Computational Applied Sciences and Engineering M.Sc.. Program

Program Director: Dr. Faculty Member Deniz Eroğlu

Email: deniz.eroglu@khas.edu.tr 

Phone: 0 212 533 57 65   Ext. 1446

Adress: Cibali Campus, D Building, Room No: 217

Using English as the medium of instruction, Computational Applied Sciences and Engineering M.Sc. program offers an interdisciplinary research and education opportunity along with modern and innovative tools enriched with recent technological advances.

Why Computational Applied Sciences and Engineering M.Sc.. Program at KHAS? An Interdisciplinary program covering a wide range of topics, such as Biological Sciences, Chemistry and Biochemistry, Electronics, Mechatronics and Computer Engineering, Mathematics, Industrial Engineering and Physics. Students will be able to see their research turn into products effectively, and gain unique skills and approaches.

Who Can Apply to this Program? In addition to students from Engineering programs, students who have a BS degree from a Natural Sciences program such as Physics, Chemistry, or Biology can apply to this program.

Program Tracks: The Computational Applied Science and Engineering Master's program offers the opportunity to specialize in one of the following subfields. In addition to compulsory Research Methods and Seminar courses in areas other than Brain and Mind, the program will include 3 Elective Area and 4 Free Elective courses. The recommended courses for each area and the faculty members working on these topics are provided below:

  • Brain and Mind
  • Computational Biology and Bioinformatics 
  • Computational Physics and Applied Mathematics  
  • Architectural Design Computing   
  • Robotics 

Brain and Mind

(Contact Information: Deniz Eroğlu)

Bahçeşehir University Faculty of Medicine and Kadir Has University Faculty of Engineering and Natural Sciences, in collaboration with expert researchers and industry participation, will offer a graduate education and research program named Brain & Mind within the scope of the Neuroscience Program. Students admitted to the program will be supported with a 100% scholarship throughout their studies, and additional living support funded by scientific projects will also be provided.

Brain and Mind; Program Objectives

The fundamental objective of this program is for students to specialize in computational neuroscience and acquire the necessary research skills to solve complex problems in this field. Specifically, it aims for an in-depth examination of the relationship between the brain and mind by learning the fundamental principles and computational methods of neuroscience. By bringing together knowledge and skills from various fields such as mathematics, statistics, programming, engineering, medicine, molecular biology, and genetics, the program aims to equip students with the ability to creatively solve real-world neuroscience problems. The program aims to foster students' ability to conduct independent research and develop critical thinking and problem-solving skills to address complex neuroscience issues. Additionally, it enables students to work in leading interdisciplinary research groups in their field and share research findings on international platforms. The program guides students in understanding and applying ethical principles in scientific research and technology use, teaching them the responsibility to produce solutions sensitive to societal needs. In line with these objectives, the program aims to ensure that its graduates become innovative and ethically conscious professionals capable of leading in the field of neuroscience on the international stage.

Brain and Mind; Specialization Areas

Academic Researcher: Graduates, if they continue their academic careers, can conduct independent research in computational neuroscience at universities and research institutions internationally and teach courses.
Industrial Researcher: Graduates can work as researchers in computational neuroscience to advance research in the field in private companies developing cutting-edge technologies such as neurotechnology.
Neuroinformatics Specialist: Graduates can specialize in neuroinformatics and work on developing software tools and databases to store, manage, and analyze neuroscience data.
Biomedical Specialist: Graduates can work as biomedical specialists developing new technologies and techniques to research and treat neurological disorders such as brain-computer interfaces or neuroimaging methods.
Clinical Neuropsychologist: Graduates with a strong background in computational neuroscience can pursue careers as clinical neuropsychologists. They can use computational methods to analyze and interpret brain imaging data for diagnostic and therapeutic purposes.

