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CREDIT Center / Publications

 

2023

D. Adesina, C. Hsieh, Y. E. Sagduyu, and L. Qian (2023). “Adversarial Machine Learning in Wireless Communications using RF Data: A Review,” in IEEE Communications Surveys & Tutorials, vol. 25, no. 1, pp. 77-100, First quarter 2023, doi: 10.1109/COMST.2022.3205184.

X. Dong, L. Nwosu, S. Reza, and L. Qian (2023). “Effective Screening and Face Mask Detection for COVID Spread Mitigation using Deep Learning and Edge Devices,” book chapter in “Advanced AI and Internet of Health Things for Combating Pandemics,” Springer Nature

L. Nwosu, X. Li, S. Kim, L. Qian, X. Dong (2023). “Proformer-based Ensemble Learning for Gene Expression Prediction,” International Conference on Intelligent Biology and Medicine (ICIBM)

Sarker, X. Dong, L. Qian (2023). “Ensemble BERT for Medication Event Classification on Electronic Health Records,” International Conference on Intelligent Biology and Medicine (ICIBM).

S. Sarker, L. Qian, X. Dong (2023).  “Medical Data Augmentation via ChatGPT: A Case Study on Medication Identification and Medical Events Classification”, The IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI) 2023.

T. Abdul-Quddoos, X. Dong, L. Qian (2023). “Systematic Comparative Analysis of Pre-trained Large Language Models on Contextualized Medication Event Extraction”, The IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI) 2023.

O. Fagbohungbe and L. Qian (2023). “Impact of Learning Rate on Noise Resistant Property of Deep Learning Models” Future Technologies Conference (FTC), November 2-3, 2023, San Francisco, United States.

T. Akinola, X. Li, R. Wilkins, P. Obiomon, L. Qian (2023). “Inverse Quantum Fourier Transform Inspired Algorithm for Unsupervised Image Segmentation,” IPDPS Workshop on Quantum Computing Algorithms, Systems, and Applications (Q-CASA), May 15, 2023, Tampa, FL, arXiv 2301.04705

Y. Zhang, H. Xu, L. Qian (2023). “Joint Optimal Placement and Dynamic Resource Allocation for multi-UAV Enhanced Reconfigurable Intelligent Surface Assisted Wireless Network,” The Proceedings of IEEE ROBOCOM 2023 (Best Paper Award).

Y. Zhang, A. Eroglu, B. Yang, L. Qian, H. Xu (2023). “Reinforcement Learning based Optimal Dynamic Resource Allocation for RIS-aided MIMO Wireless Network with Hardware Limitations,” International Conference on Computing, Networking and Communications (ICNC 2023).

K. Mensah-Bonsu, B. Yang, A. Eroglu, H. Xu, L. Qian (2023). “Polarization Analysis of Reflectarray Unit Elements Using Characteristic Modes,” 2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (USNC-URSI).

X. Dong, L. Qian, X. Li, P. Obiomon, Y. Fu, Z. Xiao, S. Yang, N. Barnes (2023). “Improving Programming Skills of Engineering Students at HBCUs Using AI enhanced Online Personalized Adaptive Learning Tools,” 2023 Gulf Southwest Region ASEE Conference, March, 2023, Denton, TX.

2022

O. Fagbohungbe, S. Reza, X. Dong, L. Qian (2022). “Efficient Privacy Preserving Edge Intelligent Computing Framework for Image Classification in IoT,” IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 6, no. 4, pp. 941-956, Aug. 2022, doi: 10.1109/TETCI.2021.3111636.

O. Onasami, M. Feng, H. Xu, M. Haile, L. Qian. (2022). “Underwater Acoustic Communication Channel Modeling using Reservoir Computing,” IEEE Access, vol. 10, pp. 56550-56563, 2022, doi: 10.1109/ACCESS.2022.3177728.

B. Yang, X. Cao, C. Huang, C. Yuen, M. Renzo, Y. Guan, D. Niyato, L. Qian, and M. Debbah (2022). “Federated Spectrum Learning for Reconfigurable Intelligent Surfaces-Aided Wireless Edge Networks,” IEEE Transactions on Wireless Communications, doi: 10.1109/TWC.2022.3178445.

X. Dong, S. Chowdhury, U. Victor, X. Li, L. Qian. (2022). “Semi-supervised Deep Learning for Cell Type Identification from Single-Cell Transcriptomic Data,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, doi: 10.1109/TCBB.2022.3173587.

