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Sep 2026Serving as Area Chair for the EACL 2026 Industry Track.
Aug 2026H-FedSN is accepted at NPJ Artificial Intelligence.
Aug 2026EGT-KG is accepted to EMNLP 2026 Industry Track.
May 2026Received the Google HE Faculty AI Fellowship.
May 2026DCM and MulFCoder, our multi-framework UI2Code papers, are accepted to ICML 2026.
May 2026Three papers accepted in the ACL 2026 cycle: LLM-Guided Tsetlin (Findings), FROST and Are LLMs Economically Viable (Industry Track).
Apr 2026Distribution-aware Re-representations is accepted to SIGIR 2026.
Apr 2026Trustworthy Agent Network is accepted to the KDD 2026 Blue Sky Track.
Jan 2026GRO-RAG is accepted to ICLR 2026.
Jan 2026Our culturally aware harmful meme detection paper is accepted to WWW 2026.
Dec 2025Papers accepted at EACL 2026 (Industry and Findings) and ICASSP 2026 (×4).
Nov 2025Truth, Trust, and Trouble receives a Best Paper Nomination at EMNLP 2025 Industry Track.

Selected Publications

For the complete list, please see my Google Scholar.

Selected venues NPJ AI ×1  ·  ICML ×3  ·  NeurIPS ×2  ·  ICLR ×1  ·  AAAI ×2  ·  KDD ×2  ·  WWW ×1  ·  SIGIR ×1  ·  ACL ×4  ·  EMNLP ×5  ·  ACM MM ×3  ·  CVPR ×1  ·  ICCPS ×1  ·  IPDPS ×1  ·  IPSN ×1

* equal contribution    † corresponding author

2026
H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications
Jiechao Gao*, Yuangang Li*, Jie Wang, Michael Lepech, Yue Zhao, Brad Campbell
NPJ Artificial Intelligence (NPJ AI), 2026
Deterministic Component Mining for Multi-framework UI2Code Generation
Zixiong Yang*, Linxiao Li*, Jiaye Lin, Binrui Wu, Xiaoyu Kang, Jiechao Gao†
International Conference on Machine Learning (ICML), 2026
MulFCoder: Framework-conditioned Multi-agent for MLLM-based Multi-framework Front-end Code Generation
Jie Wu*, Haoran Ma*, Shisong Tang, Yulin Xu, Xiaoyu Kang, Jiechao Gao†
International Conference on Machine Learning (ICML), 2026
GRO-RAG: Gradient-aware Re-rank Optimization for Multi-source Retrieval-Augmented Generation
Siyuan Chen*, Hang Ding*, Kangxiao Yu, Jiechao Gao†
International Conference on Learning Representations (ICLR), 2026
S2D-ALIGN: Shallow-to-Deep Auxiliary Learning for Anatomically-Grounded Radiology Report Generation
Jiechao Gao†, Chang Liu, Yuangang Li
AAAI Conference on Artificial Intelligence (AAAI), 2026
Mitigating hallucinations in large language models via causal reasoning
Yuangang Li*, Yiqing Shen*, Yi Nian, Jiechao Gao, Ziyi Wang, Chenxiao Yu, Shawn Li, Jie Wang, Xiyang Hu†, Yue Zhao†
AAAI Conference on Artificial Intelligence (AAAI), 2026
Trustworthy Agent Network: Trust in Agent Networks Must Be Baked In, Not Bolted On
Yixiang Yao, Yuhang Yao, Xinyi Fan, Jiechao Gao, Jie Wang, Minjia Zhang, Srivatsan Ravi, Carlee Joe-Wong
ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Blue Sky Track (KDD Blue Sky), 2026
They Said Memes Were Harmless-We Found the Ones That Hurt: Decoding Jokes, Symbols, and Cultural References
Sahil Tripathi, Gautam Siddharth Kashyap, Mehwish Nasim, Jian Yang, Jiechao Gao†, Usman Naseem
The ACM Web Conference (WWW), 2026
Distribution-aware Re-representations for Multi-Scenario Recommendations
Qi Sun, Yulin Xu, Zelin Wang, Xiaoyu Kang, Keyan Jin, Jiechao Gao†
International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2026
Are Large Language Models Economically Viable for Industry Deployment?
