Agenda
Sep 19-Sep 21 | Pullman Tbilisi Axis Towers, 37 Ilia Chavchavadze Avenue, Tbilisi 0179, Georgia
20 Sept.
Hackathons
17:30
1 hr 30 min
Storytelling Stage
Hackathons Pitching
ThruthTechThon Hackathon
DemTech Hackathon
TFGBV Hackathon
20 Sept.
DataVoter
17:30
1 hr 30 min
Meeting Room #2
Rethinking the Soviet Past Using Archival Data
Irakli Khvadagiani
Chairman of the Board of the Laboratory
of the Soviet Past
Join Irakli Khvadagiani, Chairman of the Board of the Laboratory of the Soviet Past, in this interactive workshop focused on Soviet history through newly accessible archival materials. Participants will learn methods for analyzing primary sources and discuss the challenges and opportunities of working with archival data. Explore how these materials can reshape our understanding of the Soviet experience and contribute to a more nuanced interpretation of the Soviet past.
20 Sept.
Data Art & Design
17:30
1 hr 30 min
Meeting Room #4
One-on-one feedback session
Want to receive one-on-one feedback on your data visualization from our incredible speakers? Enter the room to consult with selected data visualization experts!
20 Sept.
Data, Marketing and Ads
18:30
30 min
Main Stage
Inside the Data That Drives Marketing Decisions
Giorgi Berechikidze
Data-Driven Marketing Lecturer at Commschool &
Growth Marketing Executive at VELI.store
Join Giorgi Berechikidze, Data-Driven Marketing Lecturer at Commschool and Growth Marketing Executive at VELI.store, as he uncovers the inner workings of data-driven marketing. In this talk, Giorgi will explain the types of data marketers rely on and how this data informs both tactical and strategic decisions. Gain insight into how marketing managers analyze and interpret extensive data sets to make smarter, more informed choices. Whether you're involved in marketing strategy or simply curious about the data behind the decisions, this session will offer a deeper understanding of the data that fuels successful marketing campaigns.
21 Sept.
10:30
30 min
Pullman Tbilisi Axis Towers
WELCOME COFFEE & REGISTRATION
21 Sept.
Analytics, Data Science & Gen AI
11:00
30 min
Main Stage: Startups and Businesses
LLM Chatbots for Georgian: Tackling Challenges of a Low-Resource Language
Zurab Dzindzibadze
Head of the AI Lab at Bank of Georgia
This session looks at creating Large Language Model (LLM) chatbots for Georgian and the challenges that come with working on languages with limited digital resources. We'll compare Retrieval-Augmented Generation (RAG) to standard chatbots and discuss how they work when there isn't much language data available. We'll talk about the specific problems in making LLM chatbots for Georgian, where RAG-based models might work better than regular ones, and what to watch out for when using these technologies.
21 Sept.
Analytics, Data Science & Gen AI
11:00
1 hr 30 min
Technology Stage
Data science and data platforms in the cloud (design, decision making, how, why, when)
Brian Gillikin
Technical Lead & Data Scientist at IBM
This session explores the world of cloud-based data science and data platforms, examining how cloud technologies are transforming data management and analysis. Attendees will gain insights into cloud design and architectural decision-making, learning when and how to leverage cloud technologies for optimal data science outcomes. Discover the strategic advantages of cloud solutions and understand why integrating these technologies can be crucial for advancing your data science initiatives.
21 Sept.
Analytics, Data Science & Gen AI, Startups
11:00
45 min
Meeting Room #1
Breast Cancer Detection Through Thermal Imaging
Hayk Sargsyan
Lead Machine Learning Engineer
at LABZ.AI & ThermaiScan
Join Hayk Sargsyan as he presents findings from a clinical validation study on using thermal imaging for breast cancer detection. This non-invasive, low-risk screening method utilizes a smartphone with a thermal imaging sensor and machine learning to enhance early detection. Hayk will discuss the promising results of this approach, its challenges, and limitations, and propose future research directions. Discover how machine learning-based thermal imaging could improve breast cancer screening programs and support early detection efforts.