COURSES
QUALIFICATIONS
DOCUMENT CHECKLIST
ADMISSION SCHEDULES
ADMISSION STEPS
TUITION FEES
SCHOLARSHIPS
COURSES
PROGRAM SCHEDULE
Students will study at Mahidol University for 36 months (3 years) consisting of 2 semesters per academic year.
Academic Year
Semester 1: August – December
Semester 2: January – May
Semester 3 (summer): May – July (no class)
PROGRAM LOCATION
Students in the Doctor of Philosophy Program in Computer Science will study at the Faculty of ICT building, Mahidol University (MU), Nakhon Pathom, Thailand (Salaya Campus).
CLASS TIME
Classes are taught in the weekdays (9:00 – 16:00).
GRADUATION REQUIREMENTS
Plan 1.1 (Thesis)
- Total time of study should not exceed the study plan.
- Students must complete courses as stated in the curriculum: thesis (48 credits).
- Students must pass the Qualifying Examination.
- Students must meet the English Competence Standard of Graduate Students, Mahidol University as defined by the Faculty of Graduate Studies, Mahidol University.
- Students must participate in skill development activities by the Faculty of Graduate Studies, Mahidol University.
- Students must submit theses and pass the thesis defence in accordance with the Regulations of Mahidol University on Graduate Studies and the oral thesis defense must be open to public.
- Theses are required to be published in at least 2 international peer-reviewed academic journals.
Plan 2.1 (Thesis & Courses)
- Total time of study should not exceed the study plan.
- Students must complete courses as stated in the curriculum at least 12 credits excluding thesis (36 credits) for 48 credits in total, with a minimum CUM-GPA of 3.00.
- Students must pass the Qualifying Examination.
- Students must meet the English Competence Standard of Graduate Students, Mahidol University as defined by the Faculty of Graduate Studies, Mahidol University.
- Students must participate in skill development activities by the Faculty of Graduate Studies, Mahidol University.
- Students must submit theses and pass the thesis defence in accordance with the Regulations of Mahidol University on Graduate Studies and the oral thesis defense must be open to public.
- Theses are required to be published in an international academic journal that is listed by the Faculty of Graduate Studies, Mahidol University.
PROGRAM STRUCTURE
The structure of the entire program consists of 6 semesters (2 semesters per year). The number of credits required for graduation depends on the plan of study.
| Courses | Plan 1.1 | Plan 2.1 |
| Required Courses | – | 9 credits |
| Elective Courses not less than | – | 3 credits |
| Thesis | 48 credits | 36 credits |
| Total not less than | 48 credits | 48 credits |
STUDY PLAN
Plan 1.1 (Thesis):
| 1st Year | |||||
| 1st Semester | 2nd Semester | ||||
| * ITCS 671 | Seminar in Computer Science I | 1 credits | * ITCS 672 | Seminar in Computer Science II | 1 credits |
| ITCS 898 | Dissertation | 9 credits | ITCS 898 | Dissertation | 9 credits |
| Total 9 credits | Total 9 credits | ||||
| 2nd Year | |||||
| 1st Semester | 2nd Semester | ||||
| * ITCS 673 | Seminar in Computer Science III | 1 credits | ITCS 898 | Dissertation | 9 credits |
| ITCS 898 | Dissertation | 9 credits | |||
| Total 9 credits | Total 9 credits | ||||
| 3rd Year | |||||
| 1st Semester | 2nd Semester | ||||
| ITCS 898 | Dissertation | 6 credits | ITCS 898 | Dissertation | 6 credits |
| Total 6 credits | Total 6 credits | ||||
* Register with AUDIT
Plan 2.1 (Thesis & Courses):
1st Year | |||||
| 1st Semester | 2nd Semester | ||||
| ITCS 531 | Mathematics for Computer Science | 3 credits | ITCS 532 | Foundations of Computational Science | 3 credits |
| ITCS 671 | Seminar in Computer Science I | 1 credits | ITCS 672 | Seminar in Computer Science II | 1 credits |
| Elective Courses * not less than | 3 credits | ||||
| Total 4 credits | Total 7 credits | ||||
2nd Year | |||||
| 1st Semester | 2nd Semester | ||||
| ITCS 673 | Seminar in Computer Science III | 1 credits | ITCS 699 | Dissertation | 9 credits |
| ITCS 699 | Dissertation | 9 credits | |||
| Total 10 credits | Total 9 credits | ||||
3rd Year | |||||
| 1st Semester | 2nd Semester | ||||
| ITCS 699 | Dissertation | 9 credits | ITCS 699 | Dissertation | 9 credits |
| Total 9 credits | Total 9 credits | ||||
ELECTIVE COURSES
| Database | Network and Security | ||||
| ITCS 628 | Data Mining And Knowledge Discovery | 3 credits | ITCS 551 | Service Oriented And Cloud Computing | 3 credits |
| ITCS 629 | Knowledge Engineering | 3 credits | ITCS 554 | Information Security Management | 3 credits |
| ITCS 682 | Advanced Database Systems | 3 credits | ITCS 634 | Queuing Modeling In Computer Communication Network | 3 credits |
| ITCS 638 | Networks And Distributed Systems Security | 3 credits | |||
| ITCS 653 | Advanced Computer Architecture | 3 credits | |||
| ITCS 687 | Advanced Computer Security | 3 credits | |||
| Artificial Intelligence | Software Engineering | ||||
| ITCS 660 | Heuristic Methods For Optimization | 3 credits | ITCS 642 | Software Engineering Management | 3 credits |
| ITCS 661 | Advanced Artificial Intelligence | 3 credits | ITCS 644 | Software Quality Assurance | 3 credits |
| ITCS 662 | Advanced Pattern Recognition | 3 credits | ITCS 646 | Requirements Engineering | 3 credits |