Abdullah Mohammad, Sushant Kumar Ray, Pushkar Arora, Rafiq Ali, Ebad Shabbir, Gautam Siddharth Kashyap, Jiechao Gao†, Usman Naseem†
Annual Meeting of the Association for Computational Linguistics, Industry Track (ACL Industry), 2026
FROST: Factual Reasoning via Optimized Stochastic Trajectories in Large Language Models during Inference
Soumedhik Bharati*, Ebad Shabbir*, Jiechao Gao†
Annual Meeting of the Association for Computational Linguistics, Industry Track (ACL Industry), 2026
LLM-Guided Semantic Bootstrapping for Interpretable Text Classification with Tsetlin Machines
Jiechao Gao†, Rohan Kumar Yadav, Yuangang Li, Yuandong Pan, Jie Wang, Ying Liu, Michael Lepech
Findings of the Association for Computational Linguistics: ACL 2026 (ACL Findings)
EGT-KG: Evidence-Grounded Typed KG Retrieval for Practical Scientific QA with Small Language Models
Muran Yu, Jiechao Gao, Yuandong Pan, Barney Haoyun Miao, Andrew Carter Lesh, Kincho Law, Jie Wang, Michael Lepech
Conference on Empirical Methods in Natural Language Processing, Industry Track (EMNLP Industry), 2026
Do Clinical Question Answering Systems Really Need Specialised Medical Fine Tuning?
Sushant Kumar Ray, Gautam Siddharth Kashyap, Sahil Tripathi, Nipun Joshi, Vijay Govindarajan, Rafiq Ali, Jiechao Gao†, Usman Naseem
Conference of the European Chapter of the Association for Computational Linguistics, Industry Track (EACL Industry), 2026
Revealing the Truth with ConLLM for Detecting Multi-Modal Deepfakes
Gautam Siddharth Kashyap, Harsh Joshi, Niharika Jain, Ebad Shabbir, Jiechao Gao†, Nipun Joshi, Usman Naseem†
Conference of the European Chapter of the Association for Computational Linguistics (EACL Findings), 2026
CLARITY: A Lightweight Multimodal Transformer for Harmful Content Detection
Gautam Siddharth Kashyap, Niharika Jain, Ebad Shabbir, Harsh Joshi, Usman Naseem, Jiechao Gao†
IEEE Transactions on Artificial Intelligence (IEEE TAI), 2026
LLM-enabled multi-agent framework for automated Scan-to-BIM and Scan-to-Graph reconstruction
Yuandong Pan, Mudan Wang, Jiechao Gao, Jie Wang, Michael D. Lepech, Ioannis Brilakis
Automation in Construction (AutoCon), 2026
Perceiving Creativity in the Age of AI: How Labels, Beliefs, and Familiarity Shape Evaluations of AI-Generated and Human-Created Art
Daniel Koo, Jiechao Gao, Yuandong Pan, Jie Wang, Michael D. Lepech
Workshop on Social Influence in the Era of LLMs (SocialLLM) at ICWSM (ICWSM Workshop), 2026
2025
Calibrating Video Watch-time Predictions with Credible Prototype Alignment
Shisong Tang*, Chao Cui*, Fan Li, Jiechao Gao, Hechang Chen
International Conference on Machine Learning (ICML), 2025
Adaptive Gradient Masking for Balancing ID and MLLM-based Representations in Recommendation
Yidong Wu*, Siyuan Chen*, Binrui Wu, Fan Li, Jiechao Gao†
Conference on Neural Information Processing Systems (NeurIPS), 2025
Leveraging Label Distributions as Anchors to Enhance Video Recommendation
Yulin Xu*, Chao Cui*, Shisong Tang*, Fan Li, Bing Han, Huafeng Cao, Jiechao Gao†, Hechang Chen
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025
Aligning and Balancing ID and Multimodal Representations for Recommendation
Binrui Wu*, Shisong Tang*, Fan Li, Bing Han, Chang Meng, Jingyu Xiao, Jiechao Gao†
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025
SynFix: Dependency-Aware Program Repair via RelationGraph Analysis
Xunzhu Tang*, Jiechao Gao*, Jin Xu*, Tiezhu Sun, Yewei Song, Saad Ezzini, Wendk\^uuni C. Ou\'edraogo, Jacques Klein, Tegawend\'e F. Bissyand\'e
Findings of the Association for Computational Linguistics: ACL 2025 (ACL Findings)
Truth, Trust, and Trouble: Medical AI on the Edge ★ Best Paper Nom.
