channels
DARPA, HR0011-24-9-0505 — August 2024 – February 2026
Grant 06
co-PI
MEDAGuard: Medical Device Functionality Shielding against Adverse Effects of Authorized Updates by Leveraging EM Side-Channels
ARPA-H, 140D04-25-9-0014 — July 2025 - July 2027

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Research & Engineering

Selected Projects

01

EM Side-Channel Based System Monitoring and Profiling with Neural Networks

  • Designed and trained neural networks to profile programs on IoT devices by exploiting electromagnetic signals emitted during execution.
  • Detected malware by identifying anomalies in program behavior using EM side-channel data.
  • Achieved non-intrusive classification of circuit components without direct physical access.
  • Collected data using Software-Defined Radios (SDRs) and spectrum analyzers for high-quality signal acquisition.
02

Channel Modelling and Instruction Tracking

  • Developed models to understand and analyze input signals leading to EM emissions during software activity.
  • Constructed instruction-specific EM signal models for different devices.
  • Demonstrated instruction-level tracking of scripts using advanced signal processing techniques.
03

Quantifying Information Leakage Caused by Software Activities

  • Analyzed and quantified potential information leakage from computing devices caused by software activity.
  • Demonstrated correlation between instruction sequence, implementation, and extent of leakage.
  • Established mathematical bounds on information leakage as a theoretical framework for mitigation.
  • Bridged conventional communication systems with covert/side channels to understand security impact.
04

OpenSSL Cryptography Vulnerability Analysis

  • Applied advanced signal-processing techniques to extract sensitive information from EM emissions during OpenSSL signing operations.
  • Identified and disclosed cryptographic vulnerabilities to strengthen resistance to EM side-channel attacks.
  • Proposed countermeasures to mitigate EM-based threats.
05

Compressed Equalization

  • Developed compressed equalization techniques exploiting hidden sparsity in combined channel responses for improved signal reconstruction.
  • Derived error bounds between actual and estimated combined channels.
  • Verified approach with MATLAB simulations for fractionally and time-spaced scenarios.
06

Bounded Component Analysis

  • Developed novel BCA methods to separate dependent and independent sources from instantaneous mixtures.
  • Validated algorithms through MATLAB simulations, achieving effective source separation in real-world scenarios.
Join the Lab

Open Positions

Overview
PhD Positions Available

We are seeking motivated PhD students interested in cutting-edge research at the intersection of hardware security, machine learning, signal processing, and side-channel analysis techniques. Fully-funded positions are available for exceptional candidates.

Research Areas
What You'll Work On
  • Hardware Security & Supply Chain Security
  • Side-Channel Analysis (Electromagnetic, Power, etc.)
  • Machine Learning for Hardware Security
  • Signal Processing for Security Applications
  • Compressive Sensing
Ideal Background
What We're Looking For
  • Degree in ECE, Computer Engineering, or Computer Science
  • Experience in Signal Processing or Machine Learning
  • Background in Hardware Security or Computer Architecture
  • Programming skills in Python, MATLAB, or C/C++
  • Experience with FPGA or embedded systems
  • Hands-on experience with SDRs, Spectrum Analyzers, or Oscilloscopes (highly desirable)
Application
How to Apply

Send the following materials directly via email. Applications are reviewed on a rolling basis.

CV / Resume Transcript Statement of Research Interests
baki@wayne.edu