Xin Zhang

Assistant Professor of Computer Science

(207) 780-4499

xin.zhang@maine.edu

Download Curriculum Vitae

C282 Science Building

Education

Ph.D. Electrical Engineering, University of South Carolina, USA, 2023
M.S. Software Engineering, Chongqing University, China, 2019
B.S. Software Engineering, Chongqing University, China, 2016

Current Courses

Fall 2025

COS 160
COS 184
COS 462

Office Hours:
Wed 11:00am - 1:00pm
Thur 3:30pm - 5:30pm

Research Interests

Computer vision, particularly the robustness of CNNs, partial-label related problems, and depth estimation problem. Applied deep learning and machine learning.

Xin Zhang is joining the department in January 2024. He received his Ph.D. in Electrical Engineering, under the direction of Dr. Xiaofeng Wang, where he focused on the topic of how to quantitatively evaluate and enhance the robustness of convolutional neural network. His current research interest includes computer vision, applied deep learning, and machine learning.

The link to my personal website:https://zhangx192 3.github.io/

Department of Computer Science

Expertise

Extensive teaching experience for multiple courses, including Algorithm Analysis and Design, Operating Systems, Object-oriented Programming(C++) and Real-Time Systems (C & Matlab). Active learner with a strong background in computer science, familiar with various mainstream programming languages and software libraries. Competent programmer with experience in several industrial projects, including Web, WinForm, Android APPs and applied DL systems.

Selected Publications

Day, Jonathan, Yuqi Song, Xin Zhang, Fei Zuo, and Xianshan Qu. "MPS-Net: An Accelerated CNN for Depth Estimation from Binocular Images." 9th International Conference on Machine Vision and Information Technology (CMVIT 2025). 2025.

Song, Yuqi, Xin Zhang, and Forest Ma. "PLB-Net: A Multi-Scale Attention-Based Network for Binocular Depth Estimation with Partial Labels." 8th International Conference on Information and Computer Technologies (ICICT 2025). 2025.

Zhang, Xin, and Yuqi Song. "RBD-Net: Enhancing Binocular Depth Accuracy with Robust Multi-Scale Neural Networks." IEEE International Conference on Future Machine Learning and Data Science (FMLDS 2025). IEEE, 2025.

Fletcher, Sean, Gabby Scott, Douglas Currie, Xin Zhang, Yuqi Song, and Bruce MacLeod. "Deep Learning for Taxol Exposure Analysis: A New Cell Image Dataset and Attention-Based Baseline Model." IEEE International Conference on Future Machine Learning and Data Science (FMLDS 2025). IEEE, 2025.

Zhang, Xin, Sarah Kayembe, Forest Ma, and Yuqi Song. "Analyzing and Predicting Employee Turnover in the Restaurant Industry." 23rd IEEE/ACIS International Conference on Software Engineering, Management and Applications (SERA 2025). IEEE, 2025.

Gilles, Ethan, Yuqi Song, and Xin Zhang. "XcepKNN: Leveraging Hybrid Deep Learning for Enhanced MRI-Based Brain Tumor Classification." 23rd IEEE/ACIS International Conference on Software Engineering, Management and Applications (SERA 2025). IEEE, 2025.

Zhang, Xin, Yuqi Song, and Deiby Wu Lee. "A Review of Vision-Based Depth Estimation: Current Methods and Future Directions." 2nd International Workshop on Edge Intelligence and Vehicular Networks (EIVN 2025). 2025.

Wu Lee, Deiby, Xin Zhang, and Yuqi Song. "An Efficient CNN with Adaptive Loss for Binocular Depth Estimation." 2nd International Workshop on Edge Intelligence and Vehicular Networks (EIVN 2025). 2025.

Zuo, Fei, Xin Zhang, and Yuqi Song. "An Empirical Study on the Multi-Stage Nature of APT Attacks in Cloud Computing." 2nd International Workshop on Edge Intelligence and Vehicular Networks (EIVN 2025). 2025.

Zhang, Xin, Yuqi Song, Wyatt McCurdy, Xiaofeng Wang, and Fei Zuo. "Revising the Problem of Partial Labels from the Perspective of CNNs' Robustness." 22nd IEEE/ACIS International Conference on Software Engineering, Management and Applications (SERA 2024). IEEE, 2024.

Maarefdoust, Reihaneh, Douglas Currie, Bruce MacLeod, Yuqi Song, John Concannon, Samuel Frankel, and Xin Zhang. "Attention-Based CNN for Enhanced Detection of Arsenic Exposure." 5th International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2024). 2024.

Maarefdoust, Reihaneh, Xin Zhang, Behrooz Mansouri, and Yuqi Song. "Material Visions: Advancing Crystal Structure Prediction with Powerful Text Generation Models." 3rd International Conference on NLP and Machine Learning Trends (NLMLT 2024). 2024.

JahediBashiz, Zahra, William Richards, Xin Zhang, James Quinlan, and Yuqi Song. "Exploring the Interpretability of Deep Learning Based Material Property Prediction Methods." 28th ACIS International Winter Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2024-Winter). 2024.

Song, Yuqi, Xin Zhang, Bokai Yang, Fei Zuo, and Xianshan Qu. "A Robust Attention-based Convolutional Neural Network for Monocular Depth Estimation." 22nd IEEE/ACIS International Conference on Software Engineering, Management and Applications (SERA 2024). IEEE, 2024.

Yang, Bokai, Ling Hao, Yuqi Song, Xin Zhang, Fei Zuo, and Xianshan Qu. "Demographics, Approaches, and Conceptions: Understanding Computer Science Learning." Consortium for Computing Sciences in Colleges (CCSC) Northwestern Regional Conference. 2024.

Additional Publications

Zhang, Xin, et al. "Towards Imbalanced Large Scale Multi-label Classification with Partially Annotated Labels." 2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA). IEEE, 2023.

Zhang, Xin, et al. "Depth Monocular Estimation with Attention-based Encoder-Decoder Network from Single Image." 2022 IEEE 24th Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys). IEEE, 2022.

Zhang, Xin, et al. "An Effective Approach for Multi-label Classification with Missing Labels." 2022 IEEE 24th Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys). IEEE, 2022.

Zhang, Xin, et al. "An efficient quantum circuits optimizing scheme compared with qiskit." Collaborative Computing: Networking, Applications and Worksharing: 14th EAI International Conference, CollaborateCom 2018, Shanghai, China, December 1-3, 2018, Proceedings 14. Springer International Publishing, 2019.