AI2s winter Datathon 2021
a 24-hour data science challenge
THE AI2S DATATHON
TOPIC OVERVIEW: CRYPTO ART
Crypto Art is a rising art movement that associates digital artworks with non-fungible asset tokens. It draws its origins from conceptual art, sharing the immaterial and distributive nature of artworks, the tight blending of artworks with currency and the rejection of conventional art market and institutions. Similar to traditional artwork, the concept allows you to buy, sell and trade digital goods as if they were physical. Collectors of Crypto Art are overwhelmed with choices, reason why matching consumers with the most appropriate artworks is the key to enhancing user satisfaction. Can you suggest an artwork to an art collector?
EVENT TIMELINE: SUBSCRIPTION & SUBMISSION DEADLINES
The deadline for the registration is at 11:59 PM on Feb the 25th. The contest will begin at 10:00 AM on Feb the 27th and it will end at 10:00 AM on Feb the 28th. The deadline for submitting the solution coincides with the conclusion of the contest. The time offset considered is UTC+01:00.
LINK TO THE DATASET
If you are interested in our datathon then:
carefully read the following Eligibility and Requirements sections,
register to the devpost page and subscribe to the AI2S Winter Datathon 2021.
Upon registration, we will send you a link to the association Teams channel, the email that you will indicate in the subscription form will be our main communication channel with you.
All official communications will be also published in the Datathon News Page.
The official rules of the Contest are included in the PDF flile that you can find in the Rules section of this page.
The winner of the first place 🏆🥇 in the competition will receive a 500€ prize!!! 💰💰💰💶💶💶
The winner will be the best overall project taking into account all the judging criteria (see the "Judging criteria" section below).
Based on the prediction.csv files received from the teams participating at the competition, a Top 10 Ranking will be created using the RMSE (Root Mean Square Error) score (the less the better). Only submissions within the Top 10 Ranking will be evaluated by the judges and will compete for the final prize.
Has the candidate expressed his/her proposed solution in a scientific and procedural manner (report.pdf)?
Motivation of Choice
Has the candidate justified his/her choices with concrete hypothesis (report.pdf)?
The accuracy of the predictions will be evaluated using the root-mean-square error, or the square root of the quadratic mean of the differences between the predicted and observed values (prediction.csv).
MEet the Sponsor: Esteco
ESTECO is an independent software provider, highly specialized in numerical optimization and simulation data management with a sound scientific foundation and a flexible approach to customer needs. ESTECO's technology brings modularity, ease of use, standardization, and innovation to the engineering design process. ESTECO's smart engineering suite brings enterprise-wide solutions for design optimization, simulation and process data management (SPDM), and process integration and automation. With 20 years' experience, the company supports over 300 leading organizations in designing the products of the future, today.
Eric Medvet is an Associate Professor in Computer Engineering at the Department of Engineering and Architecture of University of Trieste, Italy. He founded and leads the Evolutionary Robotics and Artificial Life lab (ERALlab); he is the co-founder and co-head of the Machine Learning Lab. He won the silver medal at the 13th Human-Competitive Awards, 2016, for Human-Competitive Results produced by Genetic and Evolutionary Computation. He is a member of the scientific/program committee of the most important conferences on evolutionary computation. He authored and co-authored more than 120 peer-reviewed articles on international journals or conferences, with more than 20 coauthors.
After my PhD in Solid State Physics based on numerical simulations, I started an apprenticeship at ESTECO and I grew a passion for software developing.
I've been working for a couple of years as a full-stack developer in the ESTECO R&D team, focusing on cloud technologies, machine learning and artificial intelligence.
I'm quite meticulous and I love challenges and my hobbies reflect this. I love building and painting miniatures and I play lots of different board games.
MARCO DE PASQUALE
I am a Software Developer at Esteco, R&D Group. I am currently working with 4 other developers on a mobile application, for which we are exploring and studying the fascinating world of recommender systems.
I studied Physics at the University of Trieste, where I also got a Ph.D. in Earth Sciences and Fluid Mechanics. Passionate about basketball, I love both watching it and playing it in my free time. I also like music very much and have played drums for 10 years.
Luca Manzoni is an assistant professor at the University of Trieste, Italy. He obtained his Ph.D. in Computer Science from the University of Milano-Bicocca in 2013. In 2012 he obtained a JSPS postdoctoral fellowship and in 2017 he obtained an award as the best young postdoc in Computer Science and Mathematics at the University of Milano-Bicocca. He has published more than 80 paper in international journal, conferences, and workshops. His interests are in the areas of natural computing models, like P systems, reactions systems, and cellular automata and in the area of evolutionary computation, and genetic programming in particular.
Here you can find the official rules of the AI2S Winter Datathon