Mohammad Anas Azeez*, Rafiq Ali*, Ebad Shabbir, Zohaib Hasan Siddiqui, Gautam Siddharth Kashyap, Jiechao Gao†, Usman Naseem†
Conference on Empirical Methods in Natural Language Processing, Industry Track (EMNLP Industry), 2025
LLMs on a Budget? Say HOLA
Zohaib Hasan Siddiqui*, Jiechao Gao*, Ebad Shabbir*, Mohammad Anas Azeez, Rafiq Ali, Gautam Siddharth Kashyap, Usman Naseem†
Conference on Empirical Methods in Natural Language Processing, Industry Track (EMNLP Industry), 2025
AMAS: Adaptively Determining Communication Topology for LLM-based Multi-agent System
Hui Yi Leong, Yuheng Li, Yuqing Wu, Wenwen Ouyang, Wei Zhu†, Jiechao Gao†, Wei Han
Conference on Empirical Methods in Natural Language Processing, Industry Track (EMNLP Industry), 2025
FT-MDT: Extracting Decision Trees from Medical Texts via a Novel Low-rank Adaptation Method
Yuheng Li*, Jiechao Gao*, Wei Han, Wenwen Ouyang, Wei Zhu†, Hui Yi Leong
Conference on Empirical Methods in Natural Language Processing, Industry Track (EMNLP Industry), 2025
The Confidence Paradox: Can LLM Know When It Is Wrong?
Sahil Tripathi, MD Tabrez Nafis, Imran Hussain, Jiechao Gao†
International Joint Conference on Natural Language Processing and AACL (IJCNLP-AACL), 2025
Prototype-Guided Representation Projection for Multi-Domain Multi-Task Recommendation ★ Oral (top 4\%)
Binrui Wu*, Haochen Sui*, Jiaye Lin*, Jiechao Gao†, Ting Xu, Keyan Jin, Xuesong Zhang
ACM International Conference on Multimedia (ACM MM), 2025
From Guesswork to Guarantee: Towards Faithful Multimedia Web Forecasting with TimeSieve
Songning Lai*, Ninghui Feng*, Jiechao Gao*, Hao Wang, Haochen Sui, Xin Zou, Jiayu Yang, Wenshuo Chen, Lijie Hu, Hang Zhao, Xuming Hu, Yutao Yue
ACM International Conference on Multimedia (ACM MM), 2025
Track Any Anomalous Object:A Granular Video Anomaly Detection Pipeline
Yuzhi Huang*, Chenxin Li*†, Haitao Zhang, Zixu Lin, Yunlong Lin, Hengyu Liu, Wuyang Li, Xinyu Liu, Jiechao Gao, Yue Huang†, Xinghao Ding, Yixuan Yuan
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025
Atlas: Ensuring Accuracy for Privacy-Preserving Federated IoT Applications
Jiechao Gao*, Mingyue Tang*, Wenpeng Wang, Tushar Routh, Brad Campbell
ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS), 2025
Enhancing Interpretability in Self-Training with Tsetlin Machines for Mitigating Noisy Pseudo-Labels
Jiechao Gao, Rohan Kumar Yadav, Xinyuan Huang, Jie Wang
IEEE International Conference on Big Data (BigData), 2025
Federated Neural Architecture Search with Model-Agnostic Meta Learning
Xinyuan Huang, Jiechao Gao†, Jie Wang
IEEE International Conference on Big Data (BigData), 2025
Toward Fair and Efficient Neural Architecture Search in Heterogeneous Federated Learning
Xinyuan Huang, Jiechao Gao†
IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2025
U-KAN: Hybrid Spatial-Functional Deep Learning for Tumor Depth Estimation in Fluorescence-Guided Cancer Surgery
Xinyuan Huang, Hikaru Kurosawa, Jack Wunder, Sujit Patil, Jiechao Gao, Karthik Kuber, Jonathan C. Irish, Michael J. Daly
IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2025
FedBCE: Rethinking Clustered Federated Learning for Better Clustering Efficiency
Huaibin Ye, Zuobin Ying, Jiechao Gao, Ximeng Liu, Jianping Cai
International Conference on Knowledge Science, Engineering and Management (KSEM), 2025
Can We Predict Your Next Move Without Breaking Your Privacy?
