August 6 | Demo Day | AI Innovation

 

Overcoming Data Challenges & Building Real-World Solutions

 

 

45 mins, 3 case studies, and exclusive insights from 100+ AI engineers and domain experts

 

                      In our upcoming virtual demo day, Omdena’s changemakers will cover the following themes:

                                         – Overcoming data challenges through the power of collaboration and diversity 

                                         – Building innovative AI & data science solutions

                      We will end with a 15 minutes Q&A session.

The case studies

 

Topic 1: Finding the safest path in the aftermath of an earthquake 

In collaboration with Istanbul’s Impact Hub innovation center, Omdena data scientists identified the problem – emergency response in an earthquake prone region – and then the solution. The data scientists combined satellite imagery of Istanbul with street map data in order to build a tool which facilitates family reunification by indicating the shortest and safest route between two points after an earthquake.

“Omdena´s approach to AI development is by far the best that I have seen in 2019” – Semih Boyaci, Co-Founder Impact Hub Istanbul

 

 

Topic 2: Building a chatbot for Post-traumatic-stress-disorder (PTSD) assessment

32 Omdena collaborators developed a machine learning driven chatbot for PTSD assessment in war and refugee zones. 

The unique aspect of the project was that we did not start with at data set.

Only through the collaborative efforts of the project community, we could identify and annotate suitable patient data. The teams applied linear classifiers for Natural Language Processing (NLP) for PTSD risk assessment and transfer learning for data augmentation.

Topic 3: Preventing gang and gun violence via NLP and Twitter analysis 

Together with public benefit corporation Voice 4 Impact, 32 collaborators leveraged NLP techniques to spot and prevent gang and gun violence. First, a tool was created to label tweets faster and train the machine learning model. Next, the sentiment analysis team built a machine learning model to predict whether the tweets are threatening or non-threatening.

The technology will be integrated into I.D. Eco, the first technology to enable school administrators, law enforcement and public safety officials to proactively monitor and address potential threats before they become acts of violence.

How to get a chance to join the demo day

The discussion will be on an invite-only basis to ensure a helpful and effective dialogue.

You can apply below by answering two brief questions.

 

Event date

Thursday August 6, 14 UTC

45 minutes in total 

30 mins presentation and 15 minutes Q&A session and open dialogue

Event Application