① Computer Science and Technology (Academic Doctorate)

  I. Cultivation Objectives

  According to "Double First Class" of the university and the national demands for the field of computer science and technology, this discipline strives to cultivate students with excellent scientific quality, strong sense of social responsibility and good research ethics; with solid and broad basic theories and systematic and in-depth expertise in computer science and technology and related disciplines; be able to proficiently read foreign materials, write scientific and technical papers in foreign languages and conduct academic communication; capable of independently engaging in scientific research work; and making creative achievements in computer and related fields. They are able to read foreign language materials, write scientific and technical papers in foreign languages and carry out academic communications; they have the ability to engage in scientific research independently; they can make creative achievements in computer science and technology and related fields; and they are high-level and innovative talents with international perspectives who are both moral and aptitude.

  Ⅱ. Introduction of Major and Research Direction

  The main research directions of this discipline include key technologies of Internet of Things and collaborative sensing, future network computing and software-defined networks, text mining and machine translation, and research on problems related to graph theory and nonlinear theory.
  (1) Key Technology of Internet of Things and Cooperative Sensing
  Closely focusing on the opportunities and challenges of the third transformation of the information industry, and facing the major needs of the cutting-edge foundation, national strategy and regional economy, we will carry out basic researches on the Internet of Things, common technologies and supporting technologies, and apply them to two major fields, namely, urban public safety monitoring and vehicle networking. Research on vehicle networking system architecture integrating intra-vehicle network, inter-vehicle network and vehicle cloud network; research on vehicle networking network communication technology, research on communication technology between vehicles, vehicles and roadside facilities, vehicles and information platforms; research on vehicle networking information platform technology, development of vehicle networking information service platforms; research on integrated application technology based on vehicle networking, integration of vehicle terminals, communication networks and business support systems.
  (2) Future network computing and software-defined network
  At present, the traditional network system has been difficult to adapt to the cloud computing, Internet of Things, mobile Internet, big data and other new business rapid growth of data traffic and network computing needs, software-defined networks, data centers and other emerging network technologies to solve this problem to expand a new way of thinking, the direction of the research will set up a bridge between the new network technologies and new services, based on software-defined networks, data centers and other new network technologies, to build the future basic network system architecture, in order to integrate the communications network and business support systems. The research in this direction will build a bridge between new network technologies and new services, based on new network technologies such as software-defined network and data center, and construct the future basic network architecture so as to organically integrate it with the upper-layer business application services, and to realize a flexible and diversified service-driven and service customization network. Through the research in this direction, we will provide an open platform for the deep integration of the Internet and the real economy, and promote a new model of business economy and social life, such as energy Internet, industrial Internet, vehicle networking and mobile Internet, so as to push forward the development of the national economy and the overall progress of the society.
  (3) Text Mining and Machine Translation
  With the rapid popularity of the Internet, especially the rise of social media, it enables us to use natural language processing and machine learning techniques for text mining to obtain potential, valuable and novel knowledge patterns. The research in this direction focuses on four main areas, first, social media-oriented text sentiment analysis, based on cognitive linguistics and natural language processing techniques for sentiment analysis and opinion mining; second, research on information retrieval techniques based on query understanding and sequential learning, which is mainly oriented to the vertical field of information retrieval, such as microblogging retrieval, music retrieval and patent retrieval. The third is text mining for the biomedical field, through named entity recognition and gene-disease-drug relationship extraction, so as to propose relevant medical hypotheses. The fourth is machine translation, which makes use of the rich bilingual corpus on the Internet, and uses deep learning and other technologies to carry out machine translation in cross-language information retrieval, instance-based machine translation system and knowledge mining work based on large-scale corpus, mainly oriented to the field of Chinese-Japanese translation.
  (4) Research on Problems Related to Graph Theory and Nonlinear Theory
  This direction mainly includes two main aspects, one is the theoretical and applied research on problems related to nonlinear theory, which mainly includes research on fractal science, nonlinear analysis of bioelectrical signals, chaotic cryptography, complex networks, etc., aiming at enriching and further developing the theory of the construction, analysis, synchronisation, control and confidential communication of (hyper)chaotic systems, and the other is the algorithmic design and analysis of graph theory, which mainly includes isomorphism, determination, polar graph problem, hashmap problem, and the design and analysis of graph theory, mainly for the field of Chinese-Japanese translation. The second is the algorithm design and analysis of graph theory, which mainly includes the isomorphism of graphs, the polar graph problem, the Hamiltonian loop problem, the cross number problem of graphs and the Ramsey Number problem. Its research is characterised by the use of computer algorithm design and analysis ideas and combinatorial mathematical methods to explore graph theory problems.

