Meet ApplyKite Twin, the application assistant that learns with you

Meet your Twin, it learns with you

Your Twin learns with you

Launch week codes:30% off annual Pro20% off monthly Pro

Ends in00h00m00s

Pascal Van Hentenryck

A. Russell Chandler III Chair and Professor

Georgia Institute of Technology

United States

Research Interests

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Explore related searches

Professors in United States

About

Pascal Van Hentenryck is the A. Russell Chandler III Chair and Professor at the Georgia Institute of Technology, USA. His research areas encompass optimization, machine learning, and transportation systems, as evidenced by his recent work on joint rider trip planning, parcel delivery networks, and energy market bidding strategies. He has contributed significantly to the field through articles exploring large-scale power flow optimization and multimodal transit system design.

Articles (30)

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2022

Year:

2022

Year:

UNITED STATES

View details

Nysret Musliu

TU Wien

AUSTRIA

View details

Lucas Kletzander

TU Wien

AUSTRIA

View details

Kevin Dalmeijer

Senior Research Associate

Georgia Institute of Technology

UNITED STATES

View details

Allan I. Levey

Emory University School of Medicine

UNITED STATES

View details

Reem Khir

Assistant Professor

Purdue University

UNITED STATES

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Pascal Van Hentenryck

Research Interests

Make your next move.

Explore related searches

About

Articles (30)

Agentic AI for scaling diagnosis and care in neurodegenerative disease

Optimizing multiple-control Toffoli quantum circuit design with constraint programming

Integrating Column Generation and Large Neighborhood Search for Bus Driver Scheduling with Complex Break Constraints

Contextual Stochastic Optimization for Omnichannel Multicourier Order Fulfillment Under Delivery Time Uncertainty

Bilevel Optimization and Heuristic Algorithms for Integrating Latent Demand into the Design of Large-Scale Transit Systems

Inertia-Constrained Generation Scheduling: Sample Selection, Learning-Embedded Optimization Modeling, and Computational Enhancement

Transit Network Design with Two-Level Demand Uncertainties: A Machine Learning and Contextual Stochastic Optimization Framework

Boosting column generation with graph neural networks for joint rider trip planning and crew shift scheduling

Outbound Load Planning in Parcel Delivery Service Networks Using Machine Learning and Optimization

Strategic bidding in energy markets with gradient-based iterative methods

Self-Supervised Learning for Large-Scale Preventive Security Constrained DC Optimal Power Flow

Weather-informed probabilistic forecasting and scenario generation in power systems

A community-driven optimization framework for redrawing school attendance boundaries

Public Transit for Special Events: Ridership Prediction and Train Scheduling

Polyhedral Relaxations for Optimal Pump Scheduling of Potable Water Distribution Networks

Code and Data Repository for Path-Based Formulations for the Design of On-demand Multimodal Transit Systems with Adoption Awareness

Path-Based Formulations for the Design of On-demand Multimodal Transit Systems with Adoption Awareness

AI4OPT: AI Institute for Advances in Optimization

Code and Data Repository for Polyhedral Relaxations for Optimal Pump Scheduling of Potable Water Distribution Networks

Optimizing Autonomous Transfer Hub Networks: Quantifying the potential impact of self-driving trucks

Redrawing Attendance Boundaries to Promote Racial and Ethnic Diversity in Elementary Schools

Capturing Travel Mode Adoption in Designing On-Demand Multimodal Transit Systems

Compact Optimization Learning for AC Optimal Power Flow

Confidence-Aware Graph Neural Networks for Learning Reliability Assessment Commitments

End-to-End Feasible Optimization Proxies for Large-Scale Economic Dispatch

Learning Regionally Decentralized AC Optimal Power Flows with ADMM

The Bicycle Network Improvement Problem

Spatial Network Decomposition for Fast and Scalable AC-OPF Learning

Spatio-Temporal Point Processes With Attention for Traffic Congestion Event Modeling

Benders Subproblem Decomposition for Bilevel Problems with Convex Follower

Collaborators (10)

Andrew Breithaupt

Shixiang Zhu

James Lah

Nabeel Gillani

Hanyu Zhang

Nysret Musliu

Lucas Kletzander

Kevin Dalmeijer

Allan I. Levey

Reem Khir

Make your next move.