Registration for HackReason 2022 must be done here.
A list of Frequently Asked Questions can be found here.
You can find a consolidated list of resources, including th e hackathon's schedule, submission information, and more, in the UTD HackReason 2022 Notion linked here!
Additionally, make sure to join the HackReason Discord server. This will be the main communication platform for this hackathon! A guide on how to use Discord can be found here.
Since a DevPost submission is required, make sure to look over this video guide to DevPost submissions, accesible here.
Past projects from HackReason '21 can be viewed here.
Once again, Discord will be the main communication method throughout this event. Any further questions can be adressed by contacting AIS and Dr. Gupta, with their contact information respectively listed below.
Required tools:
For preparation, teams can install the s(CASP) system in advance if they have Linux (though it is also available on our Unix machines, such as cslinux1, cslinux2). The software can be downloaded and installed from this link.
Furthermore, the s(CASP) Research Paper can be viewed here.
Professor Gupta will give two 2-hour tutorials to provide the technological background, including how to use the s(CASP) system, a week prior to the event.
Introductory Workshops for s(CASP):
1. Introduction to Logic Programming & Prolog
Presented by: Dr. Gupta
Date & time: January 10th, 1 PM - 3 PM CST
2. Introduction to Answer Set Programming, s(CASP), and Automated Commonsense Reasoning
Presented by: Dr. Gupta
Date & time: January 12th, 1 PM - 3 PM CST
Additional Workshops happening during the Hackathon:
3. Presentation: Atos & their AI/ML efforts
Presented by: Atos Corp.
Date & time: January 14th, 11:45 AM CST
4. Presentation: Logic & reasoning
Presented by: Professor Moshe Vardi of Rice Universiy
Date & time: January 14th, 12 PM CST
5. Talk: Autonomous driving based on common sense reasoning
Presented by: Dr. Gopal Gupta
Date & time: January 14th, 4 PM CST
6. Talk/demo: Explainable Machine Learning
Presented by: PhD student Huaduo Wang
Date & time: January 14th, 7 PM CST
Meet HackReason's official mentors! They will be available in the official Discord channel to answer questions about the s(CASP) system, or to provide guidance on teams' projects. Their emails can be found by clicking on their name.
Dr. Gopal Gupta is the Erik Jonsson Professor of Computer Science. His research interests are in logic programming, automated (commonsense) reasoning annd answer set programming. His group has developed many software systems, including the s(CASP) system that will be used in HackReason.
Dr. Elmer Salazar is an assistant professor of instruction in computer science at UT Dallas, from where he also got his Ph.D. Professor Salazar was the designer of the s(ASP) answer ste programming system that the s(CASP) system is based on. His research interests are in logic programming, answer set programming and automated (commonsense) reasoning.
Dr. Arias is an assistant professor of computer science at King Juan Carlos University in Madrid, Spain. He is the primary developer of the s(CASP) system on which he began work while visiting UT Dallas in 2017. He got his Ph.D from Universidad Politechna de Madrid. His research interests are in logic & constraint programming languages and their applications in reasoning, particularly over stream data.
Kinjal is a PhD student in Prof. Gupta and Salazar's lab. Kinjal's research involves applying ASP & commonsense reasoning to natural language question answering and automated chatbot development. He is the team leader of the Team UTD that qualified for the Alexa Socialbot Challenge 2021 competition.
Sarat is a PhD student working under Prof. Neeraj Mittal and Prof. Gopal Gupta's supervision. His research is focussed on automatically generating concurrent algorithms from their respective sequential version using commonsense knowledge and ASP. He is also a member of the Alexa Socialbot Challenge 2021 Competition.
Suraj is a PhD student whose research interests lie in optimizing Deep Neural Networks for various computer vision problems. He has worked on a variety of projects, including problems related to Agriculture, Healthcare and Security using Cognitive Engineering, Internet of Things, Machine Learning, Computer Vision and Robotics.