赵奇，工学博士，副教授，硕士生导师；2017年于吉林大学计算机科学与技术学院获得计算机科学与技术专业工学博士学位，2015~2016年在密苏里大学联合培养；现为辽宁大学信息学部专任教师，人工智能社团负责人；研究方向为人工智能应用；作为负责人主持国家自然科学基金青年基金1项、中央高校基本科研业务专项资金1项、辽宁省科技厅项目1项、辽宁大学科研启动基金1项、东北大学基本科研业务基金1项、校企合作项目2项；中国科学院开放基金 2 项；参与东北大学创新团队项目1项、国家自然基金面上项目1项、吉林省科技厅面上项目2项；在国内外高水平学术期刊杂志上发表论文60余篇，获批专利6项，其中2项已转化，撰写教材5部。注重本科生科研能力培养，带领本科生发表多篇高水平论文，并获得多项国家级、省级竞赛奖项。
招生信息：
l 招收专业（不分先后）：计算机类、人工智能类、生物信息学等专业的硕士研究生。
l 希望你：保有探索新事物的好奇心，怀揣科研热忱，守得住初心，有理想敢追求，不甘止步于成为一名普通程序员；具备扎实的程序设计基础，熟悉深度学习模型或算法设计思路。
团队毕业生去向：
l 本科生：出国留学、复旦大学、上海交通大学、中国科学院大学、中国科学技术大学等985高校读研和读博
l 研究生：国企事业单位人工智能开发部门、高校、IT大厂AI研发和应用部门
联系方式：
l 地址：辽宁大学崇山校区
l 邮箱：qizhao7178@163.com
l 电话、微信：188-4256-3710
研究方向（不分先后）：
l 人工智能应用：AI+生物信息、AI+医学信息、AI+食品信息、AI+化工信息、AI+材料信息
l 可信人工智能
课程信息：
l 本科生：Python程序设计、算法设计与分析、生物信息学、综合程序设计
l 研究生：人工智能在生物和医学中的应用、计算生物学
代表性项目：
l 国家自然科学基金青年基金1项
l 中央高校基本科研业务专项资金1项
l 辽宁省科技厅项目2项
l 中国科学院上海硅酸盐研究所国家重点实验室开放基金 1 项
l 辽宁大学科研启动基金1项
l 东北大学创新团队项目1项
l 东北大学基本科研业务基金1项
l 校企合作项目2项
l 国家自然科学基金面上项目1项
l 吉林省科技厅面上项目2项
代表性论文：
[1] Zhao Z, Zhang T, Mao Q, Zhao Q, Luo X, Fan X, BinEncoder: Binary Code Similarity Detection Across Compilation Configurations via Microcode, Applied Intelligence, 2026
[2] Dong Y, Zhao Q, Feng Y, Yang W, Wang B, Wang Y, Gao M, Zhang J, Guan T, Recent Advances on Sensor Technologies for the Monitoring of Tumor Markers, Molecules, 2026
[3] Zhao Z, Zhao Q*, Compositional Trigger Mechanism for Stealthy Backdoor Attacks in Large Language Models, ICI, 2026
[4] Tian D, Zhu B, Kong L, Wang J, Wang Y, Zhang R, Zhao Q, Yao Y, EFE-HCTNet: An Edge Feature Enhanced Hybrid CNN-Transformer Network for the Automated Identification of Nerves in Ultrasound Images, Knowledge-Based Systems, 2026
[5] Zhao Q, Zhou YJ, Cui HR, Chen GY, Mao Q, Effect of Collagen–Chitosan–Cinnamon Essential Oil Edible Coating on the Shelf Life of Nanguo Pear, Acta Alimentaria, 2026
[6] Zhao Q, Zhang Z, Chen T, Mao Q, Shi H, Chen J, Zhao Z, Fan X, Mamba6mA: A Mamba-Based DNA N6-Methyladenine Site Prediction Model, Bioinformatics, 2026
[7] Zhao Z, Feng Y, Li S, Mao Q, Chen T, Zhao Q*, Fan X, CQR-UC: A Color QR Code-Based Underwater Wireless Communication Method with GAN-Based Image Enhancement, Journal of Visual Communication and Image Representation, 2026
[8] Teng J, Zhang Y, Wang J, Zhao Q, Deep Learning-Based Quantification of Epicardial Adipose Tissue: A Review, AI Medicine, 2026, 3(2): 8.