| ITCS 663 | Image And Signal Processing | 3 credits | ITCS 651 | Model-Driven Design And Development | 3 credits |
| ITCS 665 | Natural Language Processing | 3 credits | ITCS 657 | Validation And Verification | 3 credits |
| ITCS 667 | Advanced Computer Vision | 3 credits | |||
| Other Elective Courses | |||||
| ITCS 571 | Numerical Methods For Mathematical Optimization | 3 credits | |||
| ITCS 695 | Independent Study | 3 credits | |||
COURSE DESCRIPTION
Topics which are covered by each course are provided below.
| ITCS 531 Mathematics for Computer Science | ITCS 532 Foundations of Computational Science |
| Fundamentals of advanced mathematics used in computer science; High level sets and logics. Proof methods for advanced computer science theories; Formal logic; Mathematical induction; Graph theory; Number theory in Computer Science; Numerical analysis; Combinatorial principles; Discrete probability; State machines; Boolean algebra; Finite automata; Context free language | Fundamentals of computing theory used in Computer Science; Algorithm analysis and design; Computational complexity; Models of computation; Scientific computing; Applications of Computational Science; Simulation techniques; Numerical methods; High performance computing; Concurrent and parallel computing; Dynamic programming; Optimization model; Automata; Turing machine |
| ITCS 671 Seminar in Computer Science I | ITCS 672 Seminar in Computer Science II |
| State-of- the- art research in computer science; Knowledge of basic methodologies of conducting research project in computer science; Issues, questions and basic solutions in theories and applications of computer science and information technology; Ethics and professionalism of computer scientist and plagiarism | State-of-the-art research in computer science; Application of methodologies for conducting research project in computer science; Issues, questions and solutions in theories and applications of computer science and information technology; Ethics and professionalism of computer scientist and plagiarism |
| ITCS 673 Seminar in Computer Science III | ITCS 628 Data Mining and Knowledge Discovery |
| State-of- the- art research in computer science; Application of methodologies for conducting research project in specific computer science area; Issues, questions and solutions in theories and applications of computer science and information technology; Ethics and professionalism of computer scientist and plagiarism | Data mining techniques and algorithms; Knowledge discovery process; Data preparation; Pattern recognition; Association rules; Classification technique; Clustering technique; Data mining applications; Advanced techniques of data mining; Web mining; Text mining; Streaming data mining; Sequential data mining; Data mining visualization |
| ITCS 629 Knowledge Engineering | ITCS 682 Advanced Database Systems |
| Principles of knowledge engineering; Components and architecture of knowledge- based systems; Process and techniques for construction of knowledge- based systems; Knowledge acquisition techniques; Formats, methods, and techniques in explaining knowledge bases; Knowledge representation and reasoning; Knowledge engineering tools; Applications of knowledge engineering in many domains | Advanced database management systems; Replicated database management; Advanced query processing. Parallel and distributed databases; Data warehousing; On-line analytical processing; Distributed information integration; XML query engines; Web and semi-structured data management; Multimedia databases; Heterogeneous and peer-to-peer systems |
| ITCS 551 Service Oriented and Cloud Computing | ITCS 554 Information Security Management |
Concepts, theories, and techniques for service oriented computing; Web services and service- oriented architecture (SOA); Business Process Management (BPM); Web service composition; Semantic web and ontology; Description, discovery, and engagement of web services; Cloud computing; Cloud architecture and components; Cloud services; Cloud characteristics; Cloud security, threats, and privacy | Access control principles and policies, issues, and administration; Communication security on telecommunication networks, network security and Internet security; Risk management and business continuity planning; Security policy, standards, and organization; Computer architecture and system security; Law, investigation and ethics; Application program security; Cryptography; Computer operations security; Physical security; Disaster recovery plans and management; Information technology auditing |
| ITCS 634 Queuing Modeling in Computer Communication Networks | ITCS 638 Networks and Distributed Systems Security |
| Analytical modeling of computer and communication networks; Performance evaluations; Markovian systems; Open networks; Closed networks; Approximations; Decomposition; Simulation; Sensitivity analysis; Optimal operations of systems and local area networks | Network and distributed system security; Basic cryptography, threats and vulnerabilities in distributed systems; Security services: confidentiality, authentication, integrity, access control nonrepudiation, and their integration in network protocols; Key management, cryptographic protocols and their analysis; Access control; Delegation and revocation in distributed systems; Security architectures; Multilevel security; Security management and monitoring; Mobile computing security; Device security |
