Click on a name on the left for more information about a speaker
Ronald Oomen and Patrick Bart
Ronald Oomen and Patrick Bart are creative thinkers. They believe in visualisation because it is much stronger than words alone. Their company Visual Brain focusses on visual thinking and they guide their customers to achieve their goals by using visuals.
Talk: Workshop: masterclass visualisation
Our mission on this event is to inspire you as a student to start using your own visuals! We will show you how you can easily create a stunning powerpoint that will leave your public stunned! From this day on, during your study and career live you will remember this masterclass and use what you’ve learned. We will take you on a tour and show you why visuals work. After that we show how a perfect Powerpoint should look and we will give a few simple tips how to create your own. You can practice during the masterclass or just watch how we do it!
dr. Jakub Tomczak
Jakub Tomczak is a deep learning research engineer at Qualcomm AI Research since October 2018. Before, he was a postdoc (Marie Sklodowska-Curie Individual-Fellow) in Amsterdam Machine Learning Lab (AMLAB) at the University of Amsterdam under Prof. Max Welling supervision from Oct 2015 to Sept 2018. He has received Ph.D. in machine learning (with honors) from Wroclaw University of Technology (Poland) in March 2013. After Ph.D. studies he worked on ensemble learning, probabilistic modeling and deep learning (with a special interest in Boltzmann machines) applied to credit scoring, medicine (clinical data) and image analysis. Recently, his research focused on deep generative modeling (Variational Auto-Encoders) for medical imaging and image analysis.
Talk: The Future of Deep Learning: Deep Generative Modeling
Deep learning has become almost a default tool in many real-life problems like image analysis, audio analysis and text analysis. Due to increasing computational capabilities, neural networks are deeper and their training is faster. However, learning models that are capable of capturing rich distributions from vast amounts of (unlabeled) data remains one of the major challenges of artificial intelligence. For instance, there is an enormous number of images available online, however, labeling them all is almost an impossible task. Therefore, in order to take advantage of a flood of unlabeled data, deep generative modeling provides a natural manner of dealing with both labeled and unlabeled data. In recent years, different approaches to deep generative modeling were proposed by formulating alternative training objectives to the log-likelihood like the adversarial loss that leads to Generative Adversarial Networks (GANs) or by utilizing variational inference that results in a family of Variational Auto-Encoders (VAE). A third way is an application of autoregressive models like PixelCNN or WaveNet. During our meeting we will discuss these three approaches and point out their advatages and disadvantages. In order to present their successes, the most promising applications of these deep generative models will be outlined.
Guido Berben and Sida Nakrošytė
Guido Berben is Partner Manager at Tikkie and Sida Nakrošytė is an iOS App Developer at Tikkie.
Talk: Tikkie, from idea to popular payment app
In the beginning there was an idea that didn't look like Tikkie, even the name was not Tikkie... During this presentation we will tell you everything about the first concepts, how we came to Tikkie as you know it and how we ended up being the most popular payment app in the Netherlands with over 4 million app users and even more Tikkie payers. Tikkie started as an consumer-to-consumer payment app, but after 2,5 years we also offer several business propositions and are still improving the app with new functionalities to make life, or at least payments, easier for consumers and businesses. How do we generate and test new idea’s, what is the relation between David Hasselhof and Tikkie, what is our vision in every new proposition we develop and how do we work together in a small team with IT, marketing and sales? We will answer all of these questions and more! At last we will offer you a sneak preview in the direction we are heading and what opportunities and challenges lie ahead.
dr. Christian Majenz
Christian Majenz obtained his Master's degree in physics from University of Freiburg. His M.Sc. thesis was supervised by David Gross. He obtained his PhD from University of Copenhagen under the supervision of Matthias Christandl, spending some time at Caltech along the way. Currently, he is a postdoctoral researcher at the QuSoft center and University of Amsterdam.
Talk: Cryptography in the age of quantum computers
The quantum computer will likely change the world quite significantly, once humanity will have succeeded in building one. In addition to new opportunities for, e.g., drug development, they will pose new threats to the encryption we use on the internet every day. In this talk I will give you a glimpse into the world of quantum secure cryptography.
dr. Shane Steinert-Threlkeld
Shane has, since March 2017, been a postdoctoral researcher at the Institute for Logic, Language and Computation at the UvA. Starting in the Fall, Shane will be an Assistant Professor in (Computational) Linguistics at the University of Washington. Before Amsterdam, he received his PhD at Stanford and spent some time working at Google Research and Machine Intelligence. His primary research uses computational methods to address questions at the foundations of the language and cognitive sciences. A particular focus has been on explaining why human languages are structured the way that they are.