O. Fagbohungbe, L. Qian (2022). “The Effect of Batch Normalization on Noise Resistant Property of Deep Learning Models,” IEEE Access.

D. Adesina, C. Hsieh, Y. E. Sagduyu, and L. Qian (2022). “Adversarial Machine Learning in Wireless Communications using RF Data: A Review,” IEEE Communications Surveys and Tutorials.

L. Nwosu, X. Dong, X. Li, S. Kim, and L. Qian (2022). “Calibrated Bagging Deep Learning for Image Semantic Segmentation: A Case Study on COVID-19 Chest X-ray Image,” PLoS ONE.

X. Dong and L. Qian (2022). “Semi-supervised Bidirectional RNN for Misinformation Detection,”  Machine Learning with Applications.

X. Dong, S. Sarker, L. Qian (2022). “Integrating Human-in-the-loop into Swarm Learning for  Decentralized Fake News Detection,” The International Conference on Intelligent Data Science Technologies and Applications (IDSTA2022), Sep. 5-7, 2022. San Antonio, Texas, USA.

J. Olamofe, X. Dong, L. Qian, E. Shields (2022). “Performance Evaluation of Data Augmentation for Object Detection in XView Dataset,” The International Conference on Intelligent Data Science Technologies and Applications (IDSTA2022), Sep. 5-7, 2022. San Antonio, Texas, USA.

O. Fagbohungbe and L. Qian (2022). “L1 Batch Normalization and Noise Resistant Property of Deep Learning Models,” 2022 International Joint Conference on Neural Networks (IJCNN), 2022.

2021

J. Bassey, X. Li, and L. Qian (2021). “Device Authentication Codes based on RF Fingerprinting using Deep Learning,” EAI Endorsed Transactions on Security and Safety.

L. Nwuso, X. Li, L. Qian, S. Kim, and X. Dong (2021). “Semi-supervised Learning for COVID-19 Image Classification via ResNet,” EAI Endorsed Transactions on Bioengineering and Bioinformatics.

B. Yang, X. Cao, C. Yuen and L. Qian (2021). “Offloading Optimization in Edge Computing for Deep-Learning-Enabled Target Tracking by Internet of UAVs,” in IEEE Internet of Things Journal, vol. 8, no. 12, pp. 9878-9893, June 2021, doi: 10.1109/JIOT.2020.3016694.

B. Yang, X. Cao, C. Yuen and L. Qian (2021). “Offloading Optimization in Edge Computing for Deep-Learning-Enabled Target Tracking by Internet of UAVs,” in IEEE Internet of Things Journal, vol. 8, no. 12, pp. 9878-9893, June 2021, doi: 10.1109/JIOT.2020.3016694.

2020

B. Yang, X. Cao, J. Bassey, X. Li, and L. Qian (2020). “Computation Offloading in Multi-Access Edge Computing Networks: A Multi-Task Learning Approach”, IEEE Transactions on Mobile Computing.

B. Yang, X. Cao, X. Li, C. Yuen, and L. Qian (2020). “Lessons Learned from Accident of Autonomous Vehicle Testing: An Edge Learning-aided Offloading Framework”, IEEE Wireless Communications Letters.

J. Bassey, X. Li, and L. Qian (2020). “Device Authentication Codes based on RF Fingerprinting using Deep Learning”, arXiv:2004.08742, submitted to IEEE Transactions on Information Forensics & Security.

C. Kotteti, X. Dong, and L. Qian (2020). “Ensemble Deep Learning on Time-Series Representation of Tweets for Rumor Detection in Social Media, arXiv:2004.12500, submitted to Progress in Artificial Intelligence.

D. Adesina, J. Bassey, and L. Qian (2020). “Practical Deep Radio Frequency Spectrum Learning for Future Wireless Communications Systems”, submitted to IEEE Access.

O. Fagbohungbe, S. Reza, X. Dong, L. Qian (2020). “Efficient Privacy Preserving Edge Computing Framework for Image Classification”, submitted to IEEE Access.

X. Cao, Z. Song, B. Yang, L. Qian, Z. Han (2020). “Full-Duplex MAC in LAA/Wi-Fi Coexistence Networks: Design, Modeling and Analysis”, IEEE Transactions on Wireless Communications.

