Mode: Online (Google Meet)
Date : 05.02.24 to 10.02.24
Beneficiaries: Faculty members, students of EEE.
The 6-day International Webinar on Disruption in Artificial Intelligence (AI) and Machine Learning (ML) was a groundbreaking event that brought together leading experts, researchers, and industry professionals from around the globe. The webinar aimed to explore and discuss the latest trends, challenges, and innovations in the rapidly evolving fields of AI and ML, with a particular focus on disruptions that are reshaping industries.
Key Themes
- Introduction to Artificial intelligence and Machine learning.
- Introduction to various algorithms in AI & ML.
- Impact of AI & ML in the industrial aspect and the possible ways in which student can prepare themselves for the industry.
- Introduction of machine learning towards nanotechnology.
Objectives
- Ignite the student minds on artificial intelligence and machine learning.
- As a core teaching activity of Artificial intelligence course (21CSC206T).
- To expose students and faculty members towards different application of AI & ML.
- To expose knowledge on industrial requirement and effective tools to learn AI & ML.
Agenda of the program
| Date | Letures |
| 05.02.2024 | Introduction to Artificial Intelligence and Deep Learning, by Dr. Sishaj P Simon, Professor, Dept. of EEE, NIT, Trichy. |
| 06.02.2024 | Introduction to Machine learning and algorithms by Dr. Jeyapradha, Director, Undobot Pvt. Ltd., Chennai. |
| 07.02.2024 | AI 101 From Theory to Practice, by Mr. Rishabh Kaw, Freelance Data Scientist, Bengaluru. |
| 08.02.2024 | Machine Learning in Energy Storage Materials: A General Introduction and Case Studies, by Dr. Sourav Ghosh, Assistant Professor, Dept. of ECE, MITS, Andhra Pradesh. |
| 09.02.2024 | Machine Learning in Nano-Technology, by Dr. Mohammed Shariq, IGSTC Postdoctoral Fellow, Fraunhofer Institute of Engineering Manufacturing and Automation, Germany. |
| 10.02.2024 | Summary of Aritificial Intelligence (21CSC206T) and Quiz, by Dr. K. Vijayalakshmi, Assistant Professor, SRMIST (E&T), Ramapuram. |
Registration:
The following link was circulated in which participants are instructed to register for the event.
Introduction to Artificial Intelligence and Deep Learning
By Dr. Sishaj P Simon, Professor, Dept. of EEE, NIT, Trichy.
The speaker introduced the concept of AI and ML. He defined deep learning as a subset of machine learning that uses specialized layers of computation stacked up to create a deep structure, which overcomes limitations of conventional neural networks. Speaker explained linear regression and how it is used to predict or estimate values based on input variables. Finally speaker demonstrated an example of forecasting load using machine learning and shows how training and validation is done.
Introduction to Machine learning and algorithms
By Dr. Jeyapradha, Director, Undobot Pvt. Ltd., Chennai.
Speaker discussed the significance and properties of search algorithms, including their ability to efficiently extract information from large data sets and customize results based on user preferences. Speaker discussed the significance and properties of search algorithms, including their ability to efficiently extract information from large data sets, provide precise and accurate results, handle complex search spaces, and customize results based on user preferences. She explained the advantages of iterative deepening search, including optimality, completeness.
AI 101 From Theory to Practice,
By Mr. Rishabh Kaw, Freelance Data Scientist, Bengaluru.
Mr. Rishabh kaw discusses the importance of AI, ML, and data science in the industry and suggests ways for students to build their work portfolio. He discusses the similarities and differences between AI, ML, and data science, and what the industry demands from professionals in these fields. Rishabh kaw explains the difference between traditional software systems and machine learning systems, and discusses microservices architecture. Rishabh kaw discusses technical skills expected in AI, including programming languages (Python, SQL, R), libraries and frameworks (NumPy, Pandas, Matplotlib, PyTorch, TensorFlow, Scikit-learn), IDEs (integrated development environments)
Machine Learning in Energy Storage Materials: A General Introduction and Case Studies,
By Dr. Sourav Ghosh, Assistant Professor, Dept. of ECE, MITS, Andhra Pradesh.
Dr. Sourav Ghosh introduced the topic of machine learning in energy storage materials. He explained the three key points of optimizing performance using example data, the role of statistics, and representing and evaluating a model of inference.He explained four types of machine learning: supervised, unsupervised, semi-supervised, and reinforcement learning. Dr sourav ghosh discusses the importance of specific parameters in creating a reliable data set for machine learning in material science, and mentions the drawbacks and limitations of using machine learning in this field. They also mention the use of multilayer perception and random forest in their case study.
Machine Learning in Nano-Technology,
By Dr. Mohammed Shariq, IGSTC Postdoctoral Fellow, Fraunhofer Institute of Engineering Manufacturing and Automation, Germany.
Dr. Mohammed Sharik presented research on metal nanoparticles and discussed using machine learning models to predict electrochemical properties in supercapacitor electrodes. He discussed nanotechnology, nanomaterials, his research on metal nanoparticles, and the process of synthesizing and formulating nanoparticles into ink for additive manufacturing applications. He discussed the case study include developing four data-driven models for supercapacitor electrodes and evaluating their predictive accuracy. He outlined a case study on predicting the capacitive retention rate of supercapacitor electrodes and discussed using machine learning models in battery slurry simulation for energy storage devices.
Summary of Aritificial Intelligence (21CSC206T) and Quiz,
By Dr. K. Vijayalakshmi, Assistant Professor, SRMIST (E&T), Ramapuram.
Dr. K. Vijayalakshmi Summarized the entire Artificial Intelligence course (21CSC206T) and posted quiz on artificial intelligence & machine learning. Participants were instructed to attempt the quiz and finally, the 6 days international webinar on Disruption of Artificial intelligence & Machine Learning was concluded successfully.
Link for Quiz: https://forms.gle/ewQtDyCPBhxmYNZz5
Conclusion
The 6-day International Webinar on Disruption in Artificial Intelligence and Machine Learning proved to be a valuable platform for knowledge exchange and collaboration. Participants left with a deeper understanding of the current landscape and future directions of AI and ML, poised to contribute to the ongoing advancements in these dynamic fields. The success of the webinar sets the stage for future events, fostering continued dialogue and collaboration in the rapidly evolving world of AI and ML.
