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PH-D in Cognitive Science at Indian Institute of Technology Kanpur
Kanpur Nagar, Uttar Pradesh
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About the Specialization
What is Cognitive Science at Indian Institute of Technology Kanpur Kanpur Nagar?
This Cognitive Science Ph.D. program at IIT Kanpur focuses on understanding the human mind through an interdisciplinary lens, integrating insights from psychology, neuroscience, linguistics, computer science, and philosophy. It addresses the growing need for advanced research in artificial intelligence, human-computer interaction, and brain-inspired computing in India, fostering innovation and pushing the boundaries of knowledge in a rapidly evolving field.
Who Should Apply?
This program is ideal for master''''s graduates or exceptional bachelor''''s degree holders from diverse fields like engineering, science, humanities, or medicine who possess a strong analytical mind and a passion for interdisciplinary research into cognitive processes. It attracts aspiring academics, researchers, and innovators eager to contribute to India''''s burgeoning R&D landscape in AI and brain sciences.
Why Choose This Course?
Graduates of this program can expect to pursue careers as faculty in top universities, lead research teams in premier R&D labs, or become AI/ML scientists in tech companies across India and globally. They are equipped to address complex challenges in areas such as neuro-rehabilitation, human-centric AI development, and educational technology, commanding competitive salaries (e.g., entry-level research scientist INR 8-15 LPA).
Student Success Practices
Foundation Stage
Deep Dive into Core Theories & Research Methods- (Semester 1-2)
Actively engage with the foundational texts and theories of cognitive science and master diverse research methodologies (experimental, computational, neuroimaging). Form study groups for critical discussion and problem-solving, leveraging online academic resources.
Tools & Resources
Departmental library resources, Online academic databases (JSTOR, PubMed, Google Scholar), Statistical software (R, Python with SciPy/Pandas), MATLAB
Career Connection
Strong theoretical and methodological foundations are crucial for designing robust research projects and for later roles in academic research or R&D in industry.
Cultivate Interdisciplinary Thinking- (Semester 1-2)
Attend seminars and workshops across departments (e.g., Computer Science, Electrical Engineering, Humanities) to broaden perspectives and identify novel research intersections. Proactively seek guidance from faculty across different specializations to foster interdisciplinary problem-solving skills.
Tools & Resources
University-wide seminar schedules, Faculty office hours, Inter-departmental research groups
Career Connection
Essential for tackling complex, real-world problems in cognitive science and for fostering collaborations in academic and industrial settings.
Develop Foundational Programming & Data Skills- (Semester 1-2)
For those from non-computational backgrounds, diligently build proficiency in programming languages (e.g., Python) and data manipulation, which are critical for computational modeling and data analysis in cognitive science. Utilize online platforms for practice and join coding clubs.
Tools & Resources
Coursera, NPTEL courses on Python/R/MATLAB, HackerRank, GeeksforGeeks, IITK''''s central computing facilities
Career Connection
Invaluable for conducting computational experiments, analyzing large datasets, and pursuing roles in AI/ML research and development.
Intermediate Stage
Initiate and Present Pilot Research Projects- (Semester 3-4)
Begin working on small-scale pilot research projects under faculty supervision, applying learned methodologies to gather preliminary data. Actively participate in departmental colloquia and present findings to receive early feedback and refine research questions.
Tools & Resources
Research labs, Faculty mentors, Internal department symposia, Software for data collection (e.g., E-Prime, PsychoPy)
Career Connection
Builds confidence in independent research, strengthens presentation skills, and provides a foundation for comprehensive examination and thesis work.
Build Specialized Skill Sets in Chosen Domain- (Semester 3-5)
Deepen expertise in a chosen area (e.g., computational neuroscience, cognitive linguistics, human-computer interaction) by taking advanced electives, attending specialized workshops, and mastering domain-specific tools and software. Aim for certifications if relevant.
Tools & Resources
Advanced departmental courses, Specialized software (e.g., FreeSurfer for neuroimaging, NLTK for NLP), MOOCs on advanced topics, Professional body workshops
Career Connection
Allows for a focused research contribution, making graduates highly valuable specialists in their respective sub-fields for both academia and industry.
Network and Attend Conferences- (Semester 4-5)
Engage with the wider academic community by attending national and international cognitive science conferences (e.g., ICCS, COGSCI). Network with researchers, present early work (posters/short talks), and stay abreast of cutting-edge developments and collaborations.
Tools & Resources
Conference websites, Travel grants (university/departmental), Professional societies (e.g., Cognitive Science Society)
Career Connection
Establishes a professional network, opens doors for postdoctoral positions, and enhances visibility within the research community.
