Faculty Profile: Lin Cheng

Lin Cheng
Karl W. Hallden Professor of Engineering
Phone: (860) 297-4117	Office Location: MECC 367
Send e-mail to Lin Cheng
Trinity College faculty member since 2008

Degrees:

Ph.D., Carnegie Mellon Univ.
M.S., Carnegie Mellon Univ.
B.S., Shanghai Jiao Tong Univ, China

Professor Cheng conducts research in the fields of Wireless Communications and Signal Processing. In Wireless Communications, some of his recent works include Vehicular Networks for Smart Cities and Propagation modeling for challenging environments. His signal processing research has included such varied topics as localization, bio-signal detection and estimation, low dose medical imaging, connectivity learning in multi-branch networks, graph and hypergraph signal processing. He was a visiting professor with the School of Engineering and Applied Sciences, Harvard University, Cambridge, MA. His industrial experience includes periods with Intel, Siemens Corporate Research and General Motors Global Research.

Prof. Cheng's research and publications are widely referenced by researchers from academia and industry worldwide and were instrumental in forming the International Standard for Vehicular Networks. His work has been featured in Global media such as the Discovery Channel. According to Google Scholar, Prof. Cheng is a top cited scholar among all Trinity Faculty. Prof. Cheng is on the program committee for several top IEEE conferences and journals. He served as a guest Editor for several Special Issues on Vehicular Communications in top journals. He is a Senior Member of IEEE. Prof. Cheng earned the Charles A. Dana Research Professorship from 2019 to 2021 for outstanding research, and was elected to the Connecticut Academy of Science and Engineering.

Beyond classroom teaching, Professor Cheng supervised many undergraduate research projects that led to cutting-edge discoveries, resulting in more than 20 peer-reviewed research papers co-authored with Trinity students, including a Best Paper Award. Many students continued this passion for research to top graduate programs (such as MIT and Stanford) and their professional career. One of his recent graduate is building the hardware for autonomous driving vehicles at Intel. Another alumni is now at Tesla building clean-energy vehicles.

Professor Cheng contributed his time and expertise to professional societies such as IEEE and Electrical and Computer Engineering Department Heads Association (ECEDHA). He has served as an Associate Editor for a number of high impact journals, and as an expert reviewer for more than 200 manuscripts.

Selected Journal Publications:

L. Cheng, Y. Wu, C. Xu, K. Ashraf and A. Ashok, "Automotive Visible Light Communication: Alternative devices and Systems," Tsinghua Science and Technology, Vol. 28, No. 4, pp. 719 - 728, 2023.
P. Yang, C. Tan, M. Han, L. Cheng, X. Cui and K. Ning, "Correlation-Centric Network (CCN) Representation for Microbial Co-occurrence Patterns: New Insights for Microbial Ecology," NAR Genomics and Bioinformatics by Oxford University Press, Vol. 2, No. 2, pp. 1-11, 2020.
T. Qiao and L. Cheng, "A Coarse NLOS Detection Algorithm based on Discrete Power Levels," IET Communications, Vol. 13, No. 10, pp. 1482-1487, 2019.
P. Yang, S. Yu, L. Cheng and K. Ning, " Meta-network: Optimized Species-Species Network Analysis for Microbial Communities," BioMed Central (BMC) Genomics, Vol. 20, No. S2, pp. 143-151, 2019.
L. Cheng, M. Boban, W. Viriyasitavat and H. Tsai, "Comparison of Radio Frequency and Visible Light Propagation Channel for Vehicular Communications," IEEE Access, Vol. 6, pp. 2634-2644, 2018.
L. Cheng, J. Casazza, J. Grace, F. Bai and D. Stancil, "Channel Propagation Measurement and Modeling for Vehicular In-Cabin WiFi Networks," IEEE Transactions on Antennas and Propagation, Vol. 64, No. 12., pp. 5424-5435, 2016.
L. Cheng and T. Qiao, "Localization in the Parking Lot by Parked Vehicle Assistance," IEEE Transactions on Intelligent Transportation Systems, Vol. 17, No. 12., pp. 3629-3634, 2016.
C. Hu, L. Cheng, J. Sepulcre, K. Johnson, G. El Fakhri, Y. Lu and Q. Li, "A Spectral Graph Regression Model for Learning Brain Connectivity of Alzheimer's Disease," PLOS ONE, Vol. 10, No. 5., pp.1-24, 2015.
L. Cheng, D. Stancil, and F. Bai. "A Roadside Scattering Model for the Vehicle-to-Vehicle Communication Channel." IEEE Journal on Selected Areas of Communications 31, no. 9 (2013): 449-459.
S. Panichpapiboon and L. Cheng. "Irresponsible Forwarding Under Real Inter-vehicle Spacing Distributions." IEEE Transactions on Vehicular Technology 63, no. 5 (2013): 2264-2272.
L. Cheng and S. Panichpapiboon. "Effects of Inter-vehicle Spacing Distributions on Connectivity of VANET: A Real Traffic Perspective." IEEE Communications Magazine 50, no. 10 (2012): 90-97.
J. Fernadez, K. Borries, L. Cheng, B.V.K. Vijayakumar, D. Stancil, and F. Bai. "Performance of the 802.11p Physical Layer in Vehicle-to-Vehicle Environments." IEEE Transactions on Vehicular Technology 58, no. 9 (2011): 3-14.
L. Cheng, B. Henty, F. Bai, and D. Stancil. “A Measurement Study of Time-Scaled 802.11a Waveforms over the Mobile-to-Mobile Vehicular Channel at 5.9 GHz.” IEEE Communications Magazine 46, no. 5 (2008): 84-91.
L. Cheng, B. Henty, D. Stancil, F. Bai, and P. Mudalige. "Mobile Vehicle-to-Vehicle Narrow-band Channel Measurement and Characterization of the 5.9 GHz Dedicated Short Range Communication (DSRC) Frequency Band." IEEE Journal on Selected Areas of Communications 25, no. 8 (2007): 1501-1516.

