3 citations · 4 across the 7 of their papers we have counts for
7 papers
Column Generation for the Micro-Transit Zoning Problem
Hins Hu, Rishav Sen, Jose Paolo Talusan +3
Along with the rapid development of new urban mobility options like ride-sharing over the past decade, on-demand micro-transit services stand out as a middle ground, bridging the g…
CONSENT: A Negotiation Framework for Leveraging User Flexibility in Vehicle-to-Building Charging under Uncertainty
Rishav Sen, Fangqi Liu, Jose Paolo Talusan +5
The growth of Electric Vehicles (EVs) creates a conflict in vehicle-to-building (V2B) settings between building operators, who face high energy costs from uncoordinated charging, a…
Online Decision-Making Under Uncertainty for Vehicle-to-Building Systems
Rishav Sen, Yunuo Zhang, Fangqi Liu +5
Vehicle-to-building (V2B) systems integrate physical infrastructures, such as smart buildings and electric vehicles (EVs) connected to chargers at the building, with digital contro…
Reinforcement Learning-based Approach for Vehicle-to-Building Charging with Heterogeneous Agents and Long Term Rewards
Fangqi Liu, Rishav Sen, Jose Paolo Talusan +5
Strategic aggregation of electric vehicle batteries as energy reservoirs can optimize power grid demand, benefiting smart and connected communities, especially large office buildin…
Forecasting and Mitigating Disruptions in Public Bus Transit Services
Chaeeun Han, Jose Paolo Talusan, Dan Freudberg +3
Public transportation systems often suffer from unexpected fluctuations in demand and disruptions, such as mechanical failures and medical emergencies. These fluctuations and disru…
An Online Approach to Solving Public Transit Stationing and Dispatch Problem
Jose Paolo Talusan, Chaeeun Han, Ayan Mukhopadhyay +3
Public bus transit systems provide critical transportation services for large sections of modern communities. On-time performance and maintaining the reliable quality of service is…
On Designing Day Ahead and Same Day Ridership Level Prediction Models for City-Scale Transit Networks Using Noisy APC Data
Jose Paolo Talusan, Ayan Mukhopadhyay, Dan Freudberg +1
The ability to accurately predict public transit ridership demand benefits passengers and transit agencies. Agencies will be able to reallocate buses to handle under or over-utiliz…