Advanced Stage
Focus on Thesis Research and Publication- (Semester 6-8 (or until thesis submission))
Dedicate significant time to rigorous thesis research, data analysis, and manuscript writing. Aim to publish research findings in peer-reviewed journals and present at top-tier conferences, solidifying your contribution to the field.
Tools & Resources
Journal submission platforms, LaTeX for scientific writing, EndNote/Mendeley for citation management, Thesis supervision
Career Connection
A strong publication record is paramount for academic careers and highly valued in R&D roles in industry.
Develop Grant Writing & Mentorship Skills- (Semester 7-8)
Begin exploring grant application processes, potentially assisting faculty with proposals, and mentor junior Ph.D. students. These skills are crucial for future independent research careers and leadership roles.
Tools & Resources
University research administration office, Faculty guidance on proposal writing, Workshops on scientific writing and grant applications
Career Connection
Essential for securing funding as an independent researcher and for leadership positions in research labs.
Plan Post-Ph.D. Career & Interview Preparation- (Semester 7-8 (leading up to graduation))
Actively engage with the career development center for resume/CV building, mock interviews, and exploring diverse career paths (academia, industry R&D, entrepreneurship). Network with alumni in desired roles.
Tools & Resources
IITK Career Development Centre, LinkedIn, Alumni network, Professional mentors, Job portals (Indeed, Naukri, academic job boards)
Career Connection
Ensures a smooth transition into the desired professional role, whether in academia, industry, or startup ventures.
Program Structure and Curriculum
Eligibility:
- Candidates with a Master''''s degree in Cognitive Science or related fields (e.g., Computer Science, Engineering, Neuroscience, Psychology, Linguistics, Philosophy, Life Sciences, Economics, Statistics, Mathematics, Physics, etc.) are eligible to apply. Exceptional candidates with a Bachelor''''s degree in any of the above-mentioned disciplines with outstanding academic performance may also be considered for direct admission to the Ph.D. program. All candidates must have a strong academic record and demonstrate a keen interest in interdisciplinary research in Cognitive Science. A valid GATE/NET score or equivalent national-level examination qualification is desirable. Candidates with a B.Tech/B.S. degree applying for direct Ph.D. are generally expected to have a valid GATE score.
Duration: Ph.D. programs typically range from 3 to 5 years, with course work completed in the initial phase. The program requires completion of 30 units of course work.
Credits: 30 units (for coursework, assumed as credits) Credits
Assessment: Assessment pattern not specified
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| COG601 | Foundations of Cognitive Science | Core | 3 | History and Philosophy of Mind, Interdisciplinary Approaches to Cognition, Core Theories and Paradigms (Computationalism, Connectionism), Mind-Body Problem, Consciousness, Representationalism and Embodied Cognition, Evolutionary Psychology and Cognitive Biology |
| COG602 | Research Methods in Cognitive Science | Core | 3 | Experimental Design and Control, Quantitative and Qualitative Research Paradigms, Statistical Analysis and Hypothesis Testing, Neuroimaging Techniques (fMRI, EEG, MEG), Computational Modeling and Simulation, Ethical Considerations in Cognitive Research |
| COG603 | Cognitive Neuroscience | Core | 3 | Brain Anatomy and Functional Specialization, Neural Bases of Perception and Attention, Neurobiology of Memory and Learning, Language and Executive Functions, Brain Disorders and Cognitive Deficits, Advanced Neuroimaging Applications |
| COG604 | Cognitive Psychology | Core | 3 | Sensation, Perception, and Pattern Recognition, Models of Attention and Consciousness, Memory Systems (Working, Long-term, Semantic, Episodic), Language Acquisition, Comprehension, and Production, Problem Solving, Reasoning, and Decision Making, Concept Formation and Categorization |
| COG605 | Computational Cognitive Science | Core | 3 | Symbolic AI and Production Systems, Connectionist Models and Artificial Neural Networks, Bayesian Models of Cognition, Agent-Based Modeling and Simulation, Cognitive Architectures (ACT-R, SOAR), Machine Learning Algorithms in Cognitive Modeling |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| COG606 | Philosophy of Mind | Elective | 3 | Mind-Body Problem (Dualism, Materialism, Functionalism), Nature of Consciousness and Qualia, Intentionality and Mental Representation, Problem of Free Will and Determinism, Personal Identity and Self, Philosophy of Artificial Intelligence and Cognition |