Arpita Soni, Sahil Tripathi, Gautam Siddharth Kashyap, Manaswi Kulahara, Mohammad Anas Azeez, Zohaib Hasan Siddiqui, Nipun Joshi, Jiechao Gao†
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2025
fReeLoaders: An IoT Ecosystem for Real-Time Deadline-Driven Task Scheduling using Reinforcement Learning
Marshall Clyburn*, Nabeel Nasir*, Md Fazlay Rabbi Masum Billah, Victor Ariel Leal Sobral, Jiechao Gao, Fateme Nikseresht, Brad Campbell
ACM/IEEE Symposium on Edge Computing (SEC), 2025
FinRL Contests: Data-Driven Financial Reinforcement Learning Agents for Stock and Crypto Trading
Keyi Wang, Nikolaus Holzer, Ziyi Xia, Yupeng Cao, Jiechao Gao, Anwar Walid, Kairong Xiao, Xiao-Yang Liu Yanglet
Artificial Intelligence for Engineering (AI for Eng.), 2025
Data Efficient PV based Indoor Event Detection
Tushar Routh, Jiechao Gao, Bradford Campbell
ACM/IEEE International Conference on Cyber-Physical Systems, Poster Track (ICCPS Poster), 2025
Standard Market Environments for Financial Reinforcement Learning
Chunlin Feng, Lijian Huang, Keyi Wang, Yupeng Cao, Ming Zhu, Jiechao Gao, Xiao-Yang Liu
NeurIPS 2025 Workshop on Generative AI in Finance (NeurIPS Workshop), 2025
2024
EGGesture: Entropy-Guided Vector Quantized Variational AutoEncoder for Co-Speech Gesture Generation
Yiyong Xiao*, Kai Shu*, Haoyi Zhang*, Baohua Yin, Wai Seng Cheang, Haoyang Wang, Jiechao Gao†
ACM International Conference on Multimedia (ACM MM), 2024
ScreenSense: Screen Activity Detection in Real-World Environments with Indoor Light Sensors ★ Best Paper Cand.
Tushar Routh, Nurani Saoda, Fateme Nikseresht, Md Fazlay Rabbi Masum Billah, Jiechao Gao, Viswajith Govinda Rajan, Bradford Campbell
ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (BuildSys), 2024
Federated Learning with Knowledge Distillation to Mitigate Catastrophic Forgetting and Data Heterogeneity in IoV Systems
Jiayu Wang, Jiechao Gao†
IEEE International Conference on Big Data (BigData), 2024
FedMetaMed: Federated Meta-Learning for Personalized Medication in Distributed Healthcare Systems
Jiechao Gao†, Yuangang Li
IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2024
FODA-PG for Enhanced Medical Imaging Narrative Generation: Adaptive Differentiation of Normal and Abnormal Attributes
Kai Shu*, Yuzhuo Jia*, Ziyang Zhang, Jiechao Gao†
IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2024
Integrating Consortium Blockchain and Attribute-Based Searchable Encryption for Automotive Threat Intelligence Sharing Model
Tiange Xie, Feng Liu, Jiechao Gao, Yinghui Wang
International Conference on Science of Cyber Security (SciSec), 2024
Fed-LDR: Federated Local Data-infused Graph Creation with Node-centric Model Refinement
Jiechao Gao†, Yuangang Li, Syeda Faiza Ahmed
IEEE ICDM International Workshop on Spatial and Spatiotemporal Data Mining (ICDM SSTDM), 2024
Differentially Private Low-Rank Adaptation of Large Language Model Using Federated Learning
Xiao-Yang Liu, Rongyi Zhu, Daochen Zha, Jiechao Gao, Shan Zhong, Meikang Qiu
ACM Transactions on Management Information Systems (ACM TMIS), 2024
Risk-constrained probabilistic coordination in coupled transmission and distribution system
Aamir Nawaz, Hongtao Wang, Huiting Yang, Hammad Armghan, Jiechao Gao†
Electric Power Systems Research (EPSR), 2024
A Full-Fledged, Multi-Agent System Representing the Architecture of Smart Cities by Balancing Energy With Optimal Electricity Forecasting, Integrating Individual Comfort, and Extracting Financial Gains
M. Mahad Malik, Abdullah Altamimi, Syed Ali Abbas Kazmi, Zafar Ali Khan, Muhammad Waleed Ansari, Kamran Mujahid, Jiechao Gao
IEEE Access, 2024
2023
