Dehghanzadeh, Peyman

Peyman Dehghanzadeh

Assistant Professor | College of Engineering and Science: Department of Electrical Engineering and Computer Science

peymand@fit.edu
(321) 674-8425
Olin Engineering OEC 354

Hardware Security, Compute in Memory (CiM), RFIC, Analog IC Design

Personal Overview

Peyman Dehghanzadeh’s research focuses on analog integrated circuit (IC) and radio-frequency integrated circuit (RFIC) design, with emphasis on developing high-performance, energy-efficient, and secure circuit and system solutions. His work spans low-power and wideband analog front-end design, advanced RF architectures for wireless communication, sensing, and biomedical applications, as well as emerging areas such as compute-in-memory architectures and hardware security.

Before joining the �鶹��ýӳ�� as an Assistant Professor in the Department of Electrical and Computer Engineering, Dr. Dehghanzadeh earned his Ph.D. in Electrical Engineering from the University of Florida, where he later continued as a Postdoctoral Researcher with the Nelms Institute for the Connected World. He also brings industry experience from his role as an Analog IC Design Intern at Texas Instruments, where he developed a BCI-tolerant transmitter for noisy environments to improve robustness and performance under challenging conditions.

Educational Background

Postdoctoral Researcher in Electrical and Computer Engineering, University of Florida, Gainesville, FL, 2025.
Ph.D. in Electrical and Computer Engineering, University of Florida, Gainesville, FL, 2024.

Current Courses

ECE3541: Digital State Machines

ECE2112: Circuit Theory 2

ECE2111: Circuit Theory 1

Selected Publications

US Patents:

Multi-bit memory-based physically unclonable function - US Patent App. US20260039485A1,
Look-up table-based in-memory computing system - US Patent App. 18/769,985,
Systems and methods for interfacing natural intelligence with artificial intelligence - US Patent App. 18/916,901,
Apparatus, systems and methods for programmable logic macros - US Patent App. 18/408,267,
Systems and methods for providing distributed batteries in integrated circuits - US Patent App. 18/537,160,

Selected Publications:

DF-PUF: A Dual-Function Programmable Entropy Source for Secure Authentication and Memory Reuse, IEEE Transactions on Circuits and Systems I,
LUNA-CIM: A Programmable Compute-in-Memory Fabric for Neural Network Acceleration, IEEE Transactions on Computers
Look-Up Table based Energy-Efficient Architecture for Neural Accelerators, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems,
MBM PUF: A Multi-Bit Memory-Based Physical Unclonable Function, IEEE Transactions on Circuits and Systems I: Regular Papers,
Fusion Intelligence: A Paradigm for Merging Natural and Artificial Intelligence, IEEE Internet of Things Journal,
A multiport self-interference canceller for wideband SIMO/MIMO-STAR full-duplex arrays, IEEE Transactions on Microwave Theory and Techniques,
On-chip batteries as distributed energy sources in heterogeneous 2.5 D/3D integrated circuits, IEEE Access,
Contact-less integrity verification of microelectronics using near-field EM analysis, IEEE Access,
Non-invasive authentication of mail packages using nuclear quadrupole resonance spectroscopy, Nature, Scientific Reports 13 (1),

Conference Papers:

PROM: Protection against Reverse Engineering Attacks through Programmable Logic Macros International Symposium on Field Programmable Gate Arrays
Pasteables: A Secure On-Body Health Monitoring Platform, IEEE 68th International Midwest Symposium on Circuits and Systems (MWSCAS)
Digitally programmable CMOS feedback for network of coupled electromechanical oscillators, IEEE International Symposium on Circuits and Systems,

Research

Hardware Security: Developing robust techniques to protect integrated circuits against side-channel attacks and reverse engineering.
High-Speed, Low-Power ANN Accelerators: Designing efficient hardware accelerators for artificial neural networks to optimize performance and energy consumption in AI applications.
Compute-in-Memory (CIM): Exploring in-memory computing architectures, to enhance computational efficiency and scalability.
Analog Front-End Design: Creating high-performance analog and mixed-signal front-end circuits for RF and communication systems, prioritizing low power and high precision.

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