| COG607 | Cognitive Linguistics | Elective | 3 | Language as a Window to Cognition, Conceptual Metaphor and Metonymy, Image Schemas and Embodied Cognition, Categorization and Radial Categories, Construction Grammar and Usage-Based Models, Cognitive Approaches to Semantics and Syntax |
| COG608 | Human-Computer Interaction | Elective | 3 | User-Centered Design Principles, Usability and User Experience (UX), Cognitive Ergonomics and Human Factors, Interaction Design Paradigms and Prototyping, Evaluation Methods (Heuristic, User Testing), Accessibility, Ethics, and Future of HCI |
| COG609 | Artificial Intelligence and Cognition | Elective | 3 | History and Paradigms of AI, Knowledge Representation and Reasoning, Search Algorithms and Problem Solving, Planning and Action Selection, Natural Language Processing (NLP), Machine Learning and Cognitive Learning Models |
| COG610 | Machine Learning in Cognitive Science | Elective | 3 | Supervised, Unsupervised, and Reinforcement Learning, Deep Learning Architectures for Cognitive Tasks, Probabilistic Graphical Models, Feature Extraction and Dimensionality Reduction, Applications in Brain Data Analysis, Neural Network Models of Cognitive Processes |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| COG611 | Developmental Cognitive Science | Elective | 3 | Infant Cognition and Early Perception, Language Acquisition and Development, Theories of Cognitive Development (Piaget, Vygotsky), Social and Emotional Development, Brain Development and Critical Periods, Atypical Cognitive Development and Disorders |
| COG612 | Social Cognition | Elective | 3 | Person Perception and Attribution, Attitudes, Stereotypes, and Prejudice, Self and Identity Processes, Emotion, Motivation, and Social Influence, Group Dynamics and Collective Behavior, Cultural Influences on Cognition and Behavior |
| COG613 | Neuroimaging and Brain Stimulation Techniques | Elective | 3 | Principles of fMRI, EEG, MEG, PET, Data Acquisition and Preprocessing Methods, Statistical Analysis of Neuroimaging Data, Transcranial Magnetic Stimulation (TMS), Transcranial Direct Current Stimulation (tDCS), Applications in Cognitive Research and Neuromodulation |
| COG614 | Decision Making and Reasoning | Elective | 3 | Rational Choice Theory and Expected Utility, Heuristics, Biases, and Bounded Rationality, Prospect Theory and Behavioral Economics, Inductive and Deductive Reasoning, Probabilistic Reasoning and Bayesian Inference, Neuroeconomics and Neural Basis of Choice |
| COG615 | Language and Cognition | Elective | 3 | Psycholinguistics and Cognitive Linguistics, Language Comprehension and Production, Speech Perception and Processing, Bilingualism and Language Learning, Relationship between Language and Thought, Neurolinguistics and Aphasia |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| COG616 | Attention and Perception | Elective | 3 | Visual and Auditory Perception Systems, Models of Selective and Divided Attention, Feature Integration Theory and Perceptual Organization, Change Blindness and Inattentional Blindness, Perceptual Constancies and Illusions, Multisensory Integration and Crossmodal Perception |
| COG617 | Learning and Memory | Elective | 3 | Classical and Operant Conditioning, Memory Systems: Episodic, Semantic, Procedural, Working Memory and Executive Control, Forgetting, Amnesia, and Memory Disorders, Neural Basis of Learning and Memory Formation, Skill Acquisition and Expertise Development |
| COG618 | Consciousness | Elective | 3 | Definitions and Philosophical Theories of Consciousness, Neural Correlates of Consciousness (NCC), Integrated Information Theory (IIT), Global Workspace Theory (GWT), Altered States of Consciousness, Free Will, Agency, and Phenomenal Experience |
| COG619 | Robotics and Embodied Cognition | Elective | 3 | Embodied Artificial Intelligence, Sensorimotor Control and Motor Learning, Robot Learning from Human Interaction, Human-Robot Interaction Principles, Perception-Action Loops in Robotics, Cognitive Architectures for Autonomous Systems |
| COG620 | Advanced Topics in Cognitive Science | Elective (Special Topics) | 3 | Current Research Frontiers and Emerging Fields, Interdisciplinary Challenges and Novel Methodologies, Specific Domain Explorations in Cognitive Science, Cutting-Edge Technologies and Applications, Guest Lectures from Leading Researchers, Critical Analysis of Recent Publications |
| COG621 | Reading Course (Independent Study) | Elective (Independent Study) | 3 | Literature Review in a Specific Research Area, Critical Analysis of Scientific Papers, Development of Focused Research Questions, Independent Learning Project Design, Presentation of Findings to Faculty, Mentor Guided Research Exploration |
| COG691 | Seminar | Elective | 3 | Development of Scientific Presentation Skills, Review of Current Research Trends, Peer Feedback and Constructive Discussion, Synthesis of Academic Literature, Participation in Academic Discourse, Preparation for Conference-Style Presentations |