B. Yang, X. Cao, X. Li, Q. Zhang, and L. Qian (2020). “Mobile Edge Computing based Hierarchical Machine Learning Tasks Distribution for Industrial Internet-of-Things”, IEEE Internet-of-Things Journal, Vol. 7, No. 3, pp.2169-2180, March 2020.

X. Cao, Z. Song, B. Yang, M. ElMossallamy, L. Qian, and Zhu Han (2020). “A Distributed Ambient Backscatter MAC Protocol for Internet-of-Things Networks”, IEEE Internet-of-Things Journal, Vol. 7, No. 2, pp.1488-1501, Feb 2020.

X. Dong, S. Chowdhury, U. Victor, X. Li, L. Qian (2020). “Cell Type Identification from Single-Cell Transcriptomic Data via Semi-supervised Learning”, arXiv:2005.03994, submitted to Bioinformatics.

2019

M. Feng, L. Qian, H. Xu (2019). “Multi-Autonomous Robot Enhanced Ad-hoc Network under Uncertain and Vulnerable Environment”, IEICE Transactions, Vol.E102-B, No.10, Oct. 2019.

B. Yang, X. Cao, Z. Han, and L. Qian (2019). “A Machine Learning Enabled MAC Framework for Heterogeneous Internet-of-Things Networks.” IEEE Transactions on Wireless Communications, 18(7), 2019.

S. O. Bamgbose, X. Li, and L. Qian (2019). “Neural Network Based Nonlinear Adaptive Controller Design for a Class of Bilinear System”, IET Cognitive Computation and Systems.

B. Li, L. Qian, D. Qiao, S. Shao (2019). “MAC for the Next Generation Networks in Unlicensed Band”,Mobile Networks and Applications.

X. Dong, S. Chowdhury, L. Qian, X. Li, Y. Guan, J. Yang, and Q. Yu (2019). “Deep learning for named entity recognition on Chinese electronic medical records: combining deep transfer learning with multitask bi-directional lstm rnn,” PLoS ONE 14(5): e0216046.

S. O. Bamgbose, X. Li, and L. Qian (2019). “Trajectory tracking control optimization with neural network for autonomous vehicles,” Advances in Science, Technology and Engineering Systems Journal, Vol. 4, No. 1, pp.217-224.

X. Dong, H. Wu, Y. Yan, and L. Qian (2019). “Hierarchical Transfer Convolutional Neural Networks for Image Classification”, IEEE International Conference on Big Data, Dec 9-12, Los Angeles, CA.

X. Cao, Z. Song, B. Yang, X. Du, L. Qian, and Z. Han (2019). “Deep Reinforcement Learning MAC for Backscatter Communication Relying on Wi-Fi Architecture”, IEEE Global Communications Conference (GLOBECOM), Dec 9-13, Waikoloa, HI, USA.

N.R. Ranasinghe, L. Huang, T. Clee and J. Kemp (2019). “A machine learning approach to discriminate between explosions and earthquakes,” AGU 2019.

C. Kotteti, X. Dong, and L. Qian (2019). “Rumor Detection on Time-Series of Tweets via Deep Learning”, IEEE Military Communications Conference (Milcom), Nov 12-14, Norfolk, VA, USA.

D. Adesina, J. Bassey, and L. Qian (2019). “Practical Radio Frequency Learning for Future Wireless Communication Systems”,IEEE Military Communications Conference (Milcom), Nov 12-14, Norfolk, VA, USA.

D. Adesina, O. Adagunodo, X. Dong, and L. Qian (2019). “Aircraft Location Prediction Using Deep Learning”, IEEE Military Communications Conference (Milcom), Nov 12-14, Norfolk, VA, USA.

Z. Zhou, L. Qian, and H. Xu (2019). “Intelligent Decentralized Dynamic Power Allocation in MANET at Tactical Edge based on Mean-Field Game Theory”, IEEE Military Communications Conference (Milcom), Nov 12-14, Norfolk, VA, USA.

I. Khatri, X. Dong, J. Attia and L. Qian (2019). “Short-term Load Forecasting on Smart Meter via Deep Learning,” 51st North American Power Symposium(NAPS), October 13-15, Wichita, Kansas, USA.

L. Huang (2019). “Full Waveform Inversion Performance Analysis on GPU Clusters,” OpenMPCon 2019, Auckland, New Zealand, Sep. 10, 2019.

