7 citations · 43 across the 20 of their papers we have counts for
21 papers
Climate AI for Corporate Decarbonization Metrics Extraction
Aditya Dave, Mengchen Zhu, Dapeng Hu +1
Corporate Greenhouse Gas (GHG) emission targets are important metrics in sustainable investing [12, 16]. To provide a comprehensive view of company emission objectives, we propose…
On Mobility Equity and the Promise of Emerging Transportation Systems
Heeseung Bang, Aditya Dave, Filippos N. Tzortzoglou +2
This paper introduces a mobility equity metric (MEM) for evaluating fairness and accessibility in multi-modal intelligent transportation systems. The MEM simultaneously accounts fo…
A Mobility Equity Metric for Multi-Modal Intelligent Transportation Systems
Heeseung Bang, Aditya Dave, Filippos N. Tzortzoglou +1
In this paper, we introduce a metric to evaluate the equity in mobility and a routing framework to enhance the metric within multi-modal intelligent transportation systems. The mob…
Safe Merging in Mixed Traffic with Confidence
Heeseung Bang, Aditya Dave, Andreas A. Malikopoulos
In this letter, we present an approach for learning human driving behavior, without relying on specific model structures or prior distributions, in a mixed-traffic environment wher…
A Framework for Effective AI Recommendations in Cyber-Physical-Human Systems
Aditya Dave, Heeseung Bang, Andreas A. Malikopoulos
Many cyber-physical-human systems (CPHS) involve a human decision-maker who may receive recommendations from an artificial intelligence (AI) platform while holding the ultimate res…
Stochastic Control with Distributionally Robust Constraints for Cyber-Physical Systems Vulnerable to Attacks
Nishanth Venkatesh, Aditya Dave, Ioannis Faros +1
In this paper, we investigate the control of a cyber-physical system (CPS) while accounting for its vulnerability to external attacks. We formulate a constrained stochastic problem…
A Q-learning Approach for Adherence-Aware Recommendations
Ioannis Faros, Aditya Dave, Andreas A. Malikopoulos
In many real-world scenarios involving high-stakes and safety implications, a human decision-maker (HDM) may receive recommendations from an artificial intelligence while holding t…
Routing in Mixed Transportation Systems for Mobility Equity
Heeseung Bang, Aditya Dave, Andreas A. Malikopoulos
This letter proposes a routing framework in mixed transportation systems for improving mobility equity. We present a strategic routing game that governs interactions between compli…
Performance-Sensitive Potential Functions for Efficient Flow of Connected and Automated Vehicles
Filippos N. Tzortzoglou, Dionysios Theodosis, Aditya Dave +1
Connected and automated vehicles (CAVs) provide the most intriguing opportunity for enabling users to monitor transportation network conditions and make better decisions for improv…
Connected and Automated Vehicles in Mixed-Traffic: Learning Human Driver Behavior for Effective On-Ramp Merging
Nishanth Venkatesh, Viet-Anh Le, Aditya Dave +1
Highway merging scenarios featuring mixed traffic conditions pose significant modeling and control challenges for connected and automated vehicles (CAVs) interacting with incoming…
Worst-Case Control and Learning Using Partial Observations Over an Infinite Time-Horizon
Aditya Dave, Ioannis Faros, Nishanth Venkatesh +1
Safety-critical cyber-physical systems require control strategies whose worst-case performance is robust against adversarial disturbances and modeling uncertainties. In this paper,…
A Study of an Atomic Mobility Game With Uncertainty Under Prospect Theory
Ioannis Vasileios Chremos, Heeseung Bang, Aditya Dave +2
In this paper, we present a study of a mobility game with uncertainty in the decision-making of travelers and incorporate prospect theory to model travel behavior. We formulate a m…
Approximate Information States for Worst-Case Control and Learning in Uncertain Systems
Aditya Dave, Nishanth Venkatesh, Andreas A. Malikopoulos
In this paper, we investigate discrete-time decision-making problems in uncertain systems with partially observed states. We consider a non-stochastic model, where uncontrolled dis…
On Robust Control of Partially Observed Uncertain Systems with Additive Costs
Aditya Dave, Nishanth Venkatesh, Andreas A. Malikopoulos
In this paper, we consider the problem of optimizing the worst-case behavior of a partially observed system. All uncontrolled disturbances are modeled as finite-valued uncertain va…
Approximate Information States for Worst-case Control of Uncertain Systems
Aditya Dave, Nishanth Venkatesh, Andreas A. Malikopoulos
In this paper, we investigate a worst-case-scenario control problem with a partially observed state. We consider a non-stochastic formulation, where noises and disturbances in our…
Decentralized Control of Two Agents with Nested Accessible Information
Aditya Dave, Nishanth Venkatesh, Andreas A. Malikopoulos
In this paper, we investigate a decentralized stochastic control problem with two agents, where a part of the memory of the second agent is also available to the first agent at eac…
On Decentralized Minimax Control with Nested Subsystems
Aditya Dave, Nishanth Venkatesh, Andreas A. Malikopoulos
In this paper, we investigate a decentralized control problem with nested subsystems, which is a general model for one-directional communication amongst many subsystems. The noises…
A Dynamic Program for a Team of Two Agents with Nested Information
Aditya Dave, Andreas A. Malikopoulos
In this paper, we investigate a sequential dynamic team problem consisting of two agents with a nested information structure. We use a combination of the person-by-person and presc…
Social Media and Misleading Information in a Democracy: A Mechanism Design Approach
Aditya Dave, Ioannis Vasileios Chremos, Andreas A. Malikopoulos
In this paper, we present a resource allocation mechanism for the problem of incentivizing filtering among a finite number of strategic social media platforms. We consider the pres…
The Prescription Approach to Decentralized Stochastic Control with Word-of-Mouth Communication
Aditya Dave, Andreas A. Malikopoulos
In this paper we analyze a network of agents that communicates through word of mouth. In a word-of-mouth communication system, every agent communicates with its neighbors with dela…
Structural Results for Decentralized Stochastic Control with a Word-of-Mouth Communication
Aditya Dave, Andreas A. Malikopoulos
In this paper, we analyze a network of agents that communicate through the ``word of mouth," in which, every agent communicates only with its neighbors. We introduce the prescripti…