Ph.D. in Computer Science

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

Information Updated on Jan. 27, 2020

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)

  1. Total time of study should not exceed the study plan.
  2. Students must complete courses as stated in the curriculum: thesis (48 credits).
  3. Students must pass the Qualifying Examination.
  4. Students must meet the English Competence Standard of Graduate Students, Mahidol University as defined by the Faculty of Graduate Studies, Mahidol University.
  5. Students must participate in skill development activities by the Faculty of Graduate Studies, Mahidol University.
  6. 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.
  7. Theses are required to be published in at least 2 international peer-reviewed academic journals.

Plan 2.1 (Thesis & Courses)

  1. Total time of study should not exceed the study plan.
  2. 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.
  3. Students must pass the Qualifying Examination.
  4. Students must meet the English Competence Standard of Graduate Students, Mahidol University as defined by the Faculty of Graduate Studies, Mahidol University.
  5. Students must participate in skill development activities by the Faculty of Graduate Studies, Mahidol University.
  6. 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.
  7. 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

Information Updated on Jan. 27, 2020

 

Qualifications

Qualifications for Plan 1.1 (Thesis)

  1. 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.
  2. Have cumulative GPA not less than 3.5
  3. Hold a Master’s degree with Thesis Plan. And having a number of publications which are not part of Master Thesis work.
  4. 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)

  1. 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.
  2. Have cumulative GPA not less than 3.0
  3. 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.

Information Updated on Jan. 27, 2020

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

Information Updated on Jan. 27, 2020

Admission Schedules (Academic Year 2021)

Events Round 1
Application Period November 6, 2020 – December 31, 2020
Announcement of interview candidates January 12, 2021
Interview Date January 15, 2021
Announcement of admitted students January 31, 2021
New Student Check-In  February 1 – 7, 2021
Semester Starts (1st Semester, Academic Year 2021)  August 2021
Events Round 2
Application Period January 1, 2021 – February 28, 2021
Announcement of interview candidates March 12, 2021
Interview Date March18, 2021
Announcement of admitted students March 31, 2021
New Student Check-In April 1 – 7, 2021
Semester Starts (1st Semester, Academic Year 2021)  August 2021
Events Round 3
Application Period March 1, 2021 – April 30, 2021
Announcement of interview candidates May 12, 2021
Interview Date May 14, 2021
Announcement of admitted students May 31, 2021
New Student Check-In June 1 – 7, 2021
Semester Starts (1st Semester, Academic Year 2021)  August 2021
Events Round 4
Application Period May 1, 2021 – June 30, 2021
Announcement of interview candidates July 12, 2021
Interview Date July 16, 2021
Announcement of admitted students July 31, 2021
New Student Check-In August 1 – 7, 2021
Semester Starts (1st Semester, Academic Year 2021)  August 2021
Events Second Semester Round
Application Period July 1, 2021 – October 31, 2021
Announcement of interview candidates November 12, 2021
Interview Date November 18, 2021
Announcement of admitted students November 30, 2021
New Student Check-In December 1 – 7, 2021
Semester Starts (1st Semester, Academic Year 2021)  January 2022


Information Updated on Nov. 6, 2020

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.

Information Updated on Jan. 27, 2020

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]
2562
 Plan 1 (Thesis)
507,300
15,400
415,050
12,600
 Plan 2 (Thesis & Courses)
574,500
17,500
462,000
14,000

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.

 

Information Updated on Jan. 27, 2020

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