icpeev-2024

Summer School on Generation AI for Image Processing and Healthcare (GAIIH-2025)

Short-term summer school plays a crucial role in enhancing the skills and expertise of educators, for improving the quality of education. Rapid advancement of artificial intelligence (AI) revolutionized various domains, mainly in image processing and healthcare, where these technologies are finding innovative applications. Among the various AI paradigms, generative AI stands out because of its ability to generate new data from existing data, making it extremely valuable for tasks like data synthesis, noise reduction, image reconstruction, and more.

The summer school will focus on how generative AI applications can enhance image processing techniques and improve healthcare outcomes, especially in medical imaging, diagnostics, and personalized healthcare. The proposed Summer School on “Generative AI for Image Processing and Healthcare” is crucial in addressing the knowledge, skills, and research capabilities gaps within academia.

This proposal outlines a summer school program designed to introduce graduate students, researchers, and professionals to the core concepts of Generative AI, its applications in image processing, and how these innovations are reshaping healthcare technologies.

Objectives of the Summer School:
The primary objectives of this summer school are:

  • To introduce participants to generative AI techniques and their applications in image processing and healthcare.
  • To explore the intersection of generative AI and image processing for improving data quality, such as noise removal, data augmentation, and image reconstruction.
  • To examine the role of generative AI in advancing healthcare through improved medical imaging, diagnostics, and prediction of healthcare outcomes.
  • To enhance the ability of participants to incorporate generative AI methodologies into their research and teaching, fostering interdisciplinary collaboration between AI, image processing, and healthcare.
  • Educate participants on the principles of Generative AI and deep learning, with a special focus on their applications in image processing and healthcare.
  • Provide hands-on experience in using AI tools and frameworks such as GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and Transformers.
  • Explore real-world use cases where generative AI is applied, including medical imaging, diagnosis automation, personalized treatment planning, and drug discovery.
  • Build a collaborative learning environment where participants can work on interdisciplinary projects combining AI, healthcare, and image analysis.

The summer school will be aimed at:

  • Undergraduates, post-graduates, and research scholars in the fields of Computer Science, Biomedical Engineering, AI, and Data Science, Deep Learning, Image Processing, Healthcare, and Medical Imaging.
  • Researchers exploring AI applications in healthcare and image processing.
  • Healthcare professionals or engineers interested in learning how AI can enhance clinical practices.
  • Industry professionals are interested in the development of generative AI tools for medical applications.

Topics to be covered

  • Introduction to Generative AI: From Classification to Creation (GANs and VAE)
  • Diffusion Models, their types, and applications
  • Introduction to Transformers, their types, and applications
  • Introduction to Large Language Models and their finetuning
  • Prompt Engineering, Chat GPT-3 and Chat GPT-4
  • Collaboration of Large Language Models and Diffusion Models
  • Application of Generative models in the medical domain
  • Generative Models for Drug Design, disease detection, and personalized medicine.
  • Hands-on Sessions for important topics

Expected Outcomes

By the end of the event, participants will:

  • Gain a comprehensive understanding of generative AI models and their applications in image processing and healthcare.
  • Be equipped with practical skills to apply these techniques in their research and teaching.
  • Be able to integrate AI methodologies into their existing research, particularly in healthcare and image processing domains.
  • Contribute to collaborative projects that explore the intersection of AI, image processing, and healthcare.
  • Develop real-world, actionable projects aimed at solving healthcare challenges using AI.
  • Build strong collaborative networks with peers, experts, and industry leaders in AI and healthcare.

Registration Open: 25th March
Registration Closes: 27th April

Summer School Date: 7th to 9th May 2025

Date & Time 7th May 8th May 9th May
8:45 am – 9:30 am Registration Lecture 4 Lecture 8
9:30 am- 10:15 am Inauguration
10:15 am – 10:30 am Networking Break
10:30 – 12:00 pm Plenary Talk 1 Plenary Talk 2 Lecture 9
12:15-1:45 pm Lecture 2 Lecture 6 Lecture 10
1:45 pm-2:30 pm Lunch
2:45 pm-4:15 pm Lecture 3 Lecture 7 Lecture 11
4:15 pm-4:30 pm Networking break
4:30 pm-6:00 pm Hands-on Session 1 Hands-on Session 2 Hands-on Session 3
6:00 pm-6:30 pm Valedictory Session
Name Research Area Affiliated Department/Institute Photograph
Dr. Subramanyam Murala Computer Vision, Deep Learning Trinity College Dublin, Ireland, UK Subramanyam-Murala
Prof. G. Narahari Sastry Computer-Aided Drug Design IIT Hyderabad Prof_G_Narahari_Sastry
Dr. Shiv Ram Dubey  Deep Learning and Computer Vision IIIT Allahabad Dr.-Shiv-Ram-Dubey
Dr. R B Pachori Biomedical Signal Processing, Brain-Computer Interface IIT Indore Dr.-Ram-Bilas-Pachori
Om Ashish Mishra Large Language Models Deloitte, Hyderabad Om-Ashish-Mishra
Dr. Dhiraj Madan Quantum Machine Learning Scientist, IBM Research, Gurgaon Dhiraj-Madaan
Dr. Arnab Bhattacharya  Natural Language Processing and AI IIT Kanpur Prof.ARNAB-BHATTACHARYA
Dr. Vineeth N Balasubramanian  Computer Vision, Deep Learning IIT Hyderabad Vineeth_N_Balasubramanian
Dr. Debdoot Sheet Computation Medical Imaging IIT Kharagpur Dr.-Debdoot
Dr. Nidhi Goyal Natural Language Processing and Knowledge Graphs Mahindra University, Hyderabad Nidhi-Goyal

Registration

Students (UG/PG/P.hD) Professionals (Faculty Members/Industry Persons)
Rs. 2000 Rs. 3000

The registration fee is inclusive of GST.

Registration Open: 25th March
Registration Closes: 27th April
Registration Link: Click here

Note: The Registration Fees include

  • Access to Lunch, coffee breaks, and dinner.
  • Summer School Kit.
  • A certificate for participation in the Summer School.

In case of students, valid proof is needed for registration.

Accommodation

Accommodation in the hostel will be provided on a payment basis

Dr. Dipti Mishra (Coordinator, Summer School), Assistant Professor, Computer Science and Engineering Department, Mahindra University, Hyderabad
Email Id: dipti.mishra@mahindrauniversity.edu.in

Summer School Event ID: mu.genaisummerschool@mahindrauniversity.edu.in
Gmail ID: mu.genai.summer.school@gmail.com

Event venue Address: Mahindra University, Survey: 62/1A, Bahadurpally (Near Tech Mahindra), Jeedimetla, Hyderabad, Telangana, India, Pin: 500043.

Access from Major Transport Hubs:

  • Mahindra University is approximately 30–35 kilometers away from Rajiv Gandhi International Airport (RGIA) in Hyderabad, depending on the specific route you take. The drive usually takes around 40-60 minutes, depending on traffic conditions.
  • It is about 20–25 kilometers away from Secunderabad Railway Station. The travel time can vary, but it generally takes around 30–45 minutes by car, depending on traffic conditions.
  • It is around 25–30 kilometers away from the main bus stations in Hyderabad, such as the MGBS (Mahatma Gandhi Bus Station) or Jubilee Bus Station.