| ITCS 653 Advanced Computer Architecture | ITCS 687 Advanced Computer Security |
| Instruction set architecture; Instruction-level parallelism; Thread-level parallelism; Pipelining and superscalar architecture; SIMD (single instruction, multiple data) architecture; Vector processors; MIMD (multiple instruction, multiple data) architecture; Simultaneous multithreading; Out-of-order execution; Branch prediction; Data prediction; Exception handling; Design of advanced memory hierarchies; Memory coherency and consistency; Multicore processors; Arithmetic processors; Inter- processor communication models; Input and output; Network communication architecture; Networks-on-Chip; Performance evaluation | Advanced research in computer security; Attacks and Defenses; Authentication and access control; Security models and policy; Multilevel security; Security architecture; Integrity models and mechanisms; Security requirements analysis; Security in programming languages; Network security; Software security; Web security; Security and privacy issues in cloud computing; Security in mobile devices and medical devices; Analysis techniques and tools for vulnerability discovery and threat analysis |
| ITCS 660 Heuristic Methods for Optimization | ITCS 661 Advanced Artificial Intelligence |
| Heuristic search for solving computationally hard problems to get optimum performance and to improve system reliability; Heuristic methods to search beyond local optima; Finding values of discrete and continuous variables in both statically and dynamically dimensioned search spaces; Stochastics local search: trajectory methods including simulated annealing and tabu search, population-based methods using evolutionary computation approaches; Applications in operations research, bioinformatics, cyber security, and engineering | Concepts and techniques necessary for research and study in artificial intelligence; Problems in knowledge representation; Artificial intelligent models; Neural networks; Fuzzy logic; Genetic algorithms |
| ITCS 662 Advanced Pattern Recognition | ITCS 663 Image and Signal Processing |
| Fundamentals of characterizing and recognizing patterns and features of interest in numerical data; Basic tools and theory for signal and image understanding problems with applications to computer vision; Face recognition; Gesture recognition; Speech recognition; Affection recognition; Physiological signal analysis; Advances of pattern recognition algorithms; Decision theory; Statistical classification and recognition; Feature extraction and selection; Statistical estimation theory; Fuzzy logic; Neural networks; Hidden Markov Models; Evolutionary computation; Complexity and chaos | Fundamentals of image and signal processing; Principles and algorithms for image analysis; Filtering and feature extraction; Representation and analysis of discrete signals; Sampling; Filtering; Convolution; Z-transforms; Fourier Transform; Practical experience in image and signal processing; Biomedical image processing; Speech signal processing; Physiological signal processing |
| ITCS 665 Natural Language Processing | ITCS 667 Advanced Computer Vision |
| The role of knowledge in language processing; Models and algorithms; Languages; Thought and understanding; Regular expressions and automata; Morphology and finite- state transducers; N- gram models of syntax; Word classes and part- of- speech tagging; Context- free grammars; Parsing with context-free grammar; Features and unification; Language and complexity; Representing meaning; Semantic analysis; Lexical semantics; Word sense disambiguation and information retrieval; Discourse; Dialog; Conversational agents; Natural language generation; Machine translation | Analysis, interpretation, and inference of complex scenes using primate visual perception; The process of inference from noisy and uncertain data using probabilistic, statistical, and data-driven approaches; Image processing; Image representations; Frequency analysis; Texture models; Image segmentation and grouping; Boundary detection; Object detection; Motion estimation and tracking; Extraction of structures from motion; Bayesian inference; Object and scene recognition; Multi-view geometry; Image database |
| ITCS 642 Software Engineering Management | ITCS 644 Software Quality Assurance |
| Activities, methods, and processes to manage software engineering and software development projects using current best practices; The differences and the similarities in managing software versus hardware projects; Definition and description of software development project framework; Main activities and umbrella activities; Software development project organization and enactment; project organization, project directing, project control, review, evaluation and project closure; Risk management; Software process improvement standards; CMMI and ISO | Roles, functions, and responsibilities of a quality assurance group; Quality assurance work plan in software development; Quality assurance methods; Software reuse; Metrics and models in software quality engineering |
| ITCS 646 Requirements Engineering | ITCS 651 Model-Driven Design and Development |