  ② Computer Technology (Professional Doctorate)

  I. Cultivation Objectives

  Closely integrating with the needs of China's economic and social and scientific and technological development, facing the actual needs of enterprise (industry) engineering, cultivating and practicing socialist core values, adhering to the fundamental principle of establishing morality, cultivating talents with solid theoretical foundations in related theories, mastering the basic theories, basic knowledge and skills in the field of computer technology, and possessing the ability to solve complex engineering and technological problems, carry out engineering and technological innovations, and organize the engineering and technological research and development work. It also aims to cultivate high-level engineering technology and engineering management talents with a high sense of social responsibility and the ability to solve complex engineering technology problems, carry out engineering technology innovation and organize engineering technology research and development work.
  In view of the cultivation orientation of cultivating leading talents in engineering technology, engineering doctoral degree holders in this technical field should have the following knowledge, abilities and qualities:
  (1) Requirements for basic qualities: recipients of doctoral degree in engineering should support the leadership of the Communist Party of China (CPC), love the motherland, and have a high sense of social responsibility; serve the scientific and technological progress and social development; and abide by the academic code of ethics and engineering ethics.
  (2) Basic Knowledge Requirements: Candidates for doctoral degree in engineering should have a broad and solid foundation in mathematics and natural sciences, master systematic and in-depth expertise in the field of computer technology, be familiar with the development trends and frontiers in related technology fields, master related humanities, social sciences and engineering management, and be proficient in a foreign language.
  (3) Requirements for basic ability: Doctor of Engineering degree holders should have the ability to apply knowledge in the field of computer technology to solve complex engineering problems, carry out engineering and technological innovation, organise engineering and technological research and development as well as good communication and coordination ability, and possess international vision and cross-cultural communication ability.

