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<meta charset="UTF-8" />
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<title>BuzzConf</title>
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<body>
<div class="awesome-bg">
<section id="hero" class="">
<div id="ufo">
<img src="images/ufo.svg" class="ufo" alt="ufo">
</div>
<img src="images/city.png" class="city" alt="City">
<div class="container">
<h1 class="big-text">
<div class="buzzconf">
<img src="images/logo-title.png" class="buzzconf-image" alt="BuzzConf">
</div>
<div class="date">2020</div>
</h1>
<p class="mid-text">
A conference <span>for developers</span>, <span>by developers</span>.<br>
Functional programming, Distributed systems, Embedded systems, Programming languages,
Probabilistic programming, Big data, Profiling & debugging, Artificial intelligence, Machine learning & Deep
learning.
</p>
<div class="small-cta">
<span>27 JULY - 31 JULY</span>
<a href="https://buzzconf2020.eventbrite.com/">RESERVE YOUR SPOT FOR FREE
<svg class="icon icon-right-arrow" aria-hidden="false" role="img">
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<div class="previous-editions">
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Previous editions:
<a href="previous/2019/index.html">BuzzConf 2019</a>
</div>
</div>
<section class="section-padding" id="speaker">
<div class="container">
<h1 class="section-title">Keynote speakers</h1>
<div class="speakers-list justify-content-center">
<div class="speaker">
<a href="">
<div class="avatar">
<img src="./images/speakers/majors.png" alt="Charity Majors" />
</div>
</a>
<h3 class="name">Charity Majors</h3>
<p><a href="https://twitter.com/mipsytipsy/">@mipsytipsy</a></p>
<p class="designation">
Operations and database engineer, and founder and CTO of honeycomb.io, which builds observability for
distributed systems. Co-author of “Database Reliability Engineering” by O’Reilly.
</p>
<p class="sort-bio">
<span>Talk</span>
The Sociotechnical Path to High-Performing Teams (Begins With Observability)
</p>
</div>
<div class="speaker">
<div class="avatar">
<img src="./images/speakers/shah.png" alt="Viral B. Shah" />
</div>
<h3 class="name">Viral B. Shah</h3>
<p><a href="https://twitter.com/Viral_B_Shah">@Viral_B_Shah</a></p>
<p class="designation">
One of the creators of the Julia programming language, co-founder and CEO of Julia Computing an co-author
of the book "Rebooting India".
</p>
<p class="sort-bio">
<span>Talk</span>
Julia - A language for AI and much more
</p>
</div>
<div class="speaker">
<div class="avatar">
<img src="./images/speakers/alvaro.png" alt="Peter Alvaro" />
</div>
<h3 class="name">Peter Alvaro</h3>
<p><a href="https://twitter.com/palvaro/">@palvaro</a></p>
<p class="designation">
Assistant professor and researcher at the University of California, specializing in the intersection of
databases, distributed systems and programming languages.
</p>
<p class="sort-bio">
<span>Talk</span>
What not where: why a blue sky OS?
</p>
</div>
<div class="speaker">
<div class="avatar">
<img src="./images/speakers/siram.png" alt="Aditya Siram" />
</div>
<h3 class="name">Aditya Siram</h3>
<p><a href="https://twitter.com/deech/">@deech</a></p>
<p class="designation">
Scala developer by day, but writes Haskell, Shen, C, Rust and ATS by candlelight. His talk, titled "Nim
nuggets", will be about the Nim programming language.
</p>
<p class="sort-bio">
<span>Talk</span>
What FP Can Learn From Static Introspection
</p>
</div>
<div class="speaker">
<div class="avatar">
<img src="./images/speakers/kurt.png" alt="Will Kurt" />
</div>
<h3 class="name">Will Kurt</h3>
<p><a href="https://twitter.com/willkurt/">@willkurt</a></p>
<p class="designation">
Author of “Bayesian Statistics the Fun Way” and “Get Programming with Haskell”. He is currently the lead
Data Scientist for the pricing and recommendations team at Hopper.
</p>
<p class="sort-bio">
<span>Talk</span>
The Limits of Probability
</p>
</div>
<div class="speaker">
<div class="avatar">
<img src="./images/speakers/rackauckas.png" alt="Chris Rackauckas" />
</div>
<h3 class="name">Chris Rackauckas</h3>
<p><a href="https://twitter.com/ChrisRackauckas">@ChrisRackauckas</a></p>
<p class="designation">
Using Julia, Chris researches Scientific Machine Learning, focusing on how the randomness from scientific
data can be used to uncover the underlying mechanistic structure.