SRDA: Mobile Sensing based Fluid Overload Detection for End Stage Kidney Disease Patients using Sensor Relation Dual Autoencoder ★ Oral (13.3\%)
Mingyu Tang*, Jiechao Gao*, Guimin Dong, Carl Yang, Bradford Campbell, Brendan Bowman, Jamie Marie Zoellner, Emaad Abdel-Rahman, Mehdi Boukhechba
PMLR Conference on Health, Inference, and Learning (CHIL), 2023
PFDRL: Personalized Federated Deep Reinforcement Learning for Residential Energy Management
Jiechao Gao, Wenpeng Wang, Fateme Nikseresht, Viswajith Govinda Rajan, Bradford Campbell
International Conference on Parallel Processing (ICPP), 2023
Enabling ubiquitous occupancy detection in smart buildings: A wifi ftm-based approach
Wenpeng Wang*, Fateme Nikseresht*, Viswajith Govinda Rajan, Jiechao Gao, Bradford Campbell
International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS), 2023
SSCL: semi-supervised contrastive learning for industrial anomaly detection
Wei Cai, Jiechao Gao
Chinese Conference on Pattern Recognition and Computer Vision (PRCV), 2023
An Instability-Resilient Renewable Energy Allocation System for a Cloud Datacenter
Haiying Shen, Haoyu Wang, Jiechao Gao, Rajkumar Buyya
IEEE Transactions on Parallel and Distributed Systems (TPDS), 2023
Dynamic Datasets and Market Environments for Financial Reinforcement Learning
Xiao-Yang Liu, Ziyi Xia, Hongyang Yang, Jiechao Gao, Daochen Zha, Ming Zhu, Christina Dan Wang, Zhaoran Wang, Jian Guo
Machine Learning Journal (MLJ), 2023
Multi population-based chaotic differential evolution for multi-modal and multi-objective optimization problems
Hafiz Tayyab Rauf, Jiechao Gao*, Ahmad Almadhor, Ali Haider, Yu-Dong Zhang†, Fadi Al-Turjman
Applied Soft Computing (ASC), 2023
Rural consumers financial literacy and access to FinTech services
Morshadul Hasan, Thuhid Noor, Jiechao Gao, Muhammad Usman, Mohammad Zoynul Abedin
Journal of the Knowledge Economy (JKE), 2023
Deep Reinforcement Learning for Cryptocurrency Trading: Practical Approach to Address Backtest Overfitting
Berend Jelmer Dirk Gort*, Xiao-Yang Liu*, Xinghang Sun, Jiechao Gao, Shuaiyu Chen, Christina Dan Wang.
AAAI Bridge Program on AI for Financial Services (AAAI Bridge), 2023
2022
FinRL-Meta: Market Environments and Benchmarks for Data-Driven Financial Reinforcement Learning
Xiao-Yang Liu*, Ziyi Xia*, Jingyang Rui, Jiechao Gao, Hongyang Yang, Ming Zhu, Christina Dan Wang†, Zhaoran Wang, Jian Guo†
Conference on Neural Information Processing Systems, Datasets and Benchmarks Track (NeurIPS D&B), 2022
An Improved Lightweight PUF-PKI Digital Certificate Authentication Scheme for the Internet of Things
Zeeshan Siddiqui, Jiechao Gao†, Muhammad Khurram Khan
IEEE Internet of Things Journal (IoT-J), 2022
Graph Neural Networks in IoT: A Survey
Guimin Dong, Mingyue Tang, Zhiyuan Wang, Jiechao Gao, Sikun Guo, Lihua Cai, Robert Gutierrez, Bradford Campbell, Laura E Barnes, Mehdi Boukhechba
ACM Transactions on Sensor Networks (ACM ToSN), 2022
Identification of Buffalo Breeds Using Self-Activated-Based Improved Convolutional Neural Networks
Yuanzhi Pan, Hua Jin, Jiechao Gao†, Hafiz Tayyab Rauf
Agriculture, 2022
Pfed-ldp: A personalized federated local differential privacy framework for iot sensing data
Jiechao Gao*, Mingyue Tang*, Tianhao Wang, Bradford Campbell
ACM Conference on Embedded Networked Sensor Systems, Poster Track (SenSys Poster), 2022
Residential Energy Management System Using Personalized Federated Deep Reinforcement Learning
Jiechao Gao, Wenpeng Wang, Bradford Campbell
ACM/IEEE International Conference on Information Processing in Sensor Networks, Poster Track (IPSN Poster), 2022
2021
BLE can see: a reinforcement learning approach for RF-based indoor occupancy detection