  Ⅱ. Introduction of Major and Research Direction

  Computer technology refers to the technical methods and means used in the field of computer, its hardware technology, software technology and application technology. Computer technology has obvious comprehensive characteristics, which is closely integrated with electronic engineering, applied physics, mechanical engineering, modern communication technology and mathematics, etc., and is a research field with rapid development and wide application.
Main research directions:
  (1) DNA Computing
  Focusing on the applicational needs of DNA computing in the field of artificial intelligence, through the design of novel DNA reaction mechanisms, the construction of dynamically controllable large-scale cascade circuits and programmable logic circuits, we give a new method of reasoning and planning, learning and recognition of intelligences based on DNA computing, and achieve the experimental validation of DNA biochemical reaction of Boolean networks, neural networks, classification and discrimination and other basic AI functional modules. It is expected to provide theoretical and technical support for the application of DNA computing in the field of artificial intelligence, thus providing new methods and ideas for the development of artificial intelligence. This direction has been approved by the National Natural Science Foundation of China's Artificial Intelligence Emergency Management Project and the Key Project of National Defense Science and Technology Innovation of the Military Science and Technology Commission.
  (2) Networked Vehicles
  Focusing on the application needs of group intelligence theory for networked vehicles, and the scientific problems of coexistence, cooperation and cognition of manned and unmanned vehicles, we will study the group intelligence decision-making theory and methodology for networked vehicles, develop the machine learning theory of coexistence, cooperation and cognition of group intelligence, make breakthroughs in the key technology of open-world group intelligence, and establish a prototype validation platform for vehicle-mounted intelligent terminals and road-side intelligent terminals of networked vehicles with independent intellectual property rights. The project is approved as a key project of national defense science and technology innovation by the Military Science and Technology Commission and a key project of NSFC-Liaoning Province Joint Fund.
  (3) Natural Language Processing
  With the rapid development of the Internet, especially the rise of social media, it enables us to use natural language processing and machine learning techniques for text mining to obtain potential, valuable and novel knowledge patterns. The research in this direction focuses on two main aspects. The first is text sentiment analysis, sentiment analysis and opinion mining based on cognitive linguistics and natural language processing techniques, including group sentiment analysis and individual sentiment analysis, public opinion analysis, and monitoring and prediction of emergencies. The second is machine translation, which makes use of the rich bilingual corpus on the Internet and deep learning and other technologies to carry out machine translation in cross-language information retrieval, instance-based machine translation system and knowledge mining based on large-scale corpus, mainly for the field of Chinese-Japanese translation. It has been approved two projects of National Key R&D Programme and one key project of National Natural Science.
  (4) Knowledge Graph
  Knowledge Graph is a large-scale semantic network with entities or concepts as nodes connected through semantic relationships. By discovering the association between entities and integrating semi-structured and unstructured data, knowledge graph can help machines to understand data, explain phenomena, and knowledge reasoning, so as to discover deep relationships and achieve knowledge mining. The research in this direction has two aspects. Firstly, knowledge graph construction and application for biomedical field, for medical literature, electronic medical records, etc., through named entity recognition, gene-disease-drug relationship extraction, construction of medical knowledge graph, knowledge mining, so as to put forward relevant medical hypotheses. Secondly, oriented to the field of intelligent justice, it constructs judicial knowledge atlas and carries out research on key technologies of intelligent assisted prosecutorial case handling, intending to break through key technical difficulties such as decomposition of facts in multi-person, multi-section cases, analysis of evidence association, automatic summary generation of case facts, calibration of judicial documents, and intelligent assistance in sentencing recommendations. It has been approved as a national key research and development programme project.
  (5) New Generation Internet System
  With the continuous expansion of the scale of Internet users and the rapid development of applications, the original system in flexibility, security, intelligence, integration and other aspects of the great challenges faced by the powerful countries have a new generation of Internet system of national strategic research layout. This research direction is mainly based on software-defined network, AI-driven network, computing network fusion system, intelligent network situational awareness and other key technologies, for the deep integration of the Internet and the real economy to create an intelligent network infrastructure system, to practice the national strategy of network power, to promote the landing of the smart city, and to promote the development of the national economy and the overall progress of society.

  ③ Artificial Intelligence (Academic Doctorate)

  I. Cultivation Objectives

   This programme is based on the fundamental task of cultivating moral integrity and aiming at cultivating high-level and innovative talents with international vision for the development of "Double-First Class" of the university. Degree holders should have a theoretical foundation of both arts and sciences, a sound and systematic knowledge structure; have a broad international vision and be able to use a foreign language proficiently; be familiar with the cutting-edge dynamics of AI theoretical research and engineering technology, and have a certain degree of independent learning and active innovation ability; have strong theoretical analysis ability, the ability to solve major engineering problems in the field of AI, and the ability to resolve key scientific problems through the intersection of disciplines; and be able to combine theories with theories to solve key scientific problems in the field of AI. They have strong theoretical analysis ability, the ability to solve major engineering problems in the field of artificial intelligence and the ability to cross disciplines to solve key scientific problems, and are able to engage in scientific research or specialized engineering work in combination with practical problems related to artificial intelligence; they have a certain degree of academic ethics, humanistic qualities, and team spirit.