Talk: Ease of (machine) learning explains semantic universals
Semantic universals are properties of meaning that are attested in all of the languages of the world. In this talk, I develop an explanation for why such universals arise: expressions satisfying them are easier to learn than those that do not. Using techniques from machine learning, I show that this answer can provide a unified explanation of universals in three disparate linguistic domains, encompassing both function and content words: quantifiers, responsive predicates, and color terms
dr. Leo Ducas
I have obtained my PhD at ENS Paris, on the topic of Lattice-based Cryptography. After a post-doc at UCSD, I have joined CWI in 2015. I obtained a VENI grant in 2016, and am now tenured at CWI. My main research interest lie in the design of algorithms, both for the construction and the cryptanalysis of lattice-based cryptosystems.
Talk: Quantum-safe Cryptography from lattices: designs and attacks
The standardization and deployment of quantum-safe (aka post-quantum) cryptography is already ongoing, as a response to ever-growing fear of seeing good-old RSA and ECC succumb to the emergence of large quantum computers. May this happen in 5, 15 or 30 years, deployment delays and long term secrecy requirements urges us to act now. In this talk, I will present the basic principles of lattice-based cryptography, one of the quantum-safe option; and give an overview of the several design options. I will also explain the ongoing development in the cryptanalysis effort, much needed to make concrete security estimates.
Giulio Stramondo Msc
Giulio did his Bsc at the Politecnico di Milano, he has double MSc from the University of Illinois at Chicago and the Politecnico di Milano. Since 2016 he is a PhD student at the UvA; he works in the field of High Performance Computing and is specialised in memory systems for FPGA accelerators.
Talk: Reconfigurable Hardware for High Performance Computing
High Performance Computing is responsible for many of the spectacular developments we see today, from brain simulation to AI, and physics. However, reaching high performance does not come for free: a lot of effort in designing better applications and better architectures is ongoing, to address challenges like efficiency and high power consumption. In this talk, we focus on the ambition and challenges of the field today: reaching exascale performance with minimum power consumption. We further present in more detail one of the most promising solutions to achieve this goal: reconfigurable hardware. We will explain the principles, advantages, and disadvantages of these computing gems, and give several real-life examples where they have been proven exceptionally useful.
Robbert van Ginkel
Robbert did his Bachelor in artificial intelligence at the University of Amsterdam and got his degree in 2015. He now works as Senior Software Engineer at Uber.
Talk: Continuously shipping software to millions of people
Behind the Uber and Uber Eats apps lives a world of technology responsible for providing users with near instant and reliable service in 600+ cities across 65 countries. Whether it is getting a ride by car or bike, food delivery or shipping freight across a continent, Uber's systems need to be highly reliable as riders trust us to get them home and drivers rely on us for opportunities to earn. In addition to providing a reliable everyday service, Uber is also constantly evolving to respond to changes in cities, customer demands, and new opportunities. These fast-paced changes with significant real-world impact potential present a challenge to many of Uber's engineers every day. This talk will dive into Uber's engineering platform and take you through the journey of a change, highlighting some of the processes and systems we have built to help engineers ship with confidence.
dr. Nicola Rieke
Nicola Rieke is a senior solution architect at NVIDIA for deep learning in healthcare. With a broad expertise in the field of medical image processing, applied machine learning and computer-aided medical procedures, one of her primary responsibilities is to actively support the medical imaging community in advancing deep learning solutions. She holds a PhD (Dr. rer. nat.) from the Technical University of Munich, published various peer reviewed papers, in particular on real-time machine learning approaches for computer assistance in surgical interventions, and was honored with the prestigious MICCAI Young Scientist Award.
