MLDAS 2026
Machine Learning and Data Analytics Symposium

8-9 February, 2026

Carnegie Mellon University, Doha, Qatar

MLDAS is dedicated to fostering connections between researchers, practitioners, students, and industry experts in the fields of machine learning and data science. MLDAS aims to bridge the gap between academic insights and the practical needs of industry, featuring invited talks by prominent researchers, a panel discussion, and poster sessions by students and junior researchers.

The focus of the 2026 MLDAS edition is on SAFE AND SUSTAINABLE AI. As AI systems grow in scale and influence, ensuring their safe operation while minimizing environmental and energy impact has become a global priority. The symposium will bring together leading researchers, industry leaders, and policymakers to discuss next-generation models, architectures, frameworks, and policies that enable AI systems to remain both safe and environmentally responsible while supporting large-scale societal applications.

Topics include, but are not limited to:

  • Safe and robust AI systems
  • Efficient and sustainable AI systems
  • Green data centers and energy-aware AI infrastructures
  • Sustainable approaches for alignment and fine-tuning large-scale AI models
  • Lifecycle carbon footprint measurement of AI systems
  • Edge AI and distributed efficient computation
  • Policies and governance frameworks for Safe & Green AI
  • Quantum computing and sustainable AI

Organizers

MLDAS has been jointly organized by Boeing and QCRI since 2014.

Chairs:

Mohamed Hefeeda - Acting Research Director, QCRI
Sanjay Chawla - Chief Scientist, QCRI
Dragos Margineantu - AI Chief Technologist, Boeing

Registration and Local Arrangements Chair:

Keivin Isufaj - Software Engineer, QCRI

Keynote Speakers

Speakers from Prior Editions

Event Schedule

Registration and Coffee

Welcome and Opening Remarks

  • Symposium Overview: Mohamed Hefeeda, QCRI
  • Welcome Message: Ahmed Elmagarmid, QCRI
  • Welcome Message: Dragos Margineantu, Boeing
Session 1
Chair: Sanjay Chawla
Divy Agrawal

Private Inference in Large Language Models

Divy Agrawal

 

David Mohaisen

When AI Defends and Betrays: Lessons from Security-Critical Systems

David Mohaisen

 

Coffee Break

Session 2
Chair: Mohamed Hefeeda

QCRI Short Talks

Lunch Break

Session 3
Chair: Dragos Margineantu
Mykel Kochenderfer

Automated Decision Making for Safety Critical Applications

Mykel Kochenderfer

 

Liam Kruse

Probabilistic Safety Validation of Aerospace Systems with Adaptive Importance Sampling

Liam Kruse

 

Break

Session 4
Chair: Issa Khalil
Hai Phan

NOIR: The World’s First End-to-End Encrypted AI Router for LLM Systems

Hai Phan

 

Baochun Li

Reproducible Research Is Both Hard and Helpful: A Case Study on Federated Learning

Baochun Li

 

Registration and Coffee

Session 5
Chair: Amani Alonazi
Eric Feron

Optimization techniques for autonomous systems

Eric Feron

 

Moustafa Amin Youssef

Quantum Efficiency: A Path Toward Sustainable High-Precision Positioning and Beyond

Moustafa Amin Youssef

 

Coffee Break

 

Session 6
Chair: Mashael Al-Sabah

Session 6: QCRI Short Talks

Lunch Break

 

Session 7
Chair: Ferda Ofli
Safa Messaoud

On estimating the entropy from unnormalized densities

Safa Messaoud

 

Carl Henrik Ek

Approximate Bayesian Inference of Composite Functions

Carl Henrik Ek

 

Sponsors

Event Venue

Event venue location info and gallery

Carnegie Mellon University, Doha, Qatar

Contact Us

Address

Qatar Computing Research Institute, Doha, Qatar

Phone Number

+974 44540629