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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
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<a class="navbar-brand" href="#">PERFAIL 2025</a>
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<li class="nav-item">
<a class="nav-link" href="#section-intro">About</a>
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<a class="nav-link" href="#section-cfp">Call for Papers</a>
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<a class="nav-link" href="#section-registration">Register</a>
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<a class="nav-link" href="#section-program">Technical Program</a>
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<h1>PerFail 2025</h1>
<p class="lead">Fourth International Workshop on Negative Results in Pervasive Computing</p>
<div class="event-date">
<span>March, 2025</span>
</div>
<p class="lead">Co-located with <a href="https://www.percom.org/" target="_blank">IEEE PerCom 2025</a> in Washington DC, USA
</p>
<p class="lead quote">
“Learn from the mistakes of others. You can’t live long enough to make them all
yourself.” - Eleanor Roosevelt
</p>
</div>
</div>
<!-- .Jumbotron-->
<section id="section-intro" class="section-wrapper about-event">
<div class="container">
<div class="row">
<div class="col-md-12">
<div class="section-title">
<h1>ABOUT</h1>
</div>
</div>
</div>
<div class="row">
<!-- <div class="col-md-8">-->
<p class="lead text-block">
Not all research leads to fruitful results, trying new ways or methods may surpass the state of
the art, but sometimes the hypothesis is not proven or the improvement is insignificant. But
failure to succeed is not failure to progress and this workshop aims to create a platform for
sharing insights, experiences, and lessons learned when conducting research in the area of
pervasive computing.
</p>
<p class="lead text-block">
While the direct outcome of negative results might not contribute much to the field, the wisdom
of hindsight could be a contribution itself, such that other researchers could avoid falling
into similar pitfalls. We consider negative results to be studies that are run correctly (in the
light of the current state of the art) and in good practice, but fail in terms of proving of the
hypothesis or come up with no significance. The “badness” of the work can also come out as a
properly but unfittingly designed data collection, or (non-trivial) lapses of hindsight
especially in measurement studies.
</p>
<p class="lead text-block">
We took the insights and discussion from last year and wrote a paper about the collected
information. You can read the published manuscript in IEEE Pervasive Computitng <a
href="https://ieeexplore.ieee.org/document/10148650" target="_blank">here</a>.
</p>
<p class="lead text-block">
PerFail also has been featured in the Nature feature article "Illuminating 'the ugly side of science': fresh incentives for reporting negative results".
You can read the article <a href="https://www.nature.com/articles/d41586-024-01389-7" target="_blank">here</a>.
</p>
</div>
</div>
</section>
<!-- .about-event -->
<section id="section-cfp" class="section-wrapper cfp gray-bg">
<div class="container">
<div class="row">
<div class="col-md-12">
<div class="section-title">
<h1>CALL FOR PAPERS</h1>
</div>
</div>
</div>
<div class="row">
<!-- <div class="col-md-8">-->
<p class="lead text-block">
The papers of this workshop should highlight lessons learned from the negative results. The main
outcome of the workshop is to share experiences so that others avoid the pitfalls that the
community generally overlooks in the final accepted publications. All areas of <b>pervasive
computing</b>, <b>networking</b> and <b>systems research</b> are considered. While we take a
very broad view of “negative results”, submissions based on opinions and non-fundamental
circumstances (e.g. coding errors and “bugs”) are not in scope of the workshop as they do not
indicate if the approach (or hypothesis) was bad.
</p>
<p class="lead">
The main topics of interests include (but are not limited to):
</p>
<ol>
<li>Studies with unconvincing results which could not be verified (e.g. due to lack of datasets)
</li>
<li>Underperforming experiments due to oversights in system design, inadequate/misconfigured
infrastructure, etc.</li>
<li>Research studies with setbacks resulting in lessons learnt and acquired hindsights (e.g.
hypothesis with too limiting or too broad assumptions)</li>
<li>Unconventional, abnormal, or controversial results that contradict expectations of the
community</li>
<li>Unexpected problems affecting publications, e.g. ethical concerns, institutional policy
breaches, etc.</li>
<li>“Non-publishable” or “hard-to-publish” side-outcomes of the study, e.g . mis-trials of
experiment methodology/design, preparations for proof-of-correctness of results, etc.</li>
</ol>
<p class="lead text-block">
We also welcome submissions from experienced researchers that recounts post-mortem of
experiments or research directions they have failed in the past (e.g. in a story-based format).