H. Wu, Z. Zhou, M. Feng, Y. Yan, H. Xu, and L. Qian (2019). “Real-time Single Object Detection on The UAV,”International Conference on Unmanned Aircraft Systems, ICUAS’19, June 11-14, Atlanta, GA, USA.

B. Yang, X. Cao, X. Li, T. Kroecker, and L. Qian (2019). “Joint Communication and Computing Optimization for Hierarchical Machine Learning Task Distribution”, IEEE Symposium on Computers and Communications (ISCC 2019), June 30 – July 3, Barcelona, Spain.

J. Bassey, D. Adesina, X. Li, L. Qian, A. Aved, T. Kroecker (2019). “Intrusion Detection for IoT Devices based on RF Fingerprinting using Deep Learning”, The Fourth International Conference on Fog and Mobile Edge Computing (FMEC 2019), June 10-13, Rome, Italy.

J. Bassey, X. Li, and L. Qian (2019). “An Experimental Study of Multi-Layer Multi-Valued Neural Network”, The 2nd International Conference on Data Intelligence and Security (ICDIS 2019)

B. Yang, X. Cao, J. Bassey, X. Li, T. Kroecker, and L. Qian (2019). “Computation Offloading in Multi-Access Edge Computing Networks: A Multi-Task Learning Approach”, IEEE International Conference on Communications (ICC 2019), May 20-24, Shanghai, China.

B. Yang, H. Wu, X. Cao, X. Li, T. Kroecker, Z. Han, and L. Qian (2019). “Intelli-Eye: An UAV Tracking System with Optimized Machine Learning Tasks Offloading,” IEEE International Conference on Computer Communications (INFOCOM) Workshop 2019, Apr 29-May 2, Paris, France.

X. Cao, Z. Song, B. Yang, M. ElMossallamy, L. Qian, and Z. Han (2019). “A Distributed MAC Using Wi-Fi to Assist Sporadic Backscatter Communications,” IEEE International Conference on Computer Communications (INFOCOM) Workshop 2019, Apr 29-May 2, Paris, France.

2018

H. Jafari, X. Li, L. Qian, A. Aved, T. Kroecker (2018). “Efficient Processing of Big Uncertain Data from Multiple Sensors with High Order Multi-Hypothesis: An Evidence Theoretic Approach”, International Journal Paper of Big Data Intelligence, Vol.5(3), pp.177-190.

Journal Paper

J. Wang, Y. Gong, L. Qian, R. Jäntti, M. Pan, Z. Han (2018). “Data-Driven Optimization Based Primary Users’ Operational Privacy Preservation”, IEEE Transactions on Cognitive Communications and Networking, Vol.4(2), pp.357-367.

Journal Paper

S. Chowdhury, X. Dong, L. Qian, X. Li, Y. Guan, J. Yang, Q. Yu (2018). “A Multitask bi-directional RNN Model for Named Entity Recognition on Electronic Medical Records”, BMC Bioinformatics

X. Cao, Z. Song, B. Yang, L. Qian, Z. Han (2018). “Full-Duplex MAC in LAA/Wi-Fi Coexistence Networks: Design, Modeling and Analysis”, submitted to IEEE Transactions on Wireless Communications.

Journal paper

R. Ren, Y. Yang, P. Johnson (2018). “Design and Implementation of VetLink, a Livestock Medical System”, submitted toIEEE Potentials

Journal paper

S. O. Bamgbose, X. Li, and L. Qian (2018). “Control of complex biological systems utilizing the neural network predictor,” Computational Intelligence and Optimization Methods for Control Engineering. Springer.

Book Chapter

C. Kotteti, X. Dong, and L. Qian (2018). “Multiple Time-Series Data Analysis for Rumor Detection on Social Media”, IEEE International Conference on Big Data, Dec 10-13, 2018, Seattle, WA, USA

Conference Paper

Yongxiang Shi, Lei Huang, Xishuang Dong, Tao Liu, Jieyuan Ning (2018). “Fully convolutional neural network’s application on fault detection,” in the Proceedings of the 2018 American Geophysical Union (AGU) Fall Meeting, Washington, D.C., Dec 10-14.

Conference Paper

H. Jafari, O. Omotere, D. Adesina, H. Wu, L. Qian (2018). “IoT Devices Fingerprinting Using Deep Learning”, IEEE Military Communication Conference (MILCOM), October 29-31, 2018, Los Angeles, CA, USA

Conference Paper

M. Feng, L. Qian, H. Xu (2018). “Multi-Robot Enhanced MANET Intelligent Routing at Uncertain and Vulnerable Tactical Edge”, IEEE Military Communication Conference (MILCOM), October 29-31, 2018, Los Angeles, CA, USA.

