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Conferences / MLCon (ML Conference)

MLcon San Diego 2025

May 19–23, 2025 · Hyatt Regency La Jolla at Aventine, San Diego, CA, United States

Conference
MLCon (ML Conference) Data science & ML
Dates
May 19, 2025 – May 23, 2025
Venue
Hyatt Regency La Jolla at Aventine
Place
San Diego, CA, United States
Format
Hybrid
Status
Past
Attendance
—
Website
mlconference.ai
Recorded
0 sponsors · 31 speaker appearances
Notes
First San Diego edition; hybrid ('San Diego or Online'), conference days and expo May 20-21; part of the 'devmio San Diego Week' (upgrade USD 250). Sponsor lists on the archived pages are rendered by script and could not be recovered. Prices are regular list prices excluding tax ('instead of' prices). Speakers: every program session listed for this edition in the organizer's program database (as rendered on the program/archive pages); role follows the session type (keynote/workshop/session).

Ticket prices

TicketPriceValid untilNotesSource
Conference Day$799—regular priceweb.archive.org
2-Day Pass$1,399—regular priceweb.archive.org
3-Day Pass$1,849—regular priceweb.archive.org
4-Day Pass$2,299—regular priceweb.archive.org
All Conference Days + Bootcamp$2,599—regular price; from USD 2,339 incl. team discountweb.archive.org

Sponsors 0

No sponsors recorded

Speakers and talks 31

SpeakerCompanyRoleTalkLinks
Dr. Pieter ButeneersEmma LegalKeynoteAMA (ask me anything) Session with the ML Experts—
Dr. Pieter ButeneersEmma LegalKeynoteFrom Crapbot to ChatGPT - How we finally made chatbots work—
Garima BajpaiCanada DevOps Community of PracticeKeynoteOperationalizing AI: Leadership Insights—
Garth HensonMuseKeynoteThe Paths of Wisdom: Navigating AI’s Role in Creative Storytelling—
Joanne RodriguesState of CaliforniaKeynoteAMA (ask me anything) Session with the ML Experts—
Kris Buytaerto11yKeynoteWelcome and Opening Remarks & Lessons from 10 years of Platform Engineering—
Paul DubsXpress AIKeynoteAMA (ask me anything) Session with the ML Experts—
Sebastian MeyenSoftware & Support Media GmbHKeynoteWelcome and Opening Remarks & Lessons from 10 years of Platform Engineering—
Alex Perez-TenessaTrendioSpeakerUsing AI in social media to drive more human authenticity!—
Amit KesarwaniTreeverseSpeakerGetting ML Right in a Complex Data World—
Anand ThangarajuEplusSpeakerThe Janus Effect: Unveiling AI’s Security Dichotomy—
Apurva MisraSentickSpeakerPowering Complex Solutions with Multi-Agent AI—
Debjyoti PaulAmazon Web ServicesWorkshopBuilding Responsible and Fair LLMs: Advancing Safety, Fairness, and Robustness in AI [onsite only]—
Debjyoti PaulAmazon Web ServicesSpeakerBeyond the Benchmark: Evaluating Large Language Models for Real-World Use Case—
Debjyoti PaulAmazon Web ServicesSpeakerThe Power of Distributed Deep Learning—
Dr. Pieter ButeneersEmma LegalSpeakerTurn LLMs into Consistent APIs - Embed the power of ChatGPT in your code base—
Dr. Pieter ButeneersEmma LegalWorkshopWorkshop: ML Strategy Day—
Eduardo GonzalezXpress AISpeakerUnleashing AI Agents: Transforming Workflows with LLMs, Vector Databases, and Automation—
Eduardo GonzalezXpress AISpeakerThe Persistence Paradigm: Engineering Long-Running, Stateful AI Agents—
Het MistryNavy Federal Credit UnionSpeakerLeveraging Generative AI to Assist Individuals in Financial Distress—
Jeremy WilkenFreelancerWorkshopWorkshop: Anticipating the Future with AI—
Joanne RodriguesState of CaliforniaSpeakerRegulating Machine Learning for Ethical Impact—
Nir KaufmanTikalWorkshopAI Agent Bootcamp: LLMs Development with TypeScript - Day 2—
Nir KaufmanTikalWorkshopAI Agent Bootcamp: LLMs Development with TypeScript - Day 1—
Paril GhoriCaterpillar IncSpeakerInnovating with AI: Strategies for Financial Anomaly Detection and Predictive Analytics—
Paul DubsXpress AISpeakerFrom Sci-Fi Dreams to Reality: Our Journey to Build an AI Agent Framework—
Paul DubsXpress AISpeakerOmega Programming: A Developer's Two-Year Journey with Coding Assistants—
Pushkar GargSalesforceSpeakerData Quality Monitoring for ML Models in Production—
Ryan LaflerPremier IncSpeaker[CANCELED] Charting Your Organization’s Machine Learning Roadmap: Strategies for Avoiding Wrong Exits, Detours, and Rush-Hour Hype when Developing Algorithms for AI Workflows—
Shahriyar (Sako) MammadovGladlySpeakerSecuring AI: Lessons from Locking Down LLM Workloads—
Shahriyar (Sako) MammadovGladlySpeakerFrom Hackathons to Production: Platform Lessons from Building 50+ AI Projects—

Sources