With this workshop, our aim is to normalize the negative outcomes and inherent failures while
conducting research in pervasive computing, systems and networking, and provide a complementary
view to all the success stories in these fields.
</p>
</div>
<div class="row" style="padding-top: 2em">
<div class="section-title">
<h2><b>Important Dates*</b></h2>
</div>
<p class="lead">
<b>Paper Submission</b>: <s>November 17</s> December 1, 2024 (extended) <br>
<b>Author Notification</b>: <s>January 8</s> January 10, 2025 (extended) <br>
<b>Camera-ready Due</b>: February 2, 2025 <br>
<b>Workshop Date</b>: March, 2025 <br>
</p>
<p class="lead">* All dates are AoE (check it <a href="https://time.is/Anywhere_on_Earth" target="_blank">here</a>).</p>
</div>
</div>
</section>
<!-- .cfp-event -->
<section id="section-submission" class="section-wrapper about-event">
<div class="container">
<div class="row">
<div class="col-md-12">
<div class="section-title">
<h1>SUBMISSION GUIDELINES</h1>
</div>
</div>
</div>
<div class="row">
<!-- <div class="col-md-8">-->
<p class="lead text-block">
Regular papers should present novel perspectives within the scope of the workshop: negative
results, lessons learned, and other fruitful “failure” stories. Papers must be in PDF format and
contain 6 pages maximum (including references).
Papers should contain names and affiliations of the authors (not blinded). All papers must be
typeset
in double-column IEEE format using 10pt fonts on US letter paper, with all fonts embedded.
Submissions must be made via EasyChair. The IEEE LaTeX and Microsoft Word templates, as well as
related information, can be found at the IEEE Computer Society <a
href="https://www.ieee.org/conferences/publishing/templates.html"
target="_blank">website</a>.
</p>
<p class="lead text-block">
PerFail will be held in conjunction with IEEE Percom 2025. All accepted papers will be included
in the Percom workshops proceedings and included and indexed in the IEEE digital library Xplore.
At least one author will be required to have a full registration in the Percom 2025 conference
and present the paper during the workshop <b>in person</b>. There will be no
workshop-only registration.
</p>
<p class="lead">
<b>Submission link:</b> <a href="https://easychair.org/my/conference?conf=percom2025" target="_blank">here</a>
</p>
</div>
</div>
</section>
<section id="section-registration" class="section-wrapper registration gray-bg">
<div class="container">
<div class="row">
<div class="col-md-12">
<div class="section-title">
<h1>REGISTRATION</h1>
</div>
</div>
</div>
<div class="row">
<p class="lead text-block">
<b>Each accepted workshop paper requires a full PerCom registration (no registration is
available for workshops only).</b>
Otherwise, the paper will be withdrawn from publication.
The authors of all accepted papers must guarantee that their paper will be presented at the
workshop.
Papers not presented at the workshop will be considered as a "<b>no-show</b>" and it will <b>not
be included in the proceedings</b>.
</p>
<p class="lead">
<b>Registration link:</b> <a href="http://www.percom.org/registration/" target="_blank">here</a>
</p>
</div>
</div>
</section>
</div>
</section>
<section id="section-program" class="section-wrapper about-event">
<div class="container">
<div class="row">
<div class="col-md-12">
<div class="section-title">
<h1>TECHNICAL PROGRAM</h1>
</div>
</div>
</div>
<div class="row">
<div class="time col-sm-2">08:40 - 08:45</div>
<div class="agenda-point col-sm-10">Opening Remarks</div>
</div>
<div class="row">
<div class="time col-sm-2">08:45 - 09:35</div>
<div class="agenda-point col-sm-10">Keynote: <span class="agenda-title"*>Failing Without Being a Failure</span></div>
<figure class="thumbnail col-sm-4">
<a href="https://www.uni-due.de/es/en/en_gregor_schiele" target="_blank">
<img src="img/schiele.jpg" width="100%" class="img-responsive" alt="Image">
</a>
</figure>
<div class="col-sm-8">
<div class="speaker">
Prof. Dr. Gregor Schiele (University of Duisburg-Essen, Germany)
</div>
<p class="lead" align="justify">
Dr. Gregor Schiele is professor for embedded systems and leads since november 2014 the Intelligent Embedded Systems group at the University Duisburg-Essen at the campus Duisburg.
Before that he was working from 2012 to 2014 at the Insight Centre for Data Analytics and the Digital Enterprise Research Institute (DERI) as well as at the National University of Ireland, Galway.
From 2006 to 2012 he was working at the department of Prof. Dr. Christian Becker at the University Mannheim.
