Expression of interest PhD Positions in Edge Computing

Dear all,

we are looking for bright and highly motivated student for one PhD position
at the Department of Information Engineering at the University of Pisa.

The position is funded within the framework of the "Crosslab: Innovation
for Industry 4.0" project.
The research activities will be carried out in the "Cloud Computing, Big
Data & Cybersecurity" laboratory (
https://crosslab.dii.unipi.it/cloud-computing-big-data-cybersecurity-lab).

A short description of the research topic can be found below.

Interested people are requested to send an expression of interest by
submitting a curriculum vitae, a one-page research statement showing
motivation and understanding of the topic of the position, and the official
Transcript of Record. The expression of interest must be sent by email to
Carlo Vallati at carlo.vallati-K+ph/[email protected] with the reference [PhD expression
of interest] in the subject of the email. Applications will be reviewed
continuously until 5th July 2022.

The starting date of the PhD position is Fall 2022. The duration of the PhD
is three years. The compensation is a standard Italian Ph.D. student fare,
about 1150 Euro/month net.

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Edge Computing 2.0: Efficient Deep Learning at the Edge
================================================

Abstract: Deep neural networks (DNNs) have achieved unprecedented success
in the field of artificial intelligence (AI), including computer vision,
natural language processing, and speech recognition. However, their
superior performance comes at the considerable cost of computational
complexity, which greatly hinders their applications in many
resource-constrained devices, such as Edge computing nodes and Internet of
Things (IoT) devices. Therefore, methods and techniques that can lift the
efficiency bottleneck while preserving the high accuracy of DNNs are in
great demand to enable numerous edge AI applications.

The proposed research plan involves the analysis and identification of the
challenges related to DNNs for time series prediction both at training
time, on the GPU-enabled resource-constrained devices, and at inference
time, on microcontrollers, leveraging available open-source software such
as Tensorflow and Pytorch. The final goal of the research activity will be
the definition, design, implementation, and testing of novel algorithms to
improve the efficiency of DNNs on the edge and on
IoT devices, on real-case scenarios.

Reference contact: Carlo Vallati, email: carlo.vallati-K+ph/[email protected]

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Carlo Vallati, PhD
Associate Professor
Computer Networking Group
Department of Information Engineering
University of Pisa
Via Diotisalvi 2, 56122 Pisa - Italy
Ph. : (+39) 050-2217.572 (direct) .599 (switch)
Fax : (+39) 050-2217.600
Skype: warner83
E-mail: [email protected]://www.iet.unipi.it/c.vallati/

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