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PHD in Generative Ai at Shri Vishwakarma Skill University
Palwal, Haryana
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About the Specialization
What is Generative AI at Shri Vishwakarma Skill University Palwal?
This Generative AI PhD program at Shri Vishwakarma Skill University focuses on advanced research in creating novel data instances, such as images, text, audio, and more, that resemble real-world data. It addresses the rapidly growing demand for skilled researchers in the Indian industry, pushing the boundaries of artificial intelligence. The program emphasizes practical applications and innovative solutions relevant to the country''''s technological landscape.
Who Should Apply?
This program is ideal for highly motivated individuals with a strong background in Computer Science, Artificial Intelligence, or related fields, who possess a Master''''s degree and aspire to contribute original research to the field of Generative AI. It also targets working professionals in tech who seek to transition into advanced R&D roles or academic positions, bringing their industry experience to cutting-edge research.
Why Choose This Course?
Graduates of this program can expect to emerge as leading experts and innovators in Generative AI, highly sought after in India''''s booming AI sector. They can pursue careers as AI Research Scientists, Machine Learning Architects, or academic professors, with potential entry-level salaries ranging from INR 10-20 LPA, growing significantly with experience. The program prepares them for leadership roles in both R&D and product development.
Student Success Practices
Foundation Stage
Master Core Research Methodologies- (undefined)
Thoroughly grasp the principles of research design, data analysis, and literature review during the initial coursework. Actively participate in methodology workshops and seminars to build a robust foundation for your doctoral journey. Engage with faculty and fellow researchers to refine your understanding of academic rigor.
Tools & Resources
SVSU Central Library, Scopus, Web of Science, LaTeX for academic writing
Career Connection
A strong foundation ensures the credibility and scientific soundness of your research, critical for publications and impactful contributions to Generative AI.
Identify a Niche Research Problem- (undefined)
Proactively engage with your supervisor to pinpoint a specific, unsolved problem within Generative AI that aligns with your interests and has significant impact potential. Read extensively across diverse research papers and attend webinars to understand current trends and identify research gaps in the Indian context.
Tools & Resources
Google Scholar, arXiv, ResearchGate, SVSU Research Portal
Career Connection
Focusing on a novel problem sets you apart as an innovative researcher, highly valued by both academia and industry R&D teams working on cutting-edge AI.
Develop Advanced Programming Skills for AI- (undefined)
Continuously enhance your programming proficiency in languages like Python, focusing on libraries and frameworks essential for Generative AI (e.g., TensorFlow, PyTorch). Work on small, self-initiated projects to apply theoretical knowledge and troubleshoot practical challenges.
Tools & Resources
Python, PyTorch, TensorFlow, Kaggle, GitHub
Career Connection
Exceptional coding skills are non-negotiable for implementing and testing Generative AI models, directly translating to efficiency in research and attractiveness to employers.
Intermediate Stage
Engage in Interdisciplinary Collaboration- (undefined)
Seek opportunities to collaborate with researchers from different departments or institutions within India, especially those working on data science, ethics, or domain-specific applications. This broadens your perspective and uncovers novel research avenues for Generative AI.
Tools & Resources
Research groups within SVSU, National AI forums, Collaborative project platforms
Career Connection
Interdisciplinary work fosters holistic problem-solving skills, making you adaptable and valuable for diverse research and industry roles that require cross-functional expertise.
Participate in National and International Conferences- (undefined)
Present your preliminary research findings at relevant conferences and workshops (e.g., AAAI, NeurIPS, ICML, or India-focused AI conferences). Actively engage in networking sessions to connect with experts, gain feedback, and explore potential collaborations or post-doctoral opportunities.
Tools & Resources
Call for Papers websites, Conference proceedings, LinkedIn for networking
Career Connection
Presenting builds your academic profile, enhances visibility, and helps you secure competitive post-doctoral positions or R&D roles in leading organizations.
Publish in High-Impact Journals and Pre-print Servers- (undefined)
Aim to publish your research in reputed, peer-reviewed journals and conferences. Utilize pre-print servers like arXiv to share your work early, receive feedback, and establish priority. Focus on clear articulation of your methodology and findings.
Tools & Resources
Scopus indexed journals, Web of Science indexed journals, arXiv.org
Career Connection
A strong publication record is crucial for academic career progression and demonstrates your research capability to industrial R&D labs.
Advanced Stage
Develop Mentorship and Leadership Qualities- (undefined)
Mentor junior PhD students or Master''''s candidates in their research endeavors. Take on leadership roles in departmental committees or student research groups. This helps refine your communication, delegation, and team management skills, essential for future academic or industrial leadership positions.
Tools & Resources
SVSU mentorship programs, Departmental student bodies
Career Connection
Leadership experience is highly valued in senior research positions and academic faculty roles, demonstrating your ability to guide and inspire.
Prepare for Thesis Defense and Viva Voce- (undefined)
Systematically organize your research findings into a coherent thesis document. Conduct mock defense sessions with your supervisor and peers to refine your presentation and confidently address potential questions from examiners. Ensure all ethical guidelines are met.
Tools & Resources
SVSU PhD thesis guidelines, Previous successful thesis defenses
Career Connection
A well-prepared and confidently defended thesis is the culmination of your PhD, opening doors to advanced research positions and validating your expertise.
Strategize Post-PhD Career Path- (undefined)
Actively explore career options in both academia and industry. Tailor your CV and cover letter to specific job requirements. Network with alumni and industry professionals working in Generative AI to understand market needs and secure desired placements or post-doctoral opportunities.
Tools & Resources
SVSU Career Services, LinkedIn, Industry-specific job portals like NASSCOM FutureSkills
Career Connection
Proactive career planning ensures a smooth transition from doctoral studies to a fulfilling and impactful professional role in the dynamic field of Generative AI.
Program Structure and Curriculum
Eligibility:
- Master''''s Degree in a relevant discipline with at least 55% marks (or an equivalent grade in a point-scale wherever grading system is followed) or a 4-year Bachelor''''s degree (B.E./B.Tech./B.S.) with 75% marks (or an equivalent grade in a point-scale).
Duration: Minimum 3 years (full-time) for PhD, including 2 semesters of coursework
Credits: 16 (for coursework) Credits
Assessment: Internal: As per departmental guidelines for coursework, typically evaluated internally via assignments, presentations, and examinations. A minimum grade is required to pass the coursework., External: undefined
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| PHD-101 | Research Methodology & Quantitative Techniques | Core | 4 | Introduction to Research, Research Design and Methods, Data Collection Techniques, Statistical Analysis for Research, Hypothesis Testing and Interpretation, Academic Writing and Report Formulation |
| PHD-102 | Literature Review & Seminar | Core | 4 | Identification of Research Gaps, Techniques of Effective Literature Review, Referencing and Citation Styles, Academic Presentation Skills, Critical Analysis of Research Papers, Ethics in Reviewing Literature |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| PHD-201 | Advanced Topics in the Area of Research (Generative AI) | Elective (chosen based on research area) | 4 | Deep Learning Architectures for Generation (GANs, VAEs, Transformers), Natural Language Generation and Large Language Models (LLMs), Image and Video Synthesis Techniques, Generative Models for Code and Data, Ethical and Societal Implications of Generative AI, Applications of Generative AI in various domains |
| PHD-202 | Research & Publication Ethics | Core | 4 | Plagiarism and Academic Integrity, Authorship and Contributorship Guidelines, Conflict of Interest in Research, Research Misconduct and Data Integrity, Intellectual Property Rights and Patents, Responsible Conduct of Research |