He wrote his doctorate 2007 at the University Stuttgart at the department of Prof. Dr. Kurt Rothermel.
</p>
</div>
</div>
<div class="row">
<div class="time col-sm-2">09:35 - 10:00</div>
<div class="agenda-point col-sm-10">Paper Presentations</div>
<div class="col-sm-4">
<img class="pubs_img" src="papers/how.png" style="width: 100%">
</div>
<div class="paper-title col-sm-8">
<div class="pubs_title">
How to Minimize the Impact of Sociopolitical Factors on the Implementation of Pervasive Computing Projects
</div>
<br>
<span>
<b style="text-decoration: underline">Authors:</b>
Mirosław Hajder, Mateusz Liput, Piotr Hajder, Lucyna Hajder, Mateusz Mojżeszko, Robert Rogólski and Łukasz Kiszkowiak
</span>
<div class="abstract">
<a class="btn btn-primary" data-bs-toggle="collapse" href="#collapsePaper4"
role="button" aria-expanded="false" aria-controls="collapseExample">
Read Abstract
</a>
<div class="collapse" id="collapsePaper4">
<div class="abstract card card-body">
The article discusses the influence of socio-political factors on the implementation of research projects in the area of pervasive computing, with particular emphasis on the instability of the client's behavior.
The authors, based on their own experience, present the negative effects of changes in the client's expectations during the implementation of the project, emphasizing their impact on scientific research.
They point to lobbying activities and financing problems as the main causes of instability, which leads to difficulties in achieving research goals and implementing innovative solutions.
The authors analyze an example of a project to build a regional computer network in which a change in the client's expectations led to a modification of the design assumptions and the way the network is used.
They indicate that the original concept of the network, based on the equal treatment of all entities, was changed to favor the telecom operators.
The article draws attention to the need for stability and predictability in the implementation of research projects to avoid negative consequences for the development of science and technology.
</div>
</div>
</div>
</div>
</div>
<div class="row">
<div class="time col-sm-2">10:00 - 10:30</div>
<div class="agenda-point col-sm-10">Coffee Break</div>
</div>
<div class="row">
<div class="time col-sm-2">10:30 - 12:10</div>
<div class="agenda-point col-sm-10">Paper Presentations</div>
<div class="col-sm-4">
<img class="pubs_img" src="papers/motivation.png" style="width: 100%">
</div>
<div class="paper-title col-sm-8">
<div class="pubs_title">
Motivation Matters: Challenges and Pit-Falls of Crowdsourced Online Studies
</div>
<br>
<span>
<b style="text-decoration: underline">Authors:</b>
Eileen Becks, Viktor Matkovic and Torben Weis
</span>
<div class="abstract">
<a class="btn btn-primary" data-bs-toggle="collapse" href="#collapsePaper6"
role="button" aria-expanded="false" aria-controls="collapseExample">
Read Abstract
</a>
<div class="collapse" id="collapsePaper6">
<div class="abstract card card-body">
In the field of pervasive computing, conducting studies online via crowdsourcing platforms has become a widely adopted approach due to its advantages in efficiently accessing diverse, and scalable participant samples.
However, not all study designs are equally suited for online implementation without compromising data quality.
This issue became evident during our study on human interaction with AI assistance.
By leveraging Prolific, a crowdsourcing website enabling online studies, we investigated how humans interact with AI-generated hints while solving a pipe maze game.
The study employed ”Poor Man’s Eye Tracking,” combining mouse tracking with obscured vision fields, to monitor participant behaviour.
As our hypothesis, rising diligence in checking AI hints, after the incorrectness of the AI is pointed out, was not confirmed, analysing our data suggests a lack of intrinsic motivation and attention among participants, as reflected in the low effort to verify AI hints.
This falsified the reliability and validity of the collected data.
Our study showed that even a careful pre-selection of participants through a crowdsourced website cannot prevent issues of low motivation and attention.
Moreover, identifying missing motivation or inattentiveness in non-questionnaire components, such as game scenarios, requires additional data collection and analysis, such as mouse tracking, to retrospectively filter invalid datasets.
This paper discusses potential causes and methods to mitigate these issues and proposes strategies to identify and prevent data distortion caused by missing motivation and inattentiveness of subjects.
