The 2025 IEEE CIS Summer School is designed to enhance participants' (U.G., P.G., Ph.D., PostDoc., Faculty and Professionals) understanding of cutting-edge advancements in computational intelligence, deep learning, and large language models. The program offers a dynamic learning experience through various formats, including keynote addresses, invited talks, mentorship sessions and networking opportunities. These components aim to foster knowledge exchange, collaboration, and the development of practical skills in a supportive and engaging environment.
This summer school is designed to provide multifaceted benefits to its participants, focusing on the following key aspects:
(i) Lecture Sessions: Participants will have the opportunity to engage with distinguished speakers, including renowned scientists and professors from various domains (see the speaker list below). The sessions will cover the following topics:
a) Advancements in Computational Intelligence: Explore cutting-edge methodologies in computational intelligence, including neural networks, evolutionary algorithms, and fuzzy systems. Participants will gain a comprehensive understanding of state-of-the-art techniques and their practical applications.
b) Deep Learning Fundamentals and Applications: Gain an in-depth understanding of deep learning concepts and their real-world applications. Topics include Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Adversarial Networks (GANs), equipping participants with the skills to implement these technologies across various domains.
(ii) Mentorship Sessions: Participants will benefit from personalized and group mentoring sessions led by our renowned speakers and scientists in Computational Intelligence (CI), Deep Learning (DL), and Large Language Models (LLMs). Mentorship will be provided through interactive formats, including dedicated Q&A panels, breakout room discussions, and one-on-one interactions, ensuring a comprehensive and engaging experience. These sessions will focus on:
a) Selecting Impactful Research Topics: Guidance on identifying and pursuing meaningful research questions in cutting-edge areas.
b) Navigating Academic Publishing and Funding: Insights into writing high-quality research papers, choosing the right journals, and securing funding for projects.
c) Career Mentorship: Tailored advice on career pathways in academia, research labs, and the tech industry.
d) Entrepreneurship in AI: Exploring opportunities to build start-ups and develop innovative solutions in the AI ecosystem.
(iii) Oral/Poster Presentations and Research Showcase: Participants will have the opportunity to showcase their ongoing research, innovative ideas, or capstone projects through structured oral presentations. These sessions will be organized into thematic tracks to ensure focused and meaningful discussions:
a) Computational Intelligence and Emerging Techniques.
b) Applications of Deep Learning in Vision, NLP, and Healthcare.
c) Innovations in Large Language Models and Generative AI.
Each presentation and poster session will include a dedicated Q&A segment, enabling participants to receive constructive feedback from experts and peers. To encourage excellence, top presentations will be recognized with awards, fostering a sense of accomplishment and motivation.
(iv) Networking and Panel Discussions: Participants will have opportunities to engage in dedicated networking sessions, fostering connections with researchers, industry leaders, and IEEE members.
Prof. M. Tanveer