Talk: AI in Medical Imaging: Challenges, Tools, and Opportunities
From diagnosis over treatment planning and interventional assistance to follow-up - many medical domains build on digital information. The timely acquisition, analysis and visualization of this data is crucial for enabling modern healthcare applications and computer assistance has become an essential part of the medical workflow. With an aging population, the growing amount of acquirable information, and the possibilities of more complex, less-invasive procedures, the workload for physicians keeps increasing and more advanced support is necessary. In this talk we will discuss how artificial intelligence could enable this advanced computer assistance, what challenges we have to tackle on the way and which tools we have already at hand to bring healthcare to the next level.
dr. Debraj Roy
Debraj Roy currently works at the Department of Computational Science, University of Amsterdam as a Postdoctoral Researcher. Debraj does research in Spatial Modelling, Population Dynamics, Computational Sociology, Social Choice Theory and Complexity Science. He completed his PhD in 2017 from Nanyang Technological University, Singapore in Computer Science and Engineering. He specifically employs agent-based modelling (ABM), parallel discrete event simulation (PDES) and geographic information system (GIS) to study these systems. To calibrate and validate these models he applies methods from remote sensing, spatial statistics and information theory. His current research interests are primarily in the modelling and simulation of large-scale human complex systems. Current application areas include the study of human migration, urban poverty, crowds and egress and social contact networks.
Talk: Modeling and simulation of complex urban systems
Two primary dynamics are shaping the cities in the 21st century: processes of emergence where cities ‘emerge’ as a result of uncoordinated self-organization, and intervention through intentional design and planning by urban planners. These dynamics are opposite and complementary; impacted by high degree of uncertainties, and constraints. In this talk, I will describe how modelling and simulation can enhance our understanding of urban complex systems, particularly the role of individual behavioural interactions on collective and system level dynamics. I will discuss current application areas such as the study of human migration, urban poverty and crowds. Finally, I will discuss some challenges around validity and transferability of the models.
dr. Joris Mooij
Joris M. Mooij studied mathematics and physics and received his PhD degree with honors from the Radboud University Nijmegen (the Netherlands) in 2007. His PhD research concerned approximate inference in graphical models. During the next three years, he worked on causal discovery as a postdoc at the Max Planck Institute for Biological Cybernetics in Tübingen (Germany). In 2011 he obtained an NWO VENI grant, which allowed him to do a second postdoc, this time at the Radboud University Nijmegen. In 2013 he became Assistant Professor at the Informatics Institute of the University of Amsterdam (the Netherlands). In the next years, he obtained an NWO VIDI grant and an ERC Starting Grant, allowing him to start his own research group, consisting of 4 PhD students and 1 postdoc, focussing entirely on causal discovery. The research topics addressed by his group span the entire spectrum from causal modeling, discovery, prediction, validation and application and combine mathematical, algorithmic, statistical and modeling aspects. In 2017 he was promoted to Associate Professor. He has won several awards for his work.
Talk: How To Learn Causal Relations From Data?
Many questions in science, policy making and everyday life are of a causal nature: how would a change of A affect B? Causal inference, a branch of statistics and machine learning, studies how cause-effect relationships can be discovered from data and how these can be used for making predictions in situations where a system has been perturbed by an external intervention. The ability to reliably make such causal predictions is of great value for practical applications in a variety of disciplines. The standard method to discover causal relations is by using experimentation. Over the last decades, alternative methods have been proposed: constraint-based causal discovery methods can sometimes infer causal relations from certain statistical patterns in purely observational data. In this talk, I will introduce the basics of both approaches to causal discovery. I will discuss how these different ideas can be elegantly combined in Joint Causal Inference (JCI), a novel constraint-based approach to causal discovery from multiple data sets. This approach leads to a significant increase in the accuracy and identifiability of the predicted causal relations. One of the remaining big challenges is how to scale up the current algorithms such that large-scale causal discovery becomes feasible.
dr. Christoph Heller
Christoph Heller is working as an FPGA engineer at IMC, where he is responsible for the design and implementation of low-latency trading systems in programmable hardware. He has studied electrical engineering at RWTH Aachen University (Germany) and is holding a PhD (Dr.-Ing.) from Stuttgart University (Germany). Before joining IMC in 2016, he has worked 10+ years as a research specialist in the aerospace industry, generating numerous peer-reviewed publications and patents.
Talk: Hunting Nanoseconds - The Use of FPGAs in Electronic Trading
Nowadays, the vast majority of financial securities are traded purely electronically: Data centers have replaced crowded trading floors and digital communication networks have replaced the shouting and hand signs of the open outcry trading of the past. Electronic trading improved throughput, fairness and determinism on the markets, but also started a speed race between market participants. Today, on technically advanced exchanges, latency differences in the single-digit nanosecond range can make the difference between getting or missing a trade. In competitive markets one therefore needs to be extremely fast to monetize profitable trading opportunities. Programmable hardware devices such as FPGAs (Field Programmable Gate Arrays) can provide the required latency edge over pure software solutions, while keeping the flexibility to upgrade trading algorithms or communication protocols whenever required. In this talk, I will explain the basics of electronic trading and the interaction of trading systems with exchanges. I will provide an introduction to FPGAs and the technical and methodological trade-offs associated with their use. Based on this, we will discuss the efficient usage of FPGAs in electronic trading systems, as well as approaches to maximize trading performance by minimizing latency.