| Concepts and activities in systems requirements engineering; Requirements elicitation, analysis, modeling and specification of software engineering requirements; Requirements Validation; Requirements Change management; Requirements Traceability; Measurement and quality of requirements | Context of software design and development; Software design process; Key issues in software design; Concurrency control and handling of events, distribution of components, error and exception handling and fault tolerance, data persistence; Software design strategies and methods; Model- driven software engineering; Model-driven architecture, design patterns, frameworks; Software design quality analysis and evaluation |
| ITCS 657 Validation and Verification | ITCS 571 Numerical Methods for Mathematical Optimization |
| Software quality fundamentals and software quality assurance; Software quality management process and techniques; Static and dynamic techniques of system checking; Definitions of validation and verification; Validation and verification technique; Testing; Demonstration; Traceability; Analysis; Inspections; Peer reviews; Walkthroughs; Audits | Computational issues related to the solution of linear, integer, and nonlinear programming problems; Complexity analysis and the structure algorithms; Recent results relating to performance of algorithms, survey of the leading numerical software, modification and development of numerical software |
| ITCS 695 Independent Study | ITCS 699 Dissertation ITCS 898 Dissertation |
| In-depth study of interesting specific topics in computer science; Student selects in consultation with and complete under the guidance and the supervision of instructor | Identifying research proposal; Conducting research with concern of research ethics; Data Collection, analysis, interpretation of the result and report the result in terms of thesis; Presenting and Publishing research in international peer-reviewed journal |
QUALIFICATIONS
Qualifications for Plan 1.1 (Thesis)
- Hold a Master’s degree from an institute accredited by the Office of Higher Education Commission in computer science, computer engineering, or other IT related fields.
- Have cumulative GPA not less than 3.5
- Hold a Master’s degree with Thesis Plan. And having a number of publications which are not part of Master Thesis work.
- Applicants with qualifications other than 1-3 may be considered by the Program Director, the Dean of the ICT Faculty, and the Dean of the Faculty of Graduate Studies.
Qualifications for Plan 2.1 (Thesis & Courses)
- Hold a Master’s degree from an institute accredited by the Office of Higher Education Commission in computer science, computer engineering, or other IT related fields.
- Have cumulative GPA not less than 3.0
- Applicants with qualifications other than 1-2 may be considered by the Program Director, the Dean of the ICT Faculty, and the Dean of the Faculty of Graduate Studies.
DOCUMENT CHECKLIST
Document Checklist
- Bachelor’s degree or Master’s degree diploma or equivalent certificates.
- Official transcripts (English)
- Thai Citizen identification card or passport
- Three one-inch photos
- Two letters of recommendation
- Statement of Purpose
- TOEFL or IELTS score
Optional Document Checklist
- Resume
- Publications
- Certificates of Achievements
ADMISSION SCHEDULES
Admission Schedules (Academic Year 2023)
—–To be announced—–
ADMISSION STEPS
Admission Steps
In order to be admitted to the program, applicants must
- Submit an application form and required documents to the
Faculty of Graduate Studies - Pass the interview examination.
- Pass the research-intent presentation examination.
TUITION FEES
Academic Year | Education Fee | Expenses (overall program) | |||
International Student | Thai Student | ||||
| Baht | USD [1 USD ~ 33 Baht] | Baht | USD [1 USD ~ 33 Baht] | ||
| 2021 | Plan 1 (Thesis) | 512,700 | 15,600 | 420,450 | 12,800 |
| Plan 2 (Thesis & Courses) | 575,700 | 17,500 | 463,200 | 14,100 | |
- Official Tuition Fees Announcement from Mahidol University
SCHOLARSHIPS
Scholarships
Scholarships are available for exceptional students. The applicant can apply for a scholarship in the application form. The scholarship award will be considered by the program committee on a case by case basis.
Overview
The rapid emergence of advanced technologies tremendously impacts the world’s economic growth and social development. This challenging environment gives rise to both crucial needs as well as great opportunities for experts in computer science who can unlock the full potential of IT innovations and businesses.
Doctor of Philosophy in Computer Science program at the Faculty of Information and Communication Technology (ICT) at Mahidol University delivers graduates with strong investigatory, expository, and practical skills who are competitive, can conduct original research, and excel in industry.
Our comprehensive theoretical and applied courses, offered entirely in English, will enhance your analytical, critical, and creative thinking competencies. We guide you not only through the breadth of knowledge in computer science but also the depth of conception and experience in five specialized research areas :
- Data and Knowledge Management
- Intelligent Systems
- Interactive Multimedia Systems
- Networks, Systems, and Security
- Software Engineering