[9] Huang Z, Wang Y, Dong Y, Zhang Y, Zhao Z, Zhao Q*, FISBA: A Frequency-Domain Image Steganography-Based Covert Backdoor Attack Method for Self-Supervised Learning Models, ACAI, 2025
[10] Li Z, Zhao Q*, MambaCpG: An Accurate Model for Single-Cell DNA Methylation Status Imputation Using Mamba, Briefings in Bioinformatics, 2025
[11] Qian M, Zhao Q*, Effects of reduced sugar messages on chiffon cake rating sand human chewing behavior, Journal of Texture Studies, 2025
[12] Zhao, Z., Zhang, T., Mao, Q., Zhao, Q., & Xie, X., Guided Visual Feature Learning from Randomized EEG Trials for Object Recognition, ICME, 2025
[13] Zhao, Z., Zhang, T., Mao, Q., Zhao, Q., & Xie, X. , Location Data Publishing Mechanism in Semi-Trusted Vehicle Networks based on Differential Privacy, 2025
[14] Zhao, Z., Zhang, T., Mao, Q., Zhao, Q., & Xie, X. ,Vehicle Pseudonym Change Mechanism Based on Dynamic Game, ICMIC, 2025
[15] Zhao, Z., Zhang, T., Mao, Q., Zhao, Q., & Xie, X. ,QSM: A Quick Shuffling Method for Defending Against Low-rate Denial of Service Attacks in Microservice Systems, ICMIC, 2025
[16] Zhao, Z., Zhang, T., Mao, Q., Zhao, Q., & Xie, X. , DTS: Dynamic Traffic Scrubbing Against Link Flooding Attacks with Programmable Data Plane, 2025
[17] Zhao, Z., Zhang, T., Mao, Q., Zhao, Q., & Xie, X. ,ASTGNN: Adaptive Spatio-Temporal Graph Neural Network for Motor Imagery Recognition, 2025
[18] Xiaoya Fan, Guangyu Zhang, Pengyuan Ganzhang, Gensheng Pei, Qi Zhao, Shi-chun Bao, EEG-based Seizure Detection and Type Classification with Structured State Space Modeling and Graph Neural Networks, BIBM, 2025
[19] Zi Huang, Yanxin Wang, Yubang Dong, Yan Zhang, Zheng Zhao, Qi Zhao*: FISBA A Frequency-domain Image Steganography-based Covert Backdoor Attack Method for Self-supervised Learning Models, ACAI, 2025
[20] Li W.#, Zhao Q.#, Qian M., Effect of modifying pumpkin preparation on oral processing of breads, Journal of Texture Studies, 2024
[21] Zhao Z., Wan J., Wang Y., Li B., Zhao Q.*, ALM: Adaptive Local Mimic for Edge Microservice, 2024
[22] Liu, X., Zhao, Q., Xu, J., Luo, S., Li, J., Jiang, K., & Mao, Q. , Effect of masticatory behavior on the characteristics of biscuit bolus with different amounts of chia seed without compromising taste, International Journal of Gastronomy and Food Science , 2024
[23] Li, Y., Jiang, K., Mao, Q., & Zhao, Q , Effects of Peanut Shell Flavonoids on Composite film Properties and Cherry Tomato Preservation, Food Science & Nutrition , 2024
[24] Mao, Q., Zhuo, Y., Luo, S., Li, J., Hu, F., & Zhao, Q., Preparation and characterization of fish skin collagen-chitosan-cinnamon essential oil composite film, International Journal of Food Science & Technology , 2024
[25] Guo, Y., Zhao, Q., Li, T., & Mao, Q. ,Masticatory Simulators Based on Oral Physiology in Food Research: A Systematic Review, Journal of Texture Studies, 2024
[26] Fan, X., Cui, Y., Zhao, Z., He, Z., Zhao, Q., & Wang, Z ,Partition, Predict and Assemble Targeting-Targeting Long RNA Secondary Structure Prediction, IEEE BIBM, 2024
[27] Zhao, Z., Fan, X., Mao, Q., Xue, H., & Zhao, Q. ,AP-EH: An Encryption Hopping method based on Action Program enabled SDN, IEEE Access, 2024