Conference Paper

Lei Huang (2018). “Generate Big Data to Enable Deep Learning for Seismic Inversion,” the 2018 Rice Data Science Conference, Houston, TX, Oct. 14-15, 2018.

Conference Paper

O. Omotere, J. Fuller, L. Qian, and Z. Han (2018). “Spectrum Occupancy Prediction in Coexisting Wireless Systems using Deep Learning”, IEEE 88th Vehicular Technology Conference (VTC 2018), August 27–30, 2018, Chicago, IL.

Conference Paper

B. Yang, X. Cao, and L. Qian (2018). “A Scalable MAC Framework for Internet of Things Assisted by Machine Learning”, IEEE 88th Vehicular Technology Conference (VTC 2018), August 27–30, 2018, Chicago, IL.

Conference Paper

C. Kotteti, X. Dong, N. Li and L. Qian (2018). “Fake News Detection Enhancement with Data Imputation”, 4th Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress, August 12-15, 2018, Athens, Greece.

Conference Paper

Lei Huang, Miguel Polanco, Ted Clee (2018). “Initial Experiments on Improving Seismic Data Inversion with Deep Learning,” 2018 New York Scientific Data Summit (NYSDS), Brookhaven National Laboratory, Upton, NY, Aug. 6-8, 2018.

Conference Paper

J. Bassey, X. Li, L. Qian, A. Aved, T. Kroecker (2018). “Efficient Computing of Dempster-Shafer Theoretic Conditionals for Big Hard/Soft Data Fusion”, 21st International Conference on Information Fusion (FUSION 2018), July 10-14, 2018, Cambridge, UK

Conference Paper

S. Bamgbose, X. Li, L. Qian (2018). “Neural Network Optimized Controller for Motion and Position Control in Autonomous Systems”, 14th IEEE International Conference on Control & Automation (ICCA 2018), June 11-16, 2018, Anchorage, Alaska

Conference Paper

P. Johnson et. al. (2018). “An Innovative New Approach to Animal Care”,IEEE Global Humanitarian Technology Conference (GHTC), accepted.

Conference Paper

Chowdhury, X. Dong, L. Qian, X. Li, Y. Guan, J. Yang, Q. Yu (2018). “A Multitask bi-directional RNN Model for Named Entity Recognition on Electronic Medical Records”,International Conference on Intelligent Biology and Medicine (ICIBM 2018), Los Angeles, CA (NSF Student Travel Award).

Conference Paper

L. Huang, D. Mistry, X. Dong (2018). “Apply Generative Adversarial Networks for Synthetic Seismic Data Generation,” submitted to Workshop on Data Mining for Geophysics and Geology (DMG2), SIAM Conference on Data Mining (SDM2018).

Conference Paper

R. Sobayo, H.Wu, R. Ray and L. Qian (2018). “Integration of Convolutional Neural Network and Thermal Images into Soil Moisture Estimation”, International Conference on Data Intelligence and Security (ICDIS 2018), April 8-10, South Padre Island, USA.

Conference Paper

“Multi-Sensor Big Time-Series Data Analytics based on Evidence Theory”, PhD Dissertation by H. Jafari, Prairie View A&M University, May 2018.

PhD Dissertation

“Drug Effect Modeling For Cancer Treatment Using Hybrid Systems Control Approach”, PhD Dissertation by W. Oduola, Prairie View A&M University, August 2018.

PhD Dissertation

“Electric Load Forecasting on Embedded Devices using Machine Learning”, MS Thesis by Devin Runnels, Prairie View A&M University, August 2018.

Masters Dissertation

“Multi-Task Bi-Directional Recurrent Neural Network (Bi-RNN) for Named Entity Recognition on Electronic Medical Records”, MS Thesis by Shanta Chowdhury, Prairie View A&M University, May 2018.

Masters Dissertation

Project Title: “Synthetic Seismic Data Generation using GAN”, by Silky Sandhu, MS degree awarded in December 2018.

Masters Project

2017

Y. Wang, H. Li, and L. Qian (2017). “Belief Propagation and Quickest Detection Based Cooperative Spectrum Sensing in Heterogeneous and Dynamic Environments”, IEEE Transactions on Wireless Communications, Vol.16(11), pp.7446-7459.