dr. Douwe Kiela
Douwe Kiela is a research scientist at Facebook AI Research (FAIR) in New York. He received his PhD and MPhil from the University of Cambridge Computer Laboratory. Before that, Douwe completed an undergraduate degree in Liberal Arts & Sciences at Utrecht University with a double major in Cognitive Artificial Intelligence and Philosophy; and then a master's degree in Logic at the University of Amsterdam's Institute for Logic, Language & Computation. Douwe’s work focuses on machine learning and natural language processing, where his research interests lie in grounded language learning and developing better models for language understanding.
Talk: Grounded Multi-Agent Language Games
I will talk about recent work done at FAIR on novel directions for natural language processing research. While a lot of progress has recently been made in natural language understanding, e.g. by using word and sentence embeddings, big challenges remain. I will discuss fresh perspectives on natural language learning, in the shape of grounded multi-agent language games.
The university has become my natural professional habitat. Working with the brightest minds is a pleasure and a challenge every day. I have always been involved around creating new things and finding ways to make them last. From International Offices to Centers of Entrepreneurship to new degree programs to organizational changes. Never on my own because I believe in the strength of teamwork. Today I am director at ACE were we set up programs and (international) partnerships that enable students and young researchers to start high impact ventures. In 2011 we were awarded an European Enterprise Award. Emerce calls us the best Dutch incubator in 2018. My latest achievement is the Startup Village at Amsterdam Science Park: an out-of-the-box location for innovation and entrepreneurship. We turned second hand sea containers into offices and work spaces for science- & technology companies. I welcome new opportunities including: speaking, consultancy, advice, new leadership in areas that matter to me.
Talk: With a little help from my friends - Ecosystem for starting a tech company in Amsterdam
In this fast-moving talk we will map out education, business, incubators/ accelerators and investors in Amsterdam and their current and future activities and programs, all related to the different stages where companies are in (concept, startup, scale up, mature). It brings structure and insights, resulting in an overview of essential steps for launching and growing tech startup companies. It explains how to establish processes for running a startup and how to plan and ensure a stable growth of your startup ecosystem. We will take you around the city of Amsterdam to share possibilities for support on how to build a successful startup. After introducing the Amsterdam entrepreneurship ecosystem we will touch on all the important stakeholders that make up the ecosystem and the role that each of them plays. The talk is littered with examples of what has worked and what hasn't worked. You'll come away from this talk with valuable knowledge and a renewed enthusiasm to get started on your own tech company or join existing ones!
Van Rossum Room
Doors open09:00 - 10:00
Robbert van Ginkel10:00 - 11:00
Continuously shipping software to millions of people
Erik Boer10:30 - 11:30
With a little help from my friends - Ecosystem for starting a tech company in Amsterdam
Giulio Stramondo Msc11:00 - 11:30
Reconfigurable Hardware for High Performance Computing
dr. Nicola Rieke11:30 - 12:30
AI in Medical Imaging: Challenges, Tools, and Opportunities
dr. Joris Mooij11:30 - 12:30
How To Learn Causal Relations From Data?
dr. Debraj Roy12:00 - 12:30
Modeling and simulation of complex urban systems
Lunch12:30 - 13:30
dr. Christian Majenz13:30 - 14:30
Cryptography in the age of quantum computers
dr. Jakub Tomczak13:30 - 14:30
The Future of Deep Learning: Deep Generative Modeling
dr. Leo Ducas13:45 - 14:45
Quantum-safe Cryptography from lattices: designs and attacks
dr. Shane Steinert-Threlkeld14:45 - 15:45
Ease of (machine) learning explains semantic universals
dr. Douwe Kiela14:45 - 15:45
Grounded Multi-Agent Language Games
Ronald Oomen and Patrick Bart15:00 - 16:00
Workshop: masterclass visualisation
dr. Christoph Heller16:00 - 17:00
Hunting Nanoseconds - The Use of FPGAs in Electronic Trading
Guido Berben and Sida Nakrošytė16:00 - 17:00
Tikkie, from idea to popular payment app
Drinks17:00 - 18:00