He is the lead developer of
<a href="https://github.com/SciML/DifferentialEquations.jl">DifferentialEquations.jl</a> and
<a href="https://pumas.ai/">pumas.ai</a>.
</p>
<p class="sort-bio">
<span>Talk</span>
How full language differentiability enables scientific machine learning and Scientific Software 2.0
</p>
</div>
<div class="speaker">
<div class="avatar">
<img src="./images/speakers/fernandez.png" alt="Pablo Fernández" />
</div>
<h3 class="name">Pablo Fernandez</h3>
<p><a href="https://twitter.com/fernandezpablo/">@fernandezpablo</a></p>
<p class="designation">
Pablo has been shipping backend and frontend code in about a dozen languages for about 15 years
professionally. He lately has been working on machine learning models, on both large and small scale.
</p>
<p class="sort-bio">
<span>Talk</span>
Machine learning In The Real World
</p>
</div>
<div class="speaker">
<div class="avatar">
<img src="./images/speakers/vmartinez.png" alt="Vanina Martínez" />
</div>
<h3 class="name">María Vanina Martínez</h3>
<!-- <p><a href="https://twitter.com/">@</a></p> -->
<p class="designation">
Vanina is a PhD graduate in Computer Science from the University of Maryland College Park.
Her research
interests include reasoning under uncertainty, inconsistency management in relational databases and
knowledge bases,
defeasible reasoning, and argumentation.
</p>
<p class="sort-bio">
<span>Talk</span>
Symbolic Reasoning to model Sentiment and Knowledge Diffusion in Social Networks
</p>
</div>
<div class="speaker">
<div class="avatar">
<img src="./images/speakers/schouhy.png" alt="Sergio Chouhy" />
</div>
<h3 class="name">Sergio Chouhy</h3>
<!-- <p><a href="https://twitter.com/fernandezpablo/">@fernandezpablo</a></p> -->
<p class="designation">
Sergio is a PhD in Mathematics from University of Buenos Aires and University of Montpellier
who completed his posdoc in pure mathematics at the University of Stuttgart.
He currently works in Data Science & Operation Research at Eryx.
</p>
<p class="sort-bio">
<span>Talk</span>
Implementando Deep Q Learning con Pytorch
</p>
</div>
</div>
</div>
</section>
</div>
<section class="section-padding" id="halls">
<div class="container">
<h1 class="section-title">Location</h1>
<div class="row">
<div class="col-sm-1">
<a href="https://www.youtube.com/watch?v=QK6zEFdvXYw"><img src="./images/youtube_social_icon_red.png"></a>
</div>
<div class="col-sm-9">
<p class="sort-bio location-text">
This time we're going online for the first time! <a href="https://www.youtube.com/watch?v=fbKHLdoG7wA">Join
us as we livestream</a> two hours of talks per day, for
5 consecutive days. Free of charge!
</p>
</div>
</div>
</div>
</section>
<!--Start Daily Schedule Section-->
<section class="section-padding" id="schedule">
<div class="container">
<h1 class="section-title">Talks</h1>
<div id="workshop-ufo">
<img src="images/ufo.svg" class="ufo" alt="ufo">
</div>
</div>
<!--Start Days-->
<div class="day-one">
<div class="container">
<div class="day-title day">JULY 27th</div>
<div class="row">
<div class="col-md-8">
<div class="accordion" id="accordionOne">
<!--Start Day 1 Buttons-->
<div>
<button class="agenda-title collapsed" type="button" data-toggle="collapse" data-target="#collapseOne"
aria-expanded="false" aria-controls="collapseOne">
9PM UTC - Charity Majors: "The Sociotechnical Path to High-Performing Teams (Begins With
Observability)"
<img class="float-right plus-icon" height="20" width="20" src="./images/add.svg" alt="Toggle">
<img class="float-right minus-icon" height="20" width="20" src="./images/minus.svg" alt="Toggle">
</button>
<div id="collapseOne" class="collapse agenda-desc" aria-labelledby="headingOne">
<p>The gulf between elite and high-performing teams and the bottom 50% of teams is bigger than you
might think
-- and growing. Yet for all the time we spend
improving our skills as engineers, we pay far less attention to measuring and improving our
effectiveness at
the team level. Let's talk through
the shifting model for software ownership, what it means for ambitious teams, and why observability
is
step one to a better world.</p>
</div>
</div>
<div>
<button class="agenda-title collapsed" type="button" data-toggle="collapse" data-target="#collapseOneb"
aria-expanded="false" aria-controls="collapseOneb">
10PM UTC - María Vanina Martinez: "Symbolic Reasoning to model Sentiment and Knowledge Diffusion in
Social Networks"
<img class="float-right plus-icon" height="20" width="20" src="./images/add.svg" alt="Toggle">
<img class="float-right minus-icon" height="20" width="20" src="./images/minus.svg" alt="Toggle">
</button>
<div id="collapseOneb" class="collapse agenda-desc" aria-labelledby="headingOneb">
<p>Social media platforms, taken in conjunction, can be seen as
complex networks; in this context, understanding how agents react to
sentiments expressed by their connections is of great interest. We show
how Network Knowledge Bases help represent the integration of multiple
social networks, and explore how information flow can be handled via