  Ⅱ. Introduction of Major and Research Direction

  Dalian University of Technology (DUT) has integrated the strengths of several AI-related disciplines of Control Science and Engineering, Computer Science and Technology, Mathematics, Information and Communication Engineering, and Bioengineering. DUT has established the School of Artificial Intelligence in 2019, which focuses on the frontier field of AI and carries out talent training and scientific research. In the same year, the university was awarded the first batch of undergraduate majors in artificial intelligence, and it was one of the first colleges and universities in China to build artificial intelligence majors. The School of Artificial Intelligence relies on a number of provincial and ministerial key laboratories and engineering technology research centers in the Department of Electronic Information and Electrical Engineering. With strong faculty and research strength, it has a group of experts with high reputation among domestic and foreign counterparts, forming a reasonably structured academic echelon.
  AI is a cross-discipline, aiming at the automation of intelligent behaviors, with the characteristics of generality of research objects, symbolization of problem representations, and versatility of research methods. AI is gradually developed and perfected in the intersection and fusion of control science and engineering, computer science and technology, information and communication engineering, mathematics and many other disciplines, and belongs to a typical deep cross-discipline. AI is a typical "cross-cutting interdisciplinary discipline" with the strong instrumentality and methodology formed on the basis of a wide range of interdisciplinary researches, taking the common point of various material structures, levels, and forms of movement as the object of research, and it is a strategic technology that leads the future.
  The orientation of this major is to face the major needs of the country, to face the cutting-edge scientific problems of related disciplines, to serve the economic and social and scientific and technological development of China, especially to serve the economic revitalization of the Northeast China, to carry out research on the basic theories and key technologies of Artificial Intelligence, to achieve internationally leading scientific research results, to cultivate innovative talents, and to make contributions to the development of the national economic construction and the national defense cause. In recent years, this major has obvious characteristics and advantages in the research directions of industrial internet system of intelligent factory, active safety control of engine, information perception understanding and processing of speech, image, vision and other information in complex scenes, optimization and decision-making of production process in process industry, control and collaboration of unmanned system. In recent years, he has published more than 300 papers in authoritative journals in related fields, and has undertaken a number of important scientific research projects from national and local government departments and enterprises, including the National Science and Technology Major Project, the National Key R&D Programme, the National Natural Science Foundation of China's key projects, and the surface projects, etc. He has received a number of national and provincial and ministerial awards. It has won many national and provincial awards.
  The discipline focuses on international exchanges and cooperation, and undertakes a number of international cooperation projects of the State Fund Committee, the Ministry of Education, etc. Teachers of the discipline have left the country for academic exchanges and short-term cooperation in scientific research for more than a hundred times. The department maintains long-term academic and research cooperation with many overseas masters, and has invited experts and scholars from abroad to give lectures to the teachers and students of the department and carry out cooperative scientific researches in China. We attach importance to the combination of industry, academia and research, and have signed internship agreements with Huawei, Baidu, Neusoft and other famous enterprises at home and abroad, and built DUT-HPI teaching base with Hasso Plattner Institute of Digital Engineering of the University of Potsdam, Germany, as well as established long-term and stable cooperation with many universities in the U.S.A., the U.K., Japan, Finland and other countries. It has hosted many academic conferences at home and abroad.
  Main research directions and their contents:
  (1) Machine Learning
  It mainly includes statistical learning theory, deep reinforcement learning, unsupervised learning, semi-supervised learning, active learning and other theories and methods of research, and it carries out complex scenes of speech, image, vision and other information perception understanding and processing of applied research.
  (2) Multimedia and Big Data Mining Direction
  The research areas are cross-media unified representation, association understanding and knowledge mining, knowledge graph construction and learning, knowledge evolution and reasoning, intelligent description and generation, privacy protection learning and other theoretical and methodological research.
  (3) Natural Language Understanding and Processing
  Focusing on the core technologies of syntactic logic of natural language, character conceptual representation and deep semantic analysis, it mainly includes researches on the foundation of natural language processing, sentiment analysis, machine translation, knowledge graph, information retrieval, human-machine dialogue, and text mining.
  (4) Intelligent Control Theory and Technology
  Research on intelligent control theory and its application, focusing on the research and development of new methods and technologies, with emphasis on the applied research of intelligent control theory and technology in the fields of intelligent factory industrial internet system, active safety control of engine, optimization and decision-making of production process in process industry, and control and collaboration of unmanned system.
  (5) Intelligent System and Robot Direction
  To conduct research on theories and methods of intelligent perception, modelling, cognition and autonomous adaptation for unstructured and diverse open environments, and to enhance the long-term autonomous performance and cross-domain collaboration capability of robots and other intelligent systems.
  (6) Brain Science and Brain-Like Intelligence
  To create more capable brain-like machine learning algorithms by using in-depth research and understanding of brain representations, transformations and learning rules, focusing on novel detection of neural signals, brain advanced cognitive functions and computational models, brain-computer interfaces and hybrid intelligence, brain-like machine learning and neural computation.
  (7) Research Direction of Intelligent Perception and Computation
  It mainly explores the potential mechanism of generating intelligence, the learning method of simulated intelligence, the basic theory of computational intelligence, and the basic theory of intelligent perception such as multi-sensor human-computer interaction, and carries out the theoretical and applied research in the directions of pattern recognition, visual computation, machine learning, and data mining for large-scale multimodal data.
  (8) Artificial Intelligence Cross-direction
  This direction conducts researches on basic theories and technological applications related to the intersection of artificial intelligence. Focusing on the industrial, medical and marine fields, the research direction will cover interdisciplinary researches about control, computers, communications, mathematics and other interdisciplinary fields, with the application background of intelligent manufacturing of high-end equipment, intelligent perception and optimal decision-making of industrial processes, and intelligent control of medical robots.