</div>
</div>
</div>
</div>
<div class="col-sm-4">
<img class="pubs_img" src="papers/assessing.png" style="width: 100%">
</div>
<div class="paper-title col-sm-8">
<span class="pubs_title">
Assessing the Impact of Sampling Irregularity in Time Series Data: Human Activity Recognition As A Case Study
</span>
<br>
<span>
<b style="text-decoration: underline">Authors:</b>
Mengxi Liu, Daniel Geißler, Sizhen Bian, Bo Zhou and Paul Lukowicz
</span>
<div class="abstract">
<a class="btn btn-primary" data-bs-toggle="collapse" href="#collapsePaper2"
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<div class="abstract card card-body">
Human activity recognition (HAR) ideally relies
on data from wearable or environment-instrumented sensors
sampled at regular intervals, enabling standard neural network
models optimized for consistent time-series data as input. How-
ever, real-world sensor data often exhibits irregular sampling due
to, for example, hardware constraints, power-saving measures, or
communication delays, posing challenges for deployed static HAR
models. This study assesses the impact of sampling irregularities
on HAR by simulating irregular data through two methods:
introducing slight inconsistencies in sampling intervals (times-
tamp variations) to mimic sensor jitter, and randomly removing
data points (random dropout) to simulate missing values due
to packet loss or sensor failure. We evaluate both discrete-time
neural networks and continuous-time neural networks, which are
designed to handle continuous-time data, on three public datasets.
We demonstrate that timestamp variations do not significantly
affect the performance of discrete-time neural networks, and the
continuous-time neural network is also ineffective in addressing
the challenges posed by irregular sampling, possibly due to
limitations in modeling complex temporal patterns with missing
data. Our findings underscore the necessity for new models or
approaches that can robustly handle sampling irregularity in
time-series data, like the reading in human activity recognition, paving the way for future research in this domain.
</div>
</div>
</div>
</div>
<div class="col-sm-4">
<img class="pubs_img" src="papers/collaborative.png">
</div>
<div class="paper-title col-sm-8">
<span class="pubs_title">
Collaborative Human Activity Recognition with Passive Inter-Body Electrostatic Field
</span>
<br>
<span>
<b style="text-decoration: underline">Authors:</b>
Sizhen Bian, Vitor Fortes Rey, Siyu Yuan and Paul Lukowicz
</span>
<div class="abstract">
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<div class="abstract card card-body">
The passive body-area electrostatic field has recently been aspiringly explored for wearable motion sensing, harnessing its two thrilling characteristics: full-body motion sensitivity and environmental sensitivity, which potentially empowers human activity recognition both independently and jointly from a single sensing front-end and theoretically brings significant competition against traditional inertial sensor that is incapable in environmental variations sensing.
While most works focus on exploring the electrostatic field of a single body as the target, this work, for the first time, quantitatively evaluates the mutual effect of inter-body electrostatic fields and its contribution to collaborative activity recognition.
A wearable electrostatic field sensing front-end and wrist-worn prototypes are built, and a sixteen-hour, manually annotated dataset is collected, involving an experiment of manipulating objects both independently and collaboratively.
A regression model is finally used to recognize the collaborative activities among users.
Despite the theoretical advantages of the body electrostatic field, the recognition of both single and collaborative activities shows unanticipated less-competitive recognition performance compared with the accelerometer.
However, it is worth mentioning that this novel sensing modality improves the recognition F-score of user collaboration by 16% in the fusion result of the two wearable motion sensing modalities, demonstrating the potential of bringing body electrostatic field as a complementary power-efficient signal for collaborative activity tracking using wearables.
</div>
</div>
</div>
</div>
<div class="col-sm-4">
<img class="pubs_img" src="papers/synthetic.png" style="width: 100%">
</div>
<div class="paper-title col-sm-8">
<span class="pubs_title">
Synthetic Sensory Data Generators: How Much Progress Are We Making?
</span>
<br>
<span>
<b style="text-decoration: underline">Authors:</b>
Renuka Sharma, Abdelwahed Kamis, Sara Khalifa, Dan Bretherton and Brano Kusy
</span>
<div class="abstract">
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<div class="abstract card card-body">
Synthetic Sensory Data Generators (SSDGs)
promise to advance the state of intelligent sensing by providing
labeled training data at almost no cost. Such data can be used
to train real-world sensory classification models without manual
data collection and annotation. In this work, we dissect a promis-
ing paradigm of SSDGs (based on human motion generation) and
reveal a culprit that could hinder future progress. SSDGs are
postfixed with a simple ”calibration” component; to bridge the
distributional gap between real and synthetic data. In this study,
we conduct a critical review of this component and analyses its
contribution to the data synthesis pipeline. Our finding reveals
that, without a proper understanding of the calibration process,
the performance of SSDGs is often overestimated.