belief revision operators for local (agent-specific) knowledge bases. We
report on preliminary experiments on Twitter data showing that different
agent types react differently to the same information - this is a first
step toward developing symbolic tools to predict how agents behave as
information flows in their social environment.</p>
</div>
</div>
<!-- End Day 1 Buttons-->
</div>
</div>
</div>
</div>
</div>
<div class="day-two">
<div class="container">
<div class="day-title day">JULY 28th</div>
<div class="row">
<div class="col-md-8">
<div class="accordion" id="accordionTwo">
<div>
<button class="agenda-title collapsed" type="button" data-toggle="collapse" data-target="#collapseTwo"
aria-expanded="false" aria-controls="collapseTwo">
9PM UTC - Will Kurt: "The Limits of Probability"
<img class="float-right plus-icon" height="20" width="20" src="./images/add.svg" alt="Toggle">
<img class="float-right minus-icon" height="20" width="20" src="./images/minus.svg" alt="Toggle">
</button>
<div id="collapseTwo" class="collapse agenda-desc" aria-labelledby="headingTwo">
<p>Probability is an increasingly ubiquitous part of our daily lives, especially as developers,
researchers and data
scientists. It is easy to mistakenly think this powerful tool is all we need to understand our
world. This talk will
show how our current environment of global pandemic, political unrest and economic uncertainty
forces us to face the
limits of probability as a tool for reasoning and understanding. This talk will cover both practical
examples of the
limitations of probability as well as dive into the philosophical roots of these limitations to show
that it cannot be
our only means to engage with our world.</p>
</div>
</div>
<div>
<button class="agenda-title collapsed" type="button" data-toggle="collapse" data-target="#collapseTwob"
aria-expanded="false" aria-controls="collapseTwob">
10PM UTC - LIGHTNING TALKS: Juan Pablo Lorenzo - Gajendra Deshpande
<img class="float-right plus-icon" height="20" width="20" src="./images/add.svg" alt="Toggle">
<img class="float-right minus-icon" height="20" width="20" src="./images/minus.svg" alt="Toggle">
</button>
<div id="collapseTwob" class="collapse agenda-desc" aria-labelledby="headingTwo">
<p>Juan Pablo Lorenzo: "Delete your code: in search of a minimalist approach to software development"
</p>
<p>Gajendra Deshpande: "Computation Techniques for Encrypted Data using Python"</p>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
<div class="day-three">
<div class="container">
<div class="day-title day">JULY 29th</div>
<div class="row">
<div class="col-md-8">
<div class="accordion" id="accordionThree">
<div>
<button class="agenda-title collapsed" type="button" data-toggle="collapse" data-target="#collapseThree"
aria-expanded="false" aria-controls="collapseThree">
9PM UTC - Aditya Siram: "What FP Can Learn From Static Introspection"
<img class="float-right plus-icon" height="20" width="20" src="./images/add.svg" alt="Toggle">
<img class="float-right minus-icon" height="20" width="20" src="./images/minus.svg" alt="Toggle">
</button>
<div id="collapseThree" class="collapse agenda-desc" aria-labelledby="headingThree">
<p>What if compile time and type level programming in functional programming languages were easy,
something you reach for
without even thinking about it? What if you could debug type errors with a simple compile time print
statement? Write
highly flexible systems by being able to introspect into types at compile time? Pre-calculate large
portions of your
programs for great efficiency? Typed functional programming is a great and fun way to write
resilient software, and as
type systems have become more and more expressive in recent years, we are able to program
sophisticated and useful
properties at the type level for even better compile time safety. Just one problem: It is very
difficult, requires
advanced knowledge of the type system, the syntax is convoluted, the error messages are
impenetrable, and it is nearly
impossible to debug. This talk will dive into why we should steal static introspection from
languages like Nim, and D,
state-of-the-art imperative programming languages which can solve all these issues, make type
systems much more
approachable without losing any expressive power, and offer new design possibilities for functional
programs.</p>
</div>
</div>
<div>
<button class="agenda-title collapsed" type="button" data-toggle="collapse"
data-target="#collapseThreeb" aria-expanded="false" aria-controls="collapseThreeb">
10PM UTC - Sergio Chouhy: "Deploying Deep Q Learning with Pytorch"
<img class="float-right plus-icon" height="20" width="20" src="./images/add.svg" alt="Toggle">
<img class="float-right minus-icon" height="20" width="20" src="./images/minus.svg" alt="Toggle">
</button>
<div id="collapseThreeb" class="collapse agenda-desc" aria-labelledby="headingThree">
<p>Many things are being said about Deep Reinforcement Learning, but sometimes it is really hard to
know where to start.