[28] Zhao, Z., Zhang, T., Fan, X., Mao, Q., Wang, D., & Zhao, Q ,GMN+: A Binary Homologous Vulnerability Detection Method Based on Graph Matching Neural Network with Enhanced Attention, Applied Sciences , 2024
[29] Zhao, Q., Chen, J., Zhao, Z., Mao, Q., Shi, H., & Fan, X , ML-based RNA secondary prediction methods: A survey, AI Medicine, 2024
[30] Fan, X., Xu, P., Zhao, Q., Hao, C., Zhao, Z., & Wang, Z , A Domain Adaption Approach for EEG-based Automated Seizure Classification with Temporal-Spatial-Spectral Attention, MICCAI , 2024
[31] Wang, Y., Zhao, Q., Zhang, B., Tian, D., Zhang, R., & Zhong, W. , A Comparative Study of Deep Learning in Breast Ultrasound Lesion Detection From Two-Stage to One-Stage, from Anchor-Based to Anchor-Free, AI Medicine , 2024
[32] Zhao, Z., Zhang, T., Mao, Q., Zhao, Q., & Xie, X, Dynamic Leadership and W-event Differential Privacy in Semi-Trusted Vehicle Networks, ICMIC , 2024
[33] Zhao, Z.; Fan, X.; Xie, X.; Mao, Q.; Zhao, Q. AP-SDN: Action Program enabled Software-Defined Networking Architecture. KSII Transactions on Internet and Information Systems 2023
[34] Zhao, Q., Liu, F., Song, Y., Fan, X., Wang, Y., Yao, Y., Mao, Q., Zhao, Z. Predicting Respiratory Rate from Electrocardiogram and Photoplethysmogram Using a Transformer-Based Model. Bioengineering, 2023
[35] Liu, W., Du, S., Pang, N., Zhang, L., Sun, G., Xiao, H., Zhao, Q., Xu, L., Yao, Y.; Alastruey, J.; et al. Central Aortic Blood Pressure Waveform Estimation with a Temporal Convolutional Network. IEEE J Biomed Health Inform 2023
[36] Sun, L., He, Q., Teng, Y., Zhao, Q., Yan, X., Wang, X. A Complex Network-Based Vaccination Strategy for Infectious Diseases. Applied Soft Computing, 2023
[37] Zhao Q., Zhao Z., Fan X., et al. RNA independent fragment partition method based on deep learning for RNA secondary structure prediction., 2023
[38] Zhao Q., Zhao Z., Fan X., et al. Review of machine learning methods for RNA secondary structure prediction[J]. PLoS Comput. Biol., 2021, 17(8): e1009291.
[39] Huang J.#, Zhao Q.#, Wei X., et al. miR-351-3p promotes rat amniotic fluid-derived mesenchymal stromal cell proliferation via targeting the coding sequence of Abca4[J]. Stem Cells, 2021, 39(9): 1192-1206.
[40] Zhao Q., Mao Q., Zhao Z., et al. Prediction of plant-derived xenomiRs from plant miRNA sequences using random forest and one-dimensional convolutional neural network models[J]. BMC Genomics, 2018, 19(1): 839.
[41] Zhao Q., Liu Y., Zhang N., et al. Evidence for plant-derived xenomiRs based on a large-scale analysis of public small RNA sequencing data from human samples[J]. PLoS One, 2018, 13(6): e0187519.
[42] Zhao Q, Mao Q, Yuan W, et al. RNA-par: An RNA Exterior Loop Predicting Model for RNA Secondary Structure Prediction[J]. 2022.
[43] Liu Y.*, Zhao Q.,Zhang H., et al. A New Method to Predict RNA Secondary Structure Based on RNA Folding Simulation[J]. IEEE/ACM Trans. Comput. Biol. Bioinform., 2016, 13(5): 990-995.
[44] Zhao, Q., Liu, Y., Duan, Y., Dai, T., Xu, R., Guo, H., & Zhang, H. (2017). FledFold: a novel software for RNA secondary structure prediction. Letters in organic chemistry, 14(9), 714-716.