  ④ Artificial Intelligence (Professional Doctorate)

  I. Cultivation Objectives

  The major of Artificial Intelligence cultivates high-level talents who can engage in teaching, scientific research, management, design and related engineering and technical work in the field of Artificial Intelligence. It closely integrates with the needs of China's economic and social and scientific and technological development, especially serves the economic revitalization of the Northeast China, faces the engineering reality of enterprises (industries), fosters and practices the socialist core values, adheres to the fundamental principle of establishing morality, cultivates talents with a solid theoretical foundation in the relevant professional fields, masters the basic theories, knowledge and skills in the field of artificial intelligence, and has the ability to solve complex engineering and technological problems, carry out engineering and technological innovation, and organize engineering and technological research and development work. It aims to cultivate high-level engineering talents with solid theoretical foundation in the related professional fields, mastering basic theories and skills in the field of artificial intelligence, having the ability to solve complex engineering problems, carry out engineering technology innovation and organize engineering technology research and development, and having a high sense of social responsibility, so as to lay a foundation for the cultivation and creation of engineering technology leaders. The recipients of doctoral degree in engineering shall have the following knowledge, abilities and qualities:
  (1) Requirements for basic qualities: recipients of professional doctoral degree shall support the leadership of the CPC, love the motherland and have a high sense of social responsibility; serve the progress of science and technology and the development of the society; and abide by the code of academic ethics and engineering ethics.
  (2) Basic Knowledge Requirements: The recipients of professional doctoral degree shall have a solid knowledge base in mathematics, control, computer and other disciplines, and master the systematic and in-depth expertise in the field of artificial intelligence and the basic knowledge of engineering technology; be familiar with the development trends and frontiers in related engineering fields, and master the related knowledge of humanities and social sciences as well as engineering management; and be proficient in a foreign language.
  (3) Requirements for basic ability: the professional doctoral degree holders should have the ability to apply the knowledge in the field of Artificial Intelligence to solve complex engineering and technological problems, to carry out engineering and technological innovation, to organize engineering and technological research and development as well as the ability of communication and coordination, and the ability to have an international outlook and cross-cultural communication.