In this talk, I will tell you all about the basis of this algorithms and show you how to deploy Deep
Q Learning from scratch using Pytorch.
I will be also talking about applications of this technology in the industry.</p>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
<div class="day-four">
<div class="container">
<div class="day-title day">JULY 30th</div>
<div class="row">
<div class="col-md-8">
<div class="accordion" id="accordionOne">
<!--Start Day 4 Buttons-->
<div>
<button class="agenda-title collapsed" type="button" data-toggle="collapse" data-target="#collapseFour"
aria-expanded="false" aria-controls="collapseFour">
9PM UTC - Viral B. Shah: "Julia - A language for AI and much more"
<img class="float-right plus-icon" height="20" width="20" src="./images/add.svg" alt="Toggle">
<img class="float-right minus-icon" height="20" width="20" src="./images/minus.svg" alt="Toggle">
</button>
<div id="collapseFour" class="collapse agenda-desc" aria-labelledby="headingFour">
<p>The Julia language is now used by over half a million programmers worldwide. Created to solve the
two language problem,
Julia is demonstrating performance gains of 50x-100x for many data science tasks such as data
loading, data processing,
graph processing, machine learning and scaling. Robust support for modern deep learning and the
ability to do
differentiable programming in an intuitive way is quickly leading to Julia becoming the language of
choice for AI
workloads. My talk will discuss the origin story of Julia, the formation of the Julia community, and
all the amazing
things happening in the world of Julia.</p>
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10PM UTC - Chris Rackauckas: "How full language differentiability enables scientific machine learning
and Scientific
Software 2.0"
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<p>Scientific machine learning is a burgeoning field and its taking off in Julia. Why? The purpose of
this talk is to dive
into that question: how has language accelerated the development of Julia's SciML ecosystem? The
core
is composibility
through multiple dispatch. We will showcase how this feature is not only what makes standard Julia
code
as fast as C or Fortran,
but also allows Julia to eschew the traditional idea of "machine learning frameworks" and instead
have
machine learning directly
work on the standard functions and libraries of the whole Julia programming language.
This language-wide differentiable
programming then builds a foundation where existing climate models, helicopter simulations, and
efficiency
simulators for battery-powered
airplanes can be instantly composed with new tools for machine learning, and we will demonstrate how
this
has changed the way that
researchers in Julia do science.</p>
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9PM UTC - Pablo Fernandez: "Machine Learning in The Real World"
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<p>A tour of the last 3 years of my career where I’ve productionized 3 different machine learning
projects
on kind-of-a-big-company (Despegar).
Some of the challenges faced, not only technical but also from a product standpoint, some of the
pedagogical
work needed to convince
others of letting important decisions be made by a machine. Hopefully insights that help you bring
your own
models to production.</p>
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10PM UTC - Peter Alvaro: "What not where: why a blue sky OS?"
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<p>A world of distributed, persistent memory is on its way. Our programming models traditionally
operate on short-lived
data representations tied to ephemeral contexts such as processes or computers. In the limit,
however, data lifetime
is infinite compared to these transient actors. We discuss the implications for programming models
raised by a world
of large and potentially persistent distributed memories, including the need for explicit,
context-free,
invariant data references.
We present a novel operating system that uses wisdom from both storage and distributed systems to
center
the programming model
around data as the primary citizen, and reflect on the transformative potential of this change for
infrastructure
and applications of the future.</p>
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