Sharon is a senior data scientist at Quris AI, where she applies machine learning to improve drug safety assessment and advance personalized medicine. Her work focuses on predicting drug pharmacokinetics based on drug structure and patient parameters. Prior to joining Quris AI, she was a researcher at Amazon AWS, working on document analysis using both computer vision and natural language processing techniques. She holds an MSc in electrical engineering from Tel Aviv University and a BSc in physics and mathematics from the Hebrew University of Jerusalem as part of the Talpiot Military Program. Before transitioning to industry, she served as an electronic warfare researcher in the military.
Inbal Lavi is a senior data scientist at Microsoft in the Windows Silicon and System Integration group, specializing in computer vision. She holds an MSc in electrical engineering from Tel Aviv University and a BSc in physics from Hebrew University, where she was part of the Talpiot program. Inbal has extensive experience in the field, having previously worked at Amazon Web Services at the intersection of computer vision and natural language processing. Prior to that, she served as a machine learning researcher and team leader in the military. In her spare time, Inbal mentors in the Baot job search program.
Transitioning from an academic paper to a production-ready product presents a unique set of challenges. In this roundtable, we will explore the hurdles encountered when adapting research to real-world applications, especially in data science. These challenges include dealing with differences in datasets, handling edge cases that may not be captured in academic settings, addressing computational limitations, and ensuring robustness in production environments. Additionally, the session will highlight best practices, from validating models under real-world conditions to refining algorithms to meet industry standards. Participants will engage in an open discussion on their experiences and share strategies for successfully bridging the gap between academic research and production use. This conversation will provide insights for researchers and practitioners looking to ensure their innovations are scalable, reliable, and impactful.
| 8:45 | Reception |
|---|---|
| 9:30 | Opening remarks by WiDS TLV ambassadors |
| 9:45 | Dr. Mor Geva , Tel Aviv University: “MRI for Large Language Models: Mechanistic Interpretability from Neurons to Attention Heads” |
| 10:15 |
Panel: “Pioneering Progress: a strategic look at the GenAI revolution and the new role of data scientists“ Shani Gershtein, Melingo Mirit Elyada Bar, Intuit Dr. Asi Messica, Lightricks Moderated by Nitzan Gado, Intuit |
| 10:45 | Poster pitches |
| 10:55 | Break |
| 11:10 | Lightning talks session |
| 12:30 | Lunch & poster session |
|---|---|
| 13:30 | Roundtable session & poster session |
| 14:30 | Roundtable closing |
| 14:40 | Shunit Agmon, Technion: “Bridging the Gender Gap in Clinical AI: Temporal Adaptation with TeDi-BERT” |
| 15:00 | Shaked Naor Hoffmann, Apartment List: “Building Generative AI Agents for Production: Turning Ideas into Real-World Applications” |
| 15:20 | Closing remarks |
| 15:30 | The end |
WiDS Tel Aviv is an independent event that is organized by Intuit’s WiDS TLV ambassadors as part of the annual WiDS Worldwide conference, the WiDS Datathon, and an estimated 200 WiDS Regional Events worldwide. Everyone is invited to attend all WiDS conference and WiDS Datathon Workshop events which feature outstanding women doing outstanding work.
© 2018-2024 WiDS TLV – Intuit. All rights reserved.
Scotty – By Nir Azoulay
Design: Sharon Geva
