Segolene Dessertine-Panhard
Employers on the program
- 2019–2026Amazon Web Services2 talks
Upcoming appearances
Who’s booked ahead? →Event dates shown; only events starting today or later count. 1 upcoming event.
-
AWS re:Invent 2026 – · Las Vegas, United States
- Automate AI governance and risk management with John Deere breakout Program source ↗
No upcoming appearances are currently recorded.
The year around now
Talks in the past 12 months and announced talks ahead, one row per conference, January to December. Hover a mark for the talk.
Appearances by year
- AWS re:Invent
Talks
| Date | Event | Conference | Role | Title | Links |
|---|---|---|---|---|---|
| Nov 30, 2026 | AWS re:Invent 2026 | AWS re:Invent | breakout | Automate AI governance and risk management with John Deere as Amazon Web Services Governance frameworks designed for static deployments struggle to keep pace with AI systems that learn, adapt, and act autonomously. Walk through AWS…Show lessGovernance frameworks designed for static deployments struggle to keep pace with AI systems that learn, adapt, and act autonomously. Walk through AWS Responsible AI best practices for governing AI across the full development lifecycle. | |
| Nov 27, 2023 | AWS re:Invent 2023 | AWS re:Invent | breakout | How to build a responsible and sustainable generative AI chatbotGenerative AI–powered chatbots are increasingly being applied across multiple industries. However, their effectiveness relies on a crucial factor:…Show lessGenerative AI–powered chatbots are increasingly being applied across multiple industries. However, their effectiveness relies on a crucial factor: trustworthiness. | Video |
| Dec 2, 2019 | AWS re:Invent 2019 | AWS re:Invent | workshop | [REPEAT 1] Amazon SageMaker RL: Solving business problems with RL and bandits as Amazon Web Services France In reinforcement learning (RL), an RL agent learns in an interactive environment by trial and error using feedback from its own actions, and can make…Show lessIn reinforcement learning (RL), an RL agent learns in an interactive environment by trial and error using feedback from its own actions, and can make sophisticated multi-step decisions. As a result, RL has broad applicability in robotics, industrial control, finance, HVAC, dialog systems, online advertising, and more. | Slides |
Frequent co-speakers
| Speaker | Shared events | Shared talks | Last together |
|---|---|---|---|
| Achraf Souk | 3 | — | 2026 |
| Ali Saidi | 3 | — | 2026 |
| Amit Kumar | 3 | — | 2026 |
| Andrew Crudge | 3 | — | 2026 |
| Andrew Krug | 3 | — | 2026 |
| Andy Reedy | 3 | — | 2026 |
| Andy Warfield | 3 | — | 2026 |
| Arthur Petitpierre | 3 | — | 2026 |
| Bashuman Deb | 3 | — | 2026 |
| Ben Smith | 3 | — | 2026 |
| Brian Beach | 3 | — | 2026 |
| Chad Schmutzer | 3 | — | 2026 |
| Christian Elsen | 3 | — | 2026 |
| Clare Liguori | 3 | — | 2026 |
| David Piet | 3 | — | 2026 |
Speakers with the same name are merged into one entry, so this page may combine more than one person. Affiliations are shown as each conference listed them.