We make a number of observations demonstrating that the
performance of current SSDGs heavily depends on the calibration
process. First, generating synthetic data without calibration leads
to poorly performing down stream classifiers (when trained on
synthetic data). Second, while calibration can be unsupervised,
only supervised implementation is usable. This raises the question
of whether SSDGs are better than the relatable few-shot learners
that doesn’t require data synthesis effort. We advocate for fully
unsupervised SSDGs. Third, in some cases, the calibration value
outweighs that of the actual data generation process. Specifically,
our experiments demonstrate that a classifier trained on random
data is equally good to that trained on synthetic data when both
are calibrated! Thus, downstream classification performance isn’t
necessarily a good metric of the generated data quality. Our
findings call for rethinking the current evaluation protocols of
SSDGs.
</div>
</div>
</div>
</div>
</div>
<div class="row">
<div class="time col-sm-2">12:10 - 13:30</div>
<div class="agenda-point col-sm-10">Lunch</div>
</div>
<div class="row">
<div class="time col-sm-2">13:30 - 14:20</div>
<div class="agenda-point col-sm-10">Keynote: <span class="agenda-title">Opening Doors: Reframing Failure as Opportunity</span></div>
<figure class="thumbnail col-sm-4">
<a href="https://www.albany.edu/cehc/faculty/kimberly-cornell" target="_blank">
<img src="img/cornell.jpg" width="100%" class="img-responsive" alt="Image">
</a>
</figure>
<div class="col-sm-8">
<div class="speaker">
Prof. Dr. Kimberly Cornell (University of Albany, New York)
</div>
<p class="lead" align="justify">
Dr. Kimberly A. Cornell is an Assistant Professor at the University at Albany, College of Emergency Preparedness, Homeland Security, and Cybersecurity, where she directs the Cybersecurity & Cryptography Lab.
Her research spans cybersecurity, AI for cybersecurity, quantum computing, and quantum information science, with a focus on leveraging AI to improve security measures.
Dr. Cornell has published on related topics including the security implications of publicly accessible large language models and the applicability of quantum machine learning for climate actions.
An IEEE member and lifetime ACM member, she actively participates in professional organizations and serves on various program committees, contributing to the advancement of cybersecurity and AI research.
</p>
</div>
</div>
<div class="row">
<div class="time col-sm-2">14:20 - 15:10</div>
<div class="agenda-point col-sm-10">Paper Presentations</div>
<div class="col-sm-4">
<img class="pubs_img" src="papers/human.png" style="width: 100%">
</div>
<div class="paper-title col-sm-8">
<span class="pubs_title">
Human Factor as a Security Issue in ISP Networks
</span>
<br>
<span>
<b style="text-decoration: underline">Authors:</b>
Marek Michalski
</span>
<div class="abstract">
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<div class="abstract card card-body">
This paper presents a real case in which a network user noticed a serious security issue and reported it to the ISP. Despite providing detailed information, the problem was not resolved as quickly as technically possible due to human factors. Fortunately, the issue was eventually recognized and resolved. It could have caused significant damage, but it is unknown whether it did. The paper highlights weaknesses in certain procedures that should be improved.
</div>
</div>
</div>
</div>
<div class="col-sm-4">
<img class="pubs_img" src="papers/unforseen.png" style="width: 100%">
</div>
<div class="paper-title col-sm-8">
<div style="position: relative">
<span class="pubs_title">
Unforeseen SILLY Errors in Network Simulations and Visualizations
</span>
<br>
<span>
<b style="text-decoration: underline">Authors:</b>
Koojana Kuladinithi, Yevhenii Shudrenko, Aliyu Makama, Leonard Fisser and Andreas Timm-Giel
</span>
<div class="abstract">
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</a>
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<div class="abstract card card-body">
Factors like incorrect parameterization, unsuitable KPIs, or overlooking key aspects in design and modeling may result in misleading conclusions, time- and resource-waste.
In this paper, we share our genuine experiences from working with bachelor's, master's and PhD students, with the focus on three scenarios where distinct simulation errors commonly occur.
The first two scenarios highlight cases of unjustifiable results, leading to investigations that uncovered "silly errors" in randomization and visualization.
The third scenario, though properly modeled, failed to capture the overall picture needed to reflect real-world outcomes.
By sharing these lessons learned across experience levels, we aim to help students and researchers achieve more credible results while saving valuable time.