[45] Zhao, Q., Zhang, C., & Zhao, Z. (2017). A decoy chain deployment method based on SDN and NFV against penetration attack. PloS one, 12(12): e0189095.
[46] Zhao, Q., Zhang, C., & Zhao, Z. (2017). SCM: A method to improve network service layout efficiency with network evolution. PloS one, 12(12): e0189336.
[47] Wang, H., Fang, Z., Liu, L., Xu, P., & Zhao, Q. (2012). The Improved File Caching Mechanism Based on Aging Algorithm. In Advances in Information Technology and Industry Applications (pp. 531-538). Springer, Berlin, Heidelberg.
[48] Tang, M., Lv, Q., Lu, Z., Zhao, Q., & Song, Y. (2012, August). Dynamic virtual switch protocol using Openflow. In 2012 13th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (pp. 603-608). IEEE.
[49] Zhang, C., Fang, Z., Zhuang, L., & Zhao, Q. (2012). The Hypothesized Server Environment Based on VMware Construction. Lecture Notes in Information Technology, 19, 158.
[50] Backdoor Attacks on Self-Supervised Learning: A Survey (2026 投稿中)
[51] SDEmu-Net: Fetal Ultrasound Standard Plane Identification Based on a Sonographer-Diagnosis-Emulation and Spatio-Temporal Attention Module (2026 投稿中)
[52] Deep Learning-Based Prediction of Tumor Response to Neoadjuvant Chemotherapy in Squamous Cell Carcinoma Using FDG PET/CT Imaging (2026 投稿中)
[53] A Review of Respiratory Monitoring Methods Based on Deep Learning (2026 投稿中)
[54] A Robust Two-Step Respiratory Rate Prediction Method Employing a Time-Frequency Joint Deep Learning Model with ECG and PPG Signals (2026 投稿中)
[55] DINO-EEG: Leveraging Object Detection Models for Seizure Event Detection and Type Classification (2026 投稿中)
[56] Sonographer-Emulation and Temporal Correlation-Based Framework for Fetal Ultrasound Standard Plane Identification and Biometric Measurement (2026 投稿中)
[57] Comparative Study of Deep Learning Models for Multimodal PET/CT Prediction of Pathological Subtyping, Stage, and Ki-67 Expression in NSCLC (2026 投稿中)
代表性专利：
[1] 一种基于动作可编程软件定义网络的加密跳变方法
[2] 一种数据平面动作可编程的软件定义网络系统（已转化）
[3] 一种链路泛洪攻击流量动态清洗系统及方法（已转化）
[4] 一种仿生舌驱动装置
[5] 一种船上环境的呼吸频率预测方法及装置
[6] 一种左心室超声图像中主动脉长轴的自动测量方法
[7] 一种基于时-空-频注意力的癫痫脑电信号分类方法
[8] 一种术中脊柱图像的识别方法（审查阶段）
[9] 基层社会网格治理下社会网络中负面信息影响力最小化算法（审查阶段）
[10] 基层社会网格治理下社会网络用户的信任影响力最大化算法（审查阶段）
[11] 一种仿生舌驱动装置（审查阶段）
[12] 一种仿生咀嚼装置（审查阶段）
[13] 一种姜汁-马铃薯淀粉生物复合膜及其制备方法（审查阶段）
教材 & 教改：
[1] 《可信机器学习》
[2] 《深度学习原理与实践：从基础到进阶》
[3] 《人工智能技术在医学领域的应用研究》
[4] 《离散数学—基于Python语言的实现》
[5] 《信息保护的软-硬件方法实践手册》
[6] 结合课程思政的生物信息学教学模式探索，2021，当代教育实践与教学研究
[7] 新工科背景下粮油加工学课程思政探索与实践研究，2021，科教导刊
[8] 课程思政与计算机专业课融合的教学模式探索，2023，新教育时代
[9] 可信人工智能与人工智能伦理教学改革研究与实践，2024，航海教育研究
[10] 基于《专业人文素养》课程的思政教学改革探索，2025，时代教育
软件著作权：
[1] 基于可编程数据平面的DDOS攻击流量动态清洗系统
[2] iHealth RNA序列划分RNA-par软件
[3] TransRR呼吸频率预测软件
[4] 一种基于彩色二维码的水下通信方法
