The AIAS 2025 Program Committee is pleased to present the papers accepted for inclusion in the conference program. Each submission was subject to a rigorous peer review process conducted by the paper review committee, with careful attention to scholarly quality, originality, and relevance to the conference themes.
From more than sixty submissions, the following papers were selected for presentation. These contributions reflect significant advances in the field and exemplify the high standards of research and academic integrity upheld by AIAS 2025.
| # | Title | Authors |
|---|---|---|
| 6 | Intelligent Coordination Strategies for Multi-Agent\nNavigation in Dynamic Networks | Naga Lalitha Sree Thatavarthi |
| 8 | Evidential deep learning for uncertainty quantification and out-of-distribution detection in jet identification using deep neural networks | Mark Neubauer, Ayush Khot, Xiwei Wang, Avik Roy and Volodymyr Kindratenko |
| 12 | HiPA: Enabling One-Step Text-to-Image Diffusion via\nHigh-Frequency Promotion | Yifan Zhang, Bryan Hooi and Shuicheng Yan |
| 13 | Framework for 10X Acceleration of Open Clinical AI Science | Anjun Chen, Lu Tian and Jorg Rodriguez |
| 16 | FREE: The Foundational Semantic Recognition for Modeling\nEnvironmental Ecosystems | Shiyuan Luo, Juntong Ni, Shengyu Chen, Runlong Yu, Yiqun\nXie, Licheng Liu, Zhenong Jin, Huaxiu Yao and Xiaowei Jia |
| 17 | Identifying High-Risk Cancer Patients on Breast Cancer\nPathology Reports with Large Language Models | Raymond Ng, Trevor Kwan and Jaimie Lee |
| 20 | OmniScience: A Domain-Specialized LLM for Scientific\nReasoning and Discovery | Kai Liu and Vignesh Prabhakar |
| 21 | CRISPR-GPT for Agentic Automation of Gene Editing\nExperiments | Le Cong, Yuanhao Qu, Kaixuan Huang, Henry Cousins and\nMengdi Wang |
| 24 | Agentic Knowledge Graph Traversal in Protein-Protein\nRelation Grounding | Gabriel Reder, Carl Collins, Abbi Abdel Rehim, Larisa\nSoldatova and Ross King |
| 28 | Revisiting SUDEP Risk Prediction via Data Augmentation | Meiyu Li, Juliana Laze, Daniel Friedman, Orrin Devinsky and\nZhe Chen |
| 33 | Multi-Frame Grid Perspective for Traffic Video Captioning\nand Context-Aware VQA | Sanjita Prajapati, Ashutosh Dumka, Rajan Thakulla, Atmadip\nGoswami, Karo Ahmadi Dehrashid and Anuj Sharma |
| 34 | Synthetic AI agents for experimental social science | Colin Camerer and Thomas Henning |
| 35 | A Transformer Foundation Model for Microbiome Science:\nCross-Study Generalization and Automated Discovery | Quintin Pope, Rohan Varma, Christine Tataru, Maude David\nand Xiaoli Fern |
| 37 | Enhancing Urban Accessibility Mapping: Few-Shot and\nZero-Shot Classification with Multimodal Large Language\nModels | Sid Karki |
| 38 | Beyond Brute-Force Context: A Semantic Retrieval Framework\nfor Efficient AI Code Generation | Krishiv Piduri |
| 39 | AI as an Accelerant for the Learning Sciences:\nOpportunities, Risks, and a Vision for the Future | Stephen Hutt |
| 40 | Edge AI Agent Design for Policy-Aware Urban Waste Management | Binrong Zhu, Ruxue Jin, Yang Liu, Guiran Liu, Qun Wang and Phuong Mai Nguyen |
| 41 | Design of a Cross-Layer AI Agent for Secure Spectrum-Aware Network Slicing | Guiran Liu, Binrong Zhu, Yang Liu and Qun Wang |
| 42 | Gaining Insight into Brain Damage and Rehabilitation\nthrough Digital Twins | Risto Miikkulainen and Swathi Kiran |
| 43 | Diffusion with Attention for Inverse Optimization | John Lins and Wei Liu |
| 45 | Ask WhAI: Probing Belief Formation in Role-Primed LLM Agents | Keith Moore, Jun Kim, David Lyu, Jeffrey Heo and Ehsan Adeli |
| 46 | Not Quite Anything: Overcoming SAM’s Limitations for 3D\nMedical Imaging | Keith Moore |
| 48 | Generating 3D Small Binding Molecules Using\nShape-Conditioned Diffusion Models with Guidance | Ziqi Chen, Bo Peng, Tianhua Zhai, Daniel Adu-Ampratwum and\nXia Ning |
| 49 | LARC : Towards Human-level Constrained Retrosynthesis\nPlanning through an Agentic Framework | Frazier N. Baker, Daniel Adu-Ampratwum, Reza Averly, Botao\nYu, Huan Sun and Xia Ning |
| 52 | Evaluating protein binding interfaces with PUMBA | Azam Shirali and Giri Narasimhan |
| 53 | Domain Knowledge Infused Generative Models for Drug\nDiscovery Synthetic Data | Bing Hu, Jong-Hoon Park, Helen Chen, Young-Rae Cho and\nAnita Layton |
| 54 | The Mind Speaks – Voice Biomarkers for Cognitive Impairment\nusing Naturalistic In-Vehicle Audio | Aparna Joshi, Matthew Rizzo and Anuj Sharma |
| 55 | Unveiling Fibromyalgia Research Frontiers:\nTransformer-Based Topic and Sentiment Modeling for\nBiomedical Meta-Analysis | Yetunde Longe-Folajimi, Salem Othman and Leonidas\nDeligiannidis |
| 58 | Large Language Models in Drug Discovery: Insights from\nReasoning and Planning | Shengchao Liu |