MLconf NYC 2024 Conference Agenda
7:00AM-7:50AM
Registration & Light Breakfast
7:50-8:00
Welcome & Announcements
8:00-8:30
Dr. Ali Arsanjani: Essential Ingredients in Scaling your Organization for Scalable ML
8:30-9:00
Mahnoosh Mehrabani: NLU at Scale: Methods and Applications of Few-Shot Learning in Conversational AI
9:00-9:30
Binwei Yang: Semantic Label Representation with An Application on Multimodal Product Categorization
9:30-10:00
Jay Wang: Industrial Applications of Machine Learning in Search and Recommendations
10:00-10:15
Quick Break
10:15-10:45
Armand Ruiz: AI Factsheets as Industry Standard
10:45-11:15
Vinutha Kallem: Driving Autonomous Vehicles Forward with Real World Applications
11:15-11:45
Dr. Mehdi Bahrami: A Generative AutoML for Tabular Data
11:45-12:15
Dr. Sherin Mathews: Federated Learning: Balancing the Thin Line Between Data Intelligence and Privacy
12:15-1:30
Lunch
1:30-2:00
Matthew Schreiner: Two competing applications of non-parametric inference in practice – “Lazy” vs “Strict” Bootstrapping
2:00-2:30
Jonathan Jin: Empowering Traceable and Auditable ML in Production at Spotify with Hendrix
2:30-3:00
Networking
3:00-3:30
Eitan Anzenberg: Using Deep Learning to Understand Documents
3:30-3:45
Quick Break
3:45-4:15
Dr. Lei Tang: Scaling up Lyft’s Growth via Causal ML and Bandits
4:15-4:45
Zachary Hanif: Learnings from the Frontier: Building Multi-Tenant Compute Systems in the Enterprise
4:45-5:15
Leah McGuire: Humans helping machines help humans run machines: Combining automation and domain knowledge to enable productized modeling of the growth of biologics
5:15-5:30
Closing Remarks