Journal Paper

L. Qian, J. Zhu, S. Zhang (2017). “Survey of Wireless Big Data”, Journal Paper of Communications and Information Networks, 2(1), pp.1-18.

Journal Paper

Lei Huang, Xishuang Dong, Ted Clee (2017). “A Scalable Deep Learning Platform For Identifying Geological Features from Seismic Attributes,” The Leading Edge, Vol. 36 no. 3 pp. 249-256, Mar. 2017

Journal Paper

J. Wang, Y. Gong, L. Qian, R. Jäntti, M. Pan, Z. Han (2017). “Primary Users’ Operational Privacy Preservation via Data-Driven Optimization”, IEEE Globecom, Dec. 4-8, Singapore (Best Paper Award).

Conference Paper

I. Olakodana, Y. Wang, L. Qian (2017). “Advanced Data Processing for Communication-constrained Underwater Domain”, The Eleventh ACM International Conference on Underwater Networks and Systems (WUWNet 2017), Nov. 6-8, Halifax, NS, Canada.

Conference Paper

S. Bamgbose, X. Li, L. Qian (2017). “Closed Loop Control of Blood Glucose Level with Neural Network Predictor for Diabetic Patients”, IEEE HealthCom, Oct 12-15, 2017, Dalian, China.

Conference Paper

D. Mistry, Y. Zhu, L. Huang (2017). “Scalable Intelligent Oilfield Streaming Data Analytics Platform,” the Fifth Digital Oilfield Summit Forum & International Academic Conference (DOSFIAC 2017).

Conference Paper

O. Omotere, L. Qian, R. Jäntti, M. Pan, Z. Han (2017). “Big RF Data Assisted Cognitive Radio Network Coexistence in 3.5GHz Band”, the 26th International Conference on Computer Communications and Networks (ICCCN 2017), July 31- Aug 3, Vancouver, Canada.

Conference Paper

H. Asaadi and B. Chapman (2017). “Comparative Study of Deep Learning Framework in HPC Environments”, New York Scientific Data Summit (NYSDS), Aug 6-9, 2017, New York, NY, USA.

Conference Paper

C. Chen, Y. Yan, L. Huang, and L. Qian (2017). “Implementing a Distributed Volumetric Data Analytics Toolkit on Apache Spark”, New York Scientific Data Summit (NYSDS), Aug 6-9, New York, NY, USA.

Conference Paper

H. Jafari, X. Li, L. Qian, A. Aved, T. Kroecker (2017). “Evidence Theory Enabled Quickest Change Detection Using Big Time-Series Data from Internet of Things”, 19th International Conference on Data Mining, Big Data, Database and Data System, June 15-16, Toronto, Canada.

Conference Paper

X. Dong, L. Qian, and L. Huang (2017). “Short-Term Load Forecasting in Smart Grid: A Combined CNN and K-Means Clustering Approach”, IEEE International Conference on Big Data and Smart Computing (IEEE BigComp 2017), Juji, Korea.

Conference Paper

O. Adejuwon, H. Wu, Y. Yan, and L. Qian (2017). “Performance Evaluation of Target Identification Model Using Deep Learning”, The 15th International Conference on Software Engineering Research and Practice, July 17-20, Las Vegas, NV, USA.

Conference Paper

X. Dong, L. Qian, and L. Huang (2017). “A CNN Based Bagging Learning Approach to Short-Term Load Forecasting in Smart Grid”, The 3rd IEEE International Conference on Cloud and Big Data Computing, Aug 4 – 8, San Francisco, CA, USA

Conference Paper

J. Dennis, L. Huang, W. Lim, H. Wu, and Y. Yan (2017). “Implementing Deep Neural Networks on Fresh Breeze,” The International Parallel Computing Conference (Parco 2017), Sep 12-15, Bologna, Italy.

Conference Paper

L. Huang (2017). “Deep Learning on a GPU-enabled Cloud for Seismic Interpretation,” SEG Annual Conference 2017, Houston, TX, Sep. 27, 2017.

Conference Paper

X. Dong, S. Chowdhury, L. Qian, Y. Guan, J. Yang, Q. Yu (2017). “Transfer Bi-directional LSTM RNN for Named Entity Recognition in Chinese Electronic Medical Records”, IEEE HealthCom, Oct 12-15, 2017.

Conference Paper