The Bridge - Issue 2, 2022 - 31

Graduate Research SP
Naznin Akter
Kappa Delta Chapter
Florida International University, Ph.D. Candidate in Electrical Engineering
RESEARCH TOPIC
Novel Materials and Devices for THz Detection and Emission
Technological advances necessitate the use of previously unused and unregulated bandwidth to set a new standard for the
highest data rates. To reach a high data transfer rate, it requires a wider frequency range and larger bandwidth. As a result,
the THz spectrum (0.1-10 THz) has emerged as the next frontier of wireless communication for beyond 5G technologies.
My research focused on investigating THz waves-plasmon interactions in novel field effect (FET) that could be used as a THz
detector at room and cryogenic temperatures, with high responsivity, low noise, tunability, compact size, faster response time,
and lower cost. In comparison to traditional table-top bulky and costly THz detector devices, these detector devices would be
the best candidate
for future THz
on-chip applications.
Furthermore, the
same devices are
expected to act as
THz emitters under
right biasing condition.
Left to right: Image-1: Working with THz-TDS setup. Image-2: Working with THz-BWO setup.Image-3: Working in cleanroom with EBL process.
LEARN MORE
https://scholar.google.com/citations?user=btGhWQMAAAAJ&hl=en&oi=ao
Md Razuan Hossain
Gamma Tau
University of Mississippi, Ph.D. Student in Electrical and Computer Engineering
RESEARCH TOPIC
Neuromorphic Computing
Reservoir Computing (RC) is a highly efficient machine learning algorithm specially suited for processing temporal datasets. RC
systems extract features from input by projecting them into a high-dimensional space. A major advantage of the RC framework
is that it only requires the readout layer to be trained which significantly reduces the training cost for complex temporal data. In
recent years, memristors have become extremely popular in neuromorphic applications due to their attractive analogy to biological
synapses. Alamethicin-doped, synthetic biomembrane can emulate key synaptic functions due to its volatile memristive property
which can enable learning and computation.
In contrast to its solid-state counterparts, this twoterminal
biomolecular memristor features a similar
structure, switching mechanism, and ionic transport
modality as biological synapses while consuming
considerably lower power. Our goal is to develop a
biomolecular memristor-based reservoir system to
solve tasks such as classification and time-series
analysis in a simulation-based environment.
Image Left: " MNIST classification " - this photo shows that the biomolecular memristors have been
doing MNIST classification. Image Right: " Reservoir Computing " - it describes the architecture of our
reservoir to solve classification and dynamic problem
LEARN MORE
https://scholar.google.com/citations?user=xKb9n6oAAAAJ&hl=en
CONTACT
https://www.linkedin.com/in/md-razuan-hossain-527ab7b1/
CONTACT
https://www.linkedin.com/in/nazninpmp/
TLIGHT
HKN.ORG
31
https://scholar.google.com/citations?user=btGhWQMAAAAJ&hl=en&oi=ao https://www.linkedin.com/in/nazninpmp/ https://scholar.google.com/citations?user=xKb9n6oAAAAJ&hl=en https://www.linkedin.com/in/md-razuan-hossain-527ab7b1/ https://hkn.ieee.org/

The Bridge - Issue 2, 2022

Table of Contents for the Digital Edition of The Bridge - Issue 2, 2022

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The Bridge - Issue 2, 2022 - Cover1
The Bridge - Issue 2, 2022 - Cover2
The Bridge - Issue 2, 2022 - page
The Bridge - Issue 2, 2022 - 4
The Bridge - Issue 2, 2022 - 5
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The Bridge - Issue 2, 2022 - Cover3
The Bridge - Issue 2, 2022 - Cover4
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