activity
20232025
most citedNeurosymbolic Reinforcement Learning and Planning: A Survey

56 citations · 116 across the 10 of their papers we have counts for

collaborators

10 papers

cs.RO2025

Integrating Neurosymbolic AI in Advanced Air Mobility: A Comprehensive Survey

Kamal Acharya, Iman Sharifi, Mehul Lad +2

Neurosymbolic AI combines neural network adaptability with symbolic reasoning, promising an approach to address the complex regulatory, operational, and safety challenges in Advanc…

cs.LG2025★ 4 cited

A Data-Driven Approach to Enhancing Gravity Models for Trip Demand Prediction

Kamal Acharya, Mehul Lad, Liang Sun +1

Accurate prediction of trips between zones is critical for transportation planning, as it supports resource allocation and infrastructure development across various modes of transp…

cs.LG2025★ 3 cited

Neurosymbolic AI for Travel Demand Prediction: Integrating Decision Tree Rules into Neural Networks

Kamal Acharya, Mehul Lad, Liang Sun +1

Travel demand prediction is crucial for optimizing transportation planning, resource allocation, and infrastructure development, ensuring efficient mobility and economic sustainabi…

physics.soc-ph2024

Regional Air Mobility Flight Demand Modeling in Tennessee State

Kamal Acharya, Mehul Lad, Houbing Song +1

Advanced Air Mobility (AAM), encompassing Urban Air Mobility (UAM) and Regional Air Mobility (RAM), offers innovative solutions to mitigate the issues related to ground transportat…

stat.AP2024

Demand Modeling for Advanced Air Mobility

Kamal Acharya, Mehul Lad, Liang Sun +1

In recent years, the rapid pace of urbanization has posed profound challenges globally, exacerbating environmental concerns and escalating traffic congestion in metropolitan areas.…

cs.CR2024★ 3 cited

Decoding Android Malware with a Fraction of Features: An Attention-Enhanced MLP-SVM Approach

Safayat Bin Hakim, Muhammad Adil, Kamal Acharya +1

The escalating sophistication of Android malware poses significant challenges to traditional detection methods, necessitating innovative approaches that can efficiently identify an…

cs.NE2024★ 2 cited

Improving Air Mobility for Pre-Disaster Planning with Neural Network Accelerated Genetic Algorithm

Kamal Acharya, Alvaro Velasquez, Yongxin Liu +3

Weather disaster related emergency operations pose a great challenge to air mobility in both aircraft and airport operations, especially when the impact is gradually approaching. W…

cs.CL2024★ 44 cited

A Survey on Symbolic Knowledge Distillation of Large Language Models

Kamal Acharya, Alvaro Velasquez, Houbing Herbert Song

This survey paper delves into the emerging and critical area of symbolic knowledge distillation in Large Language Models (LLMs). As LLMs like Generative Pre-trained Transformer-3 (…

cs.AI2023★ 56 cited

Neurosymbolic Reinforcement Learning and Planning: A Survey

K. Acharya, W. Raza, C. M. J. M. Dourado +2

The area of Neurosymbolic Artificial Intelligence (Neurosymbolic AI) is rapidly developing and has become a popular research topic, encompassing sub-fields such as Neurosymbolic De…

cs.CV2023★ 4 cited

TMHOI: Translational Model for Human-Object Interaction Detection

Lijing Zhu, Qizhen Lan, Alvaro Velasquez +4

Detecting human-object interactions (HOIs) is an intricate challenge in the field of computer vision. Existing methods for HOI detection heavily rely on appearance-based features,…