</div>
</div>
</div>
</div>
</div>
</div>
<div class="row">
<div class="time col-sm-2">15:10 - 15:35</div>
<div class="agenda-point col-sm-10">Coffee Break</div>
</div>
<div class="row">
<div class="time col-sm-2">15:35 - 16:00</div>
<div class="agenda-point col-sm-10">Paper Presentations</div>
<div class="col-sm-4">
<img class="pubs_img" src="papers/flow.png" style="width: 100%">
</div>
<div class="paper-title col-sm-8">
<div style="position: relative">
<span class="pubs_title">
When Flow Balance Backfires: The Traffic Surge from Reflexive Forwarding in ICNs
</span>
<br>
<span>
<b style="text-decoration: underline">Authors:</b>
Asanga Udugama, Sneha Kulkarni, Thenuka Karunathilake and Anna Förster
</span>
<div class="abstract">
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<div class="abstract card card-body">
Information-Centric Networking (ICN) is a promising networking architecture for the Internet of Things (IoT).
Architectural elements such as in-network caching and content-based security can help communicate the vast amounts of content the IoT is expected to generate.
Since the IoT exhibits several communication patterns distinct from the request-response interactions of ICNs, a draft standard called Reflexive Forwarding was discussed at the IETF.
Reflexive Forwarding (RF) was proposed to address communications in the IoT, among other use cases.
Our investigations, although initially showing promising results, revealed that RF, when used in large-scale IoT deployments, was associated with exponential growth in packet traffic.
This work highlights this problem by examining various aspects of ICN operation when employing RF for communications in the IoT.
</div>
</div>
</div>
</div>
</div>
</div>
<div class="row">
<div class="time col-sm-2">16:00 - 16:50</div>
<div class="agenda-point col-sm-10">Keynote: <span class="agenda-title">Failing Forward: Embracing Negative Results to Drive Innovation</span></div>
<figure class="thumbnail col-sm-4">
<a href="https://www.qut.edu.au/about/our-people/academic-profiles/sara.khalifa" target="_blank">
<img src="img/khalifa.png" width="100%" class="img-responsive" alt="Image">
</a>
</figure>
<div class="col-sm-8">
<div class="speaker">
Prof. Sara Khalifa (Queensland University of Technology, Australia)
</div>
<p class="lead" align="justify">
Sara Khalifa is an associate professor at Queensland University of Technology.
Her research revolves around the broad aspects of ubiquitous sensing and edge computing for Internet of Things (IoT) applications.
Specifically, she focuses on enhancing the energy efficiency of mobile sensing systems and developing lightweight machine learning techniques for resource-constrained sensing devices.
From 2016-2023, she was with CSIRO’s Data61 establishing the foundational research area of “Energy Harvesting Sensing (EHS)” as a core research focus developing a new paradigm for energy-efficient sensing and context recognition, opening up a multitude of new applications, generating IP, and attracting significant funding and commercial interest.
</p>
</div>
</div>
<div class="row">
<div class="time col-sm-2">16:50 - 17:00</div>
<div class="agenda-point col-sm-10">Closing Words</div>
</div>
</section>
<section id="section-committee" class="section-wrapper team gray-bg">
<div class="container">
<div class="row">
<div class="col-md-12">
<div class="section-title">
<h1>COMMITTEE</h1>
</div>
</div>
</div>
<div class="row">
<div class="col-md-12">
<div class="section-title">
<h1>Organizing Committee</h1>
</div>
</div>
</div>
<div class="row justify-content-center">
<div class="col-lg-3 col-md-4">
<figure class="thumbnail">
<a href="https://ellapeltonen.wordpress.com/" target="_blank"><img
src="img/committee/ellaPeltonen.jpg" class="img-responsive" alt="Image"></a>
<figcaption class="caption text-center">
<h3>Ella Peltonen
<small>University of Oulu</small>
</h3>
<ul class="social-links">
<li><a href="https://twitter.com/Ella_Peltonen" target="_blank"><i
class="fa-brands fa-twitter"></i></a></li>
</ul>
