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The agenda below is subject to change without notice.

Unless otherwise specified, all events take place at the Royal Sonesta Chicago River North, Gallery Ballroom

Monday, May 6th, 2024
Time Presentation Title Affiliation and Authors Theme
6:30 - 9:30 EVENING NETWORKING EVENT -
Drinks and heavy hors d'oeurves
Royal Sonesta Chicago River North, Canvas Room		 AGIFORS Social Event


Tuesday, May 7th, 2024
Time Presentation Title Affiliation and Authors  Theme
8:00 - 8:45 Registration open (coffee + pastries available)    
8:45 - 9:00 Welcome from AGIFORS and United Airlines AGIFORS   
9:00 - 9:25

Enhancing Robustness to Forecast Errors in Availability Control for Airline Revenue Management

 Lufthansa
T. Gonçalves, B. Almada-Lobo		 Demand Forecasting & Estimation
9:25 - 9:50 Price Endogeneity in Demand Models for Revenue Management  Embry-Riddle Aeronautical University
S. Mumbower		 Demand Forecasting & Estimation
9:50 - 10:15 When good is good enough: A discrete approach to forecast calibration  Amadeus
A. Matson		 Demand Forecasting & Estimation
10:15 - 10:40 Cross Elasticity in Airline Revenue Management United Airlines
A. Bhardwaj, A. Jain		 Demand Forecasting & Estimation
10:40 - 11:00 MORNING BREAK     
11:00 - 11:25

Enhancing Airline RM Measurement Capabilities Through Rigorous and Disciplined Experimentation 

 acmetric
C. Nauerz, P. Gorgi, V. Antsibor		 A/B Testing and Experimentation
11:25 - 11:50 AI-driven Pricing of Airline Seats: Evidence From a Large-scale Online Field Experiment  Lufthansa Group, PROS
A. Furtuna, G. Sarlas, R. Kumar, S. Boluki, D. Walczak		 A/B Testing and Experimentation
11:50 - 12:15 Automated Benefits Estimation for Personalized Recommendations with Experimentation Engines  Sabre
R. Ratliff, B. Rundquist		 A/B Testing and Experimentation
12:15 - 12:30 Sponsor Presentation - The Evolution to Offers and Orders Accelya
T. Radcliffe		 Sponsor Presentation
12:30 - 1:30 LUNCH     
1:30 - 1:55 Transforming Revenue Management: Air India's Journey with Data Science and Advanced Analytics  Air India
K. Jha, A. Rawat		 Applications of AI and ML in RM
1:55 - 2:20 Generative AI & LMM: Transforming Airline RM 
 Fetcherr
U. Yerushalmi, A. Cohen		 Applications of AI and ML in RM
2:20 - 2:45 Revenue forecast: machine learning model vs. analytical approach 
 LOT Polish Airlines
K. Macielak, M. Gorczyca, M. Łukaszewski, P. Radon, D. Śliwiński		 Applications of AI and ML in RM
2:45 - 3:10 Application of Generative AI for Airline Demand Forecasting  Amadeus
T. Fiig, S. Nanty		 Applications of AI and ML in RM
3:10 - 3:30 AFTERNOON BREAK     
3:30 - 3:55 Using Simulations to Improve Revenue Management Systems  Breeze Airways
S. Druzdzel		 Simulations in Revenue Management
3:55 - 4:20 Calibration of networks for competitive RM simulation tools Georgia Tech
L. Garrow
 Simulations in Revenue Management
4:20 - 4:50 Sponsor Presentation acmetric  Sponsor Presentation
4:50 - 5:00 END OF DAY 1    
6:30 - 9:15 Evening Social Event (Boarding 6:15pm)
Dinner Cruise on Lake Michigan - depart Navy Pier		   Social Event


Wednesday, May 8th, 2024
Time Presentation Title Affiliation and Authors Theme
8:00 - 9:00 Morning coffee    
9:00 - 9:45

Keynote Address from Scott Kirby, CEO, United Airlines

 United Airlines
S. Kirby		 Keynote Address
9:45 - 10:10 An Adaptive Data-Driven Approach to Air Cargo Revenue Management PROS
E. Eren		 Air Cargo Revenue Management
10:10 - 10:35 Mid-term decision making in airline cargo using machine learning FLYR
A. Garg, N. Shukla		 Air Cargo Revenue Management
10:35 - 10:55 MORNING BREAK     
10:55 - 11:20

Dynamic pricing for airline ancillary products with machine learning

 Air France
J. Bruno, A. Winckels, S. Ghamloush		 Ancillary and Offer Optimization
11:20 - 11:50 Sponsor Presentation - How data science enables the airline retailing transformation Amadeus
Y.-M. Piana, M. Wittman		 Sponsor Presentation
11:50 - 12:05Sponsor PresentationATPCOSponsor Presentation
12:05 - 1:05 LUNCH     
1:05- 1:30 Unlocking Revenue Potential in Complex Networks using Hybrid Forecasting: Collaborative Study with Amtrak  ExPretio Technologies
K. Pérez, B. Narasimhan, V. de Sousa		 Network Management
1:30 - 1:55 Optimizing Airline Operations through Integrated Flight Scheduling and Revenue Management
 University of Massachusetts, Dartmouth
S. Sibdari, H. Nouinou		 Network Management
1:55 - 2:20 Generating optimal bid prices via reinforcement learning with batch and shape constraints FLYR
A. Gupta, N. Shukla		 Bid Prices and Optimization
2:20 - 2:40AFTERNOON BREAK   
2:40 - 3:05 Independent optimization or not United Airlines
C. Keceli, A. Jain		 Bid Prices and Optimization
3:05 - 3:30 Shadow prices of demand and applications Finnair
F. Nikitin		 Bid Prices and Optimization
3:30 - 3:45 Presentation award voting and conference end AGIFORS


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