Md Fazlay Rabbi Masum Billah, Nurani Saoda, Jiechao Gao, Bradford Campbell
ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN), 2021
The smart building privacy challenge
Tong Wu*, Murtadha Aldeer*, Tahiya Chowdhury, Amber Haynes, Fateme Nikseresht, Mahsa Pahlavikhah Varnosfaderani, Jiechao Gao, Arsalan Heydarian, Brad Campbell, Jorge Ortiz
ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (BuildSys), 2021
UbiTrack: Enabling scalable & low-cost device localization with onboard wifi
Wenpeng Wang, Zetian Liu, Jiechao Gao, Nurani Saoda, Bradford Campbell
ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (BuildSys), 2021
Multi-agent reinforcement learning based distributed renewable energy matching for datacenters
Haoyu Wang, Haiying Shen, Jiechao Gao, Kevin Zheng, Xiaoying Li
International Conference on Parallel Processing (ICPP), 2021
FinRL: Deep Reinforcement Learning Framework to Automate Trading in Quantitative Finance
Xiao-Yang Liu, Hongyang Yang, Jiechao Gao, Christina Wang
ACM International Conference on AI in Finance (ICAIF), 2021
FinRL-Meta: A Universe of Near-Real Market Environments for Data-Driven Deep Reinforcement Learning in Quantitative Finance
Xiao-Yang Liu, Jingyang Rui, Jiechao Gao, Liuqing Yang, Hongyang Yang, Zhaoran Wang, Christina Dan Wang, Jian Guo
Conference on Neural Information Processing Systems (NeurIPS Workshop), 2021
A Novel Security Mechanism of 6G for IMD using Authentication and Key Agreement Scheme
M Poongodi, Mounir Hamdi, Jiechao Gao, Hafiz Tayyab Rauf
IEEE Global Communications Conference Workshops (GLOBECOM Workshop), 2021
Decentralized federated learning framework for the neighborhood: a case study on residential building load forecasting
Jiechao Gao, Wenpeng Wang, Zetian Liu, Md Fazlay Rabbi Masum Billah, Bradford Campbell
ACM Conference on Embedded Networked Sensor Systems, AIChallengeIoT Workshop (SenSys Workshop), 2021
2020
Smartly handling renewable energy instability in supporting a cloud datacenter
Jiechao Gao, Haoyu Wang, Haiying Shen
IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2020
Machine learning based workload prediction in cloud computing
Jiechao Gao, Haoyu Wang, Haiying Shen
International Conference on Computer Communications and Networks (ICCCN), 2020
Task failure prediction in cloud data centers using deep learning
Jiechao Gao, Haoyu Wang, Haiying Shen
IEEE Transactions on Services Computing (TSC), 2020
2019
Task failure prediction in cloud data centers using deep learning
Jiechao Gao, Haoyu Wang, Haiying Shen
IEEE International Conference on Big Data (BigData), 2019
Preprints

Public preprints not yet published in a peer-reviewed venue.

Harbor Adapters and Harbor-Index: Infrastructure and a Curated Meta-Dataset for Large-Scale Agentic Evaluation
arXiv
PrivateHub: Contrastive Diffusion Model for Private Sensor-Intensive Environment Data Generation
arXiv
The Orchestration Gap: Why Process Automation Stalls in Operationally Complex Industries
arXiv
Clusters are All You Need: Pre-Training the Tsetlin Machine with Semantic Clusters from Language Models for Interpretability
arXiv
Artificial Intelligence-Aided Digital Twin Design: A Systematic Review and Future Directions
Preprints.org
Book Chapters
DNA computing in cryptography
Jiechao Gao, Tiange Xie
Advances in Computers (Elsevier), 2022
Cloud Computing and Big Data
Hongzhuo Qi, Yi Qin, Jiechao Gao
Harbin Institute of Technology Press, 2020
Introduction of Bigdata and Artificial Intelligence Applications
Jinglan Wu, Dongliang Lin, Jiechao Gao, Ye Xu
University of Electronic Science and Technology of China Press, 2019