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Ayan Mukhopadhyay

12 accepted papers

2025

ESCORT: Efficient Stein-variational and Sliced Consistency-Optimized Temporal Belief Representation for POMDPs

NeurIPS 2025poster

In Partially Observable Markov Decision Processes (POMDPs), maintaining and updating belief distributions over possible underlying states provides a principled way to summarize action-observation history for effective decision-making under uncertainty. As environments grow more realistic, belief dis…

Cited by 0SourceScholar
2025

NS-Gym: A Comprehensive and Open-Source Simulation Framework for Non-Stationary Markov Decision Processes

NeurIPS 2025poster

Many real-world applications require decision-making where the environmental dynamics evolve over time. These non-stationary environments pose significant challenges to traditional decision-making models, which typically assume stationary dynamics. Non-stationary Markov decision processes (NS-MDPs)…

Cited by 0SourceScholar
2025

Scalable Decision-Making in Stochastic Environments through Learned Temporal Abstraction

ICLR 2025spotlight

Sequential decision-making in high-dimensional continuous action spaces, particularly in stochastic environments, faces significant computational challenges. We explore this challenge in the traditional offline RL setting, where an agent must learn how to make decisions based on data collected throu…

2024

Deploying ADVISER: Impact and Lessons from Using Artificial Intelligence for Child Vaccination Uptake in Nigeria

AAAI 2024technical

More than 5 million children under five years die from largely preventable or treatable medical conditions every year, with an overwhelmingly large proportion of deaths occurring in underdeveloped countries with low vaccination uptake. One of the United Nations' sustainable development goals (SDG 3)…

Cited by 1SourcePDFScholar
2024

Deploying Mobility-On-Demand for All by Optimizing Paratransit Services

IJCAI 2024poster

While on-demand ride-sharing services have become popular in recent years, traditional on-demand transit services cannot be used by everyone, e.g., people who use wheelchairs. Paratransit services, operated by public transit agencies, are a critical infrastructure that offers door-to-door transporta…

2024

Multi-Agent Reinforcement Learning with Hierarchical Coordination for Emergency Responder Stationing

ICML 2024poster

An emergency responder management (ERM) system dispatches responders, such as ambulances, when it receives requests for medical aid. ERM systems can also proactively reposition responders between predesignated waiting locations to cover any gaps that arise due to the prior dispatch of responders or…

Cited by 2SourcePDFScholar
2024

SmartTransit.AI: A Dynamic Paratransit and Microtransit Application

IJCAI 2024poster

New rideshare and shared mobility services have transformed urban mobility in recent years. Such services have the potential to improve efficiency and reduce costs by allowing users to share rides in high-capacity vehicles and vans. Most transit agencies already operate various ridepooling services,…

Cited by 0SourcePDFScholar
2022

ADVISER: AI-Driven Vaccination Intervention Optimiser for Increasing Vaccine Uptake in Nigeria

IJCAI 2022poster

More than 5 million children under five years die from largely preventable or treatable medical conditions every year, with an overwhelmingly large proportion of deaths occurring in under-developed countries with low vaccination uptake. One of the United Nations' sustainable development goals (SDG 3…

2022

Offline Vehicle Routing Problem with Online Bookings: A Novel Problem Formulation with Applications to Paratransit

IJCAI 2022poster

Vehicle routing problems (VRPs) can be divided into two major categories: offline VRPs, which consider a given set of trip requests to be served, and online VRPs, which consider requests as they arrive in real-time. Based on discussions with public transit agencies, we identify a real-world problem…

2021

WildfireDB: An Open-Source Dataset Connecting Wildfire Occurrence with Relevant Determinants

NeurIPS 2021poster

Modeling fire spread is critical in fire risk management. Creating data-driven models to forecast spread remains challenging due to the lack of comprehensive data sources that relate fires with relevant covariates. We present the first comprehensive and open-source dataset that relates historical fi…

Cited by 12SourceScholar
2020

Robust Spatial-Temporal Incident Prediction

UAI 2020poster

Spatio-temporal incident prediction is a central issue in law enforcement, with applications in fighting crimes like poaching, human trafficking, illegal fishing, burglaries and smuggling. However, state of the art approaches fail to account for evasion in response to predictive models, a common fo…

Cited by 6SourcePDFScholar