Suggested Courses:

  • Introduction to the Nervous System  
  • Introduction to Neuroscience    
  • Introduction to Neuroinformatics
  • Methods in Neuroscience
  • Collection and Analysis of Neuroscience Data
  • Neural Data Analysis
  • Neural Image Processing
  • Brain Modeling from Data
  • Human-Computer Interfaces and Neurocomputer Feedback
  • Neural Mathematics: Bridging Mathematics and Brain Science
  • Dynamical Systems for Neuroscientists
  • Computational Neuron Models
  • Network Science
  • Computational Dynamics: Applications to Neuroscience
  • Systems Neuroscience
  • Neurotechnology
  • Neuroscience and Music

Computational Biology and Bioinformatics
(Contact Information: Prof. Dr. Ebru Demet AKDOĞAN)

Suggested Courses:

  • BIO510 - Computer-Aided Drug Design Prof. Dr. Ebru Demet AKDOĞAN
  • BIO555 - Molecular Modeling and Graphics Prof. Dr. Ebru Demet AKDOĞAN
  • BIO622 - Special Topics in Medicinal Chemistry Prof. Dr. Kemal YELEKÇİ
  • BIO522 - Computational Structural Biology Dr. Öğr. Üyesi Şebnem EŞSİZ
  • BIO523 - Introduction to Programming and Algorithm Dr. Öğr. Üyesi Şebnem EŞSİZ

Computational Physics and Applied Mathematics

(Contact Information: Deniz Eroğlu, Ayşe Hümeyra Bilge)

Suggested Courses:

  • CSE 502 Mathematical Methods in Computational Sciences
  • CSE 503 Advanced Linear Algebra
  • CSE 504 Classical Mechanics
  • CSE 506 Electromagnetic Theory
  • CSE 507 Dynamics of Complex Systems
  • CSE 510 Complex Networks and Their Applications
  • CSE512 Numerical Methods for Solving Large Scale Eigenvalue Problem
  • CSE 513 High Performance Computing for Science and Engineering
  • CSE 514 Dynamic Programming and Reinforcement Learning
  • CSE 515 Introduction to Quantum Computation

Architectural Design Computing

(Contact Information: Assistant Professor Sabri Gökmen)

Suggessted Courses

  • CSE *** - Architectural Design Computing
  • CSE *** - Digital Modeling and Fabrication
  • CSE *** - Architectural Design Scripting and Generative Systems
  • ARCH 506 - Architectural Morphology
  • ARCH *** - Research Methods in Architectural Design Computing

Robotics (Contact Information: Özkan Karabacak, Assistant Professor Mine SARAÇ STROPPA)

Suggessted Courses

  • CSE 502 Mathematical Methods in Computational Sciences
  • CSE 504 Classical Mechanics
  • CSE 507 Dynamics of Complex Systems
  • CSE 513 High Performance Computing for Science and Engineering
  • CSE 514 Dynamic Programming and Reinforcement Learning
  • CSE *** Virtual Reality, Augmented reality, Mixed reality

Free Elective:

BIO 510 Computer Aided Drug Design
BIO 511 Bioinformatics
BIO 530 Computational Molecular Biology and Genomics
BIO 555 Molecular Modelling and Graphics
CE 509 Design and Analysis of Algorithms
CE 511 Neural Networks and Fuzzy Systems
CE 513 Parallel and Distributed Computing
CE 514 Data Mining
CE 516 Theory of Computation
CE 608 Graph Algorithms
CSE 607 Phase Transitions and Renormalization Group
CSE 612 Applied Thermodynamics
CSE 613 Applied Fluid Mechanics
CSE 614 Computational Fluid Dynamics
CSE 616 Stream and Complex Event Processing
CSE 617 Numerical Solution of Ordinary and Partial Differential Equations
CSE 618  Mathematical Methods in Applied Science and Engineering
CSE 619 Scientific Computing
CSE 620  Probability and Stochastic Processes and Applications
CSE 621  Statistical Methods in Engineering
CSE 622  Variational Methods in Engineering
CSE 617  Numerical Solution of Ordinary and Partial Differential Equations
CSE 620  Probability and Stochastic Processes and Applications
EE 501  Probability and Stochastic Processes
EE 503  Information Theory and Coding
EE 507  Statistical Sigmal Processing
EE 530  Optimal Control
FE 511  Stochastic Differential Equations
FE 515  Simulation Techniques in Risk Management
IE 503  Engineering Optimization and Applications
IT 560  Big Data Analytics
IT 601  High Performance Scientific Computing
MAT 602  Advanced Optimization and its Applications
MAT 603  Numerical Linear Algebra
CSE ***  Virtual Reality, Augmented Reality, Mixed Reality
CE 506  Computational Geometry
CE 509  Design and Analysis of Algorithms
CE 511  Neural Networks and Fuzzy Systems
CE 515  Data Science and Analytics
CE 516  Theory of Computation
CE 609  Machine Learning
MAT 603  Numerical Linear Algebra