  Ⅱ. Introduction of Major and Research Direction

  Dalian University of Technology (DUT) has integrated the strengths of several AI-related disciplines within the university, and established the "School of Artificial Intelligence of Dalian University of Technology" in 2019, which is aimed at the frontiers of artificial intelligence and carries out talent training and scientific research. In the same year, the university was awarded the first batch of undergraduate majors in artificial intelligence, and it was one of the first colleges and universities in China to build artificial intelligence majors. The School of Artificial Intelligence relies on a number of provincial and ministerial key laboratories and engineering technology research centers in the Department of Electronic Information and Electrical Engineering. With strong faculty and research strength, it has a group of experts with high reputation among domestic and foreign counterparts, forming a reasonably structured academic echelon. In recent years, the university has undertaken a number of important scientific research projects from national and local government departments and enterprises and institutions, including the National Science and Technology Major Special Project, the National Key Research and Development Programme, the National Natural Science Foundation of China's key projects, surface projects and so on.
  Artificial Intelligence is a cross-discipline aiming at the automation of intelligent behaviors, which is characterized by the generality of the research object, the symbolic representation of the problem, and the versatility of the research method. Artificial Intelligence is gradually developed and perfected in the intersection and integration of many disciplines such as control science and engineering, computer science and technology, information and communication engineering, mathematics, etc., and belongs to a typical deep cross-discipline. Artificial intelligence is essentially a typical interdisciplinary research on the basis of a wide range of interdisciplinary research, with a variety of material structure, levels, forms of movement and other common points as the object of study and the formation of instrumental, methodological "cross-cutting cross-disciplinary", is to lead the future of strategic technology. The Department of Artificial Intelligence is oriented to the major needs of the country and the frontier scientific problems of related disciplines, and carries out research on theories, key technologies and applications. In recent years, this major has obvious characteristics and advantages in the research direction of intelligent control of complex systems, computer vision, intelligent robotic systems, high-dimensional numerical analysis and optimisation. Attaching importance to international academic exchanges and the combination of industry, academia and research, it has signed internship practice agreements with Huawei, Baidu, Neusoft and other famous enterprises at home and abroad, built a DUT-HPI teaching base in cooperation with the Hasso Plattner Institute for Digital Engineering of the University of Potsdam, Germany, and established long-term and stable cooperative relations with a number of colleges and universities in the U.S., the UK, Japan, Finland and other countries. It has hosted many large-scale academic conferences at home and abroad, which has made the programme have a great influence at home and abroad, and its rapid development has attracted the attention of schools of similar specialties at home and abroad.
  Main research directions and their contents:
  (1) Machine Learning
  Mainly carry out statistical learning theory, deep reinforcement learning, unsupervised learning, semi-supervised learning, active learning and other theories and methods of research, and to carry out complex scenes of speech, image, vision and other information perception understanding and processing of applied research.
  (2) Multimedia and Big Data Mining Direction
  The research areas are cross-media unified representation, association understanding and knowledge mining, knowledge graph construction and learning, knowledge evolution and reasoning, intelligent description and generation, privacy protection learning and other theoretical and methodological research.
  (3) Natural Language Understanding and Processing
  Focusing on the core technologies of syntactic logic of natural language, character conceptual representation and deep semantic analysis, it mainly includes research on the foundation of natural language processing, sentiment analysis, machine translation, knowledge graph, information retrieval, human-machine dialogue, and text mining.
  (4) Intelligent Control Theory and Technology
  It conducts researches on intelligent control theory and its application, focusing on the research and development of new methods and technologies, with emphasis on the applied research of intelligent control theory and technology in the fields of intelligent factory industrial internet system, active safety control of engine, optimization and decision-making of production process in process industry, and control and collaboration of unmanned system.
  (5) Intelligent System and Robot Direction
  To conduct research on theories and methods of intelligent perception, modelling, cognition and autonomous adaptation for unstructured and diverse open environments, and to enhance the long-term autonomous performance and cross-domain collaboration capability of robots and other intelligent systems.
  (6) Brain Science and Brain-Like Intelligence
  It aims to develop more capable brain-like machine learning algorithms by using in-depth research and understanding of brain representations, transformations and learning rules. It focuses on novel detection of neural signals, brain advanced cognitive functions and computational models, brain-computer interfaces and hybrid intelligence, brain-like machine learning and neural computation.
  (7) Research Direction of Intelligent Perception and Computation
  It mainly explores the potential mechanism of generating intelligence, the learning method of simulated intelligence, the basic theory of computational intelligence, and the basic theory of intelligent perception such as multi-sensor human-computer interaction, and carries out the theoretical and applied research in the directions of pattern recognition, visual computation, machine learning, and data mining for large-scale multimodal data.
  (8) Artificial Intelligence Cross-direction
  It conducts researches on basic theories and technological applications related to the intersection of artificial intelligence. Focusing on the industrial, medical and marine fields, the research will cover interdisciplinary research in control, computer, communication, mathematics and other interdisciplinary fields, with the application background of intelligent manufacturing of high-end equipment, intelligent perception and optimal decision-making of industrial processes, and intelligent control of medical robots.