</figcaption>
</figure>
</div>
<div class="col-lg-3 col-md-4">
<figure class="thumbnail">
<a href="https://maltejosten.github.io/" target="_blank"><img
src="img/committee/josten.jpg" class="img-responsive" alt="Image"></a>
<figcaption class="caption text-center">
<h3>Malte Josten
<small>University of Duisburg-Essen</small>
</h3>
</figcaption>
</figure>
</div>
<div class="col-lg-3 col-md-4">
<figure class="thumbnail">
<a href="https://www.nitindermohan.com/" target="_blank"><img src="img/committee/nitinder.jpeg"
class="img-responsive" alt="Image"></a>
<figcaption class="caption text-center">
<h3>Nitinder Mohan
<small>TU Delft</small>
</h3>
<ul class="social-links">
<li><a href="https://twitter.com/nitinder_mohan" target="_blank"><i
class="fa-brands fa-twitter"></i></a></li>
</ul>
</figcaption>
</figure>
</div>
<div class="col-lg-3 col-md-4">
<figure class="thumbnail">
<a href="https://vs.uni-due.de/en/person/zdankin/" target="_blank"><img
src="img/committee/Peter-Zdankin.jpeg" class="img-responsive" alt="Image"></a>
<figcaption class="caption text-center">
<h3>Peter Zdankin
<small>University of Duisburg-Essen</small>
</h3>
<ul class="social-links">
<li><a href="https://twitter.com/PZdankin" target="_blank"><i
class="fa-brands fa-twitter"></i></a></li>
</ul>
</figcaption>
</figure>
</div>
<div class="col-lg-3 col-md-4">
<figure class="thumbnail">
<a href="https://tanyashreedhar.github.io/" target="_blank"><img src="img/committee/tanya.jpeg"
class="img-responsive" alt="Image"></a>
<figcaption class="caption text-center">
<h3>Tanya Shreedhar
<small>TU Delft</small>
</h3>
<ul class="social-links">
<li><a href="https://twitter.com/tanyashreedhar" target="_blank"><i
class="fa-brands fa-twitter"></i></a></li>
</ul>
</figcaption>
</figure>
</div>
</div>
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<div class="col-md-12">
<div class="section-title">
<h1>Technical Program Committee</h1>
</div>
</div>
</div>
<div class="row justify-content-center">
<div class="col-lg-3 col-md-4">
<figure class="thumbnail">
<a href="http://homepage.tudelft.nl/8e79t/" target="_blank"><img src="img/committee/ding.jpeg"
class="img-responsive" alt="Image"></a>
<figcaption class="caption text-center">
<h3>Aaron Ding
<small>TU Delft</small>
</h3>
<ul class="social-links">
<li><a href="https://twitter.com/aaronyiding" target="_blank"><i
class="fa-brands fa-twitter"></i></a></li>
</ul>
</figcaption>
</figure>
</div>
<div class="col-lg-3 col-md-4">
<figure class="thumbnail">
<a href="https://www.uni-due.de/es/en/en_erbsloeh.php" target="_blank"><img
src="img/committee/erbsloeh.jpg" class="img-responsive" alt="Image"></a>
<figcaption class="caption text-center">
<h3>Andreas Erbslöh
<small>University of Duisburg-Essen</small>
</h3>
</figcaption>
</figure>
</div>
<div class="col-lg-3 col-md-4">
<figure class="thumbnail">
<a href="https://www.uni-bamberg.de/en/mobi/team/daniela-nicklas/" target="_blank"><img
src="img/committee/nicklas.jpg" class="img-responsive" alt="Image"></a>
<figcaption class="caption text-center">
<h3>Daniela Nicklas
<small>University of Bamberg</small>
</h3>
</figcaption>
</figure>
</div>
<div class="col-lg-3 col-md-4">
<figure class="thumbnail">
<a href="http://ece-research.unm.edu/tsiropoulou/index.html" target="_blank"><img
src="img/committee/tsiropoulou.jpg" class="img-responsive" alt="Image"></a>
<figcaption class="caption text-center">
<h3>Eirini Eleni Tsiropoulou
<small>University of New Mexico</small>
</h3>
<ul class="social-links">
<li><a href="https://twitter.com/Tsiropoulou_EE" target="_blank"><i
class="fa-brands fa-twitter"></i></a></li>
</ul>
</figcaption>
</figure>
</div>
<div class="col-lg-3 col-md-4">
<figure class="thumbnail">
<a href="http://www.cs.ucf.edu/~gsolmaz/" target="_blank"><img src="img/committee/solmaz.jpg"
class="img-responsive" alt="Image"></a>
<figcaption class="caption text-center">
<h3>Gürkan Solmaz
<small>NEC Labs Europe</small>
</h3>
</figcaption>
</figure>
</div>
<div class="col-lg-3 col-md-4">
<figure class="thumbnail">