Selected Conference Publications (*denotes co-authorship with Trinity undergraduate students):

L. Cheng, E. Verbeek (*) and S. Skardal, "A Preliminary Study on the VANET Topology Characteristics from Propagation-Aware Traffic Flows Extracted from Measured Data," IEEE International Symposium on Antennas and Propagation, Montreal, Canada, July 5-10, 2020.
K. Chen (*), A. Mudvari (*), F. Guajardo(*), L. Cheng and T. Ning, "Heart Murmurs Clustering Using Machine Learning," The 14th International Congress on Signal Processing, Beijing, China, Aug 12-16, 2018.
K. Chen (*), F. Guajardo (*), L. Cheng and T. Ning, "Unsupervised Detection of Heart Sounds and Clicks with Murmurs," The 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, Shanghai, China, Oct 14-16, 2017.
L. Cheng and T. Qiao, "An Indoor Localization Algorithm in the Absence of A Priori Propagation Information," IEEE International Symposium on Antennas and Propagation, San Diego, California, July 9-15, 2017.
T. Ning, L. Cheng and K. Hsieh, "Identification and Features Extraction of Systolic and Diastolic Murmurs," The 13th IEEE International Conference on Signal Processing, Chengdu, China, Nov. 6-10, 2016.
L. Cheng, H. Tsai, W. Viriyasitavat and M. Boban, "Comparison of Radio Frequency and Visible Light Propagation Channel for Vehicular Communications," ACM International Workshop on Connected and Automated Vehicle Mobility, MobiCom 2016, New York, NY, Oct 2016.
P. Zhou, L. Cheng and D. Wu, "Shortest Path Routing in Unknown Environments: Is the Adaptive Optimal Strategy Available?" IEEE SECON 2016, London, UK, June 27 – 30, 2016.
L. Cheng, H. Cho(*) and P. Yoon, "An Accelerated Procedure for Hypergraph Coarsening on the GPU," IEEE Extreme Computing Conference (HPEC ‘15), Waltham, MA, September 15-17, 2015.
L. Cheng, H. Cho (*), and P. Yoon. "GPU Accelerated Vessel Segmentation Using Laplacian Eigenmaps,." The 12th IASTED International Conference on Parallel and Distributed Computing and Networks (PDCN 2014), pp. 177-184, Innsbruck, Austria, February 17-19, 2014.
C. Hu, L. Cheng, J. Sepulcre, G. El Fakhri, Y. Lu, and Q. Li. "Matched Signal Detection on Graphs: Theory and Application to Brain Network Classification." The 23rd biennial International Conference on Information Processing in Medical Imaging (IPMI 2013), Asilomar, CA, June 29-July 3, 2013. (Acceptance rate 10%, IPMI only accepts around 50 papers worldwide every two years)
C. Hu, L. Cheng, J. Sepulcre, G. El Fakhri, Y. Lu, and Q. Li. "A Graph Theoretical Regression Model for Brain Connectivity Learning of Alzheimer's Disease." IEEE International Symposium on Biomedical Imaging (ISBI), San Francisco, CA, April 7-11, 2013. (Acceptance rate 19% for oral presentation)
L. Cheng, H. Cho (*), P. Yoon, and J. Zhao (*). "An Efficient Out-of-Core Implementation of Block Cholesky Decomposition on a Multi-GPU System." The 24th IASTED International Conference on Parallel and Distributed Computing and Systems, Las Vegas, NV, November 12-14, 2012. (Best paper award)
C. Hu, L. Cheng, and Y. Lu. "Graph-based Regularization for Color Image Demosaicking." IEEE International Conference on Image Processing, Orlando, FL, September 30-October 3, 2012.