<a href="https://www.in.tum.de/cm/research-group/joerg-ott/" target="_blank"><img
src="img/committee/ott.jpg" class="img-responsive" alt="Image"></a>
<figcaption class="caption text-center">
<h3>Jörg Ott
<small>Technical University of Munich</small>
</h3>
</figcaption>
</figure>
</div>
<div class="col-lg-3 col-md-4">
<figure class="thumbnail">
<a href="https://www.cl.cam.ac.uk/~jac22/" target="_blank"><img src="img/committee/crowcroft.jpeg"
class="img-responsive" alt="Image"></a>
<figcaption class="caption text-center">
<h3>Jon Crowcroft
<small>University of Cambridge</small>
</h3>
<ul class="social-links">
<li><a href="https://twitter.com/tforcworc" target="_blank"><i
class="fa-brands fa-twitter"></i></a></li>
</ul>
</figcaption>
</figure>
</div>
<div class="col-lg-3 col-md-4">
<figure class="thumbnail">
<a href="https://researchportal.helsinki.fi/en/persons/jussi-kangasharju" target="_blank"><img
src="img/committee/kangasharju.png" class="img-responsive" alt="Image"></a>
<figcaption class="caption text-center">
<h3>Jussi Kangasharju
<small>University of Helsinki</small>
</h3>
<ul class="social-links">
<li><a href="https://twitter.com/kangasharju" target="_blank"><i
class="fa-brands fa-twitter"></i></a></li>
</ul>
</figcaption>
</figure>
</div>
<div class="col-lg-3 col-md-4">
<figure class="thumbnail">
<a href="https://olivergasser.net/" target="_blank"><img src="img/committee/gasser.jpg"
class="img-responsive" alt="Image"></a>
<figcaption class="caption text-center">
<h3>Oliver Gasser
<small>IPinfo</small>
</h3>
</figcaption>
</figure>
</div>
<div class="col-lg-3 col-md-4">
<figure class="thumbnail">
<a href="https://www.cst.cam.ac.uk/people/rk647" target="_blank"><img
src="img/committee/kolcun.jpg" class="img-responsive" alt="Image"></a>
<figcaption class="caption text-center">
<h3>Roman Kolcun
<small>University of Cambridge</small>
</h3>
<ul class="social-links">
<li><a href="https://twitter.com/KolcunRoman" target="_blank"><i
class="fa-brands fa-twitter"></i></a></li>
</ul>
</figcaption>
</figure>
</div>
<div class="col-lg-3 col-md-4">
<figure class="thumbnail">
<a href="https://people.utwente.nl/s.bayhan" target="_blank"><img src="img/committee/bayhan.jpeg"
class="img-responsive" alt="Image"></a>
<figcaption class="caption text-center">
<h3>Suzan Bayhan
<small>University of Twente</small>
</h3>
<ul class="social-links">
<li><a href="https://twitter.com/suzan_bayhan" target="_blank"><i
class="fa-brands fa-twitter"></i></a></li>
</ul>
</figcaption>
</figure>
</div>
<div class="col-lg-3 col-md-4">
<figure class="thumbnail">
<a href="https://www.aalto.fi/en/people/stephan-sigg" target="_blank"><img src="img/committee/sigg.jpg"
class="img-responsive" alt="Image"></a>
<figcaption class="caption text-center">
<h3>Stephan Sigg
<small>Aalto University</small>
</h3>
<ul class="social-links">
<li><a href="https://twitter.com/StephSigg" target="_blank"><i
class="fa-brands fa-twitter"></i></a></li>
</ul>
</figcaption>
</figure>
</div>
<div class="col-lg-3 col-md-4">
<figure class="thumbnail">
<a href="https://www.vs.uni-due.de/" target="_blank"><img src="img/committee/weis.jpg"
class="img-responsive" alt="Image"></a>
<figcaption class="caption text-center">
<h3>Torben Weis
<small>University of Duisburg-Essen</small>
</h3>
</figcaption>
</figure>
</div>
<div class="col-lg-3 col-md-4">
<figure class="thumbnail">
<a href="https://www.cs.ox.ac.uk/people/vadim.safronov/" target="_blank"><img src="img/committee/safronov.jpg"
class="img-responsive" alt="Image"></a>
<figcaption class="caption text-center">
<h3>Vadim Safronov
<small>University of Oxford</small>
</h3>
</figcaption>
</figure>
</div>
</div>
</div>
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<h1>Previous Editions</h1>
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<a href="https://perfail-workshop.github.io/2022/">1st PerFail 2022</a><br>
<a href="https://perfail-workshop.github.io/2023/">2nd PerFail 2023</a><br>
<a href="https://perfail-workshop.github.io/2024/">3rd PerFail 2024</a>
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