2nd International Research Workshop on Advances in Deep Learning and Applications (2022)

WADLA 2.0
21-25 Febuary 2022
Sponsored By

DST, GoI

NEWS

Program

Tentative program - All times are given in IST time (UTC+5:30)

About

Breakthroughs in data science and computing power, especially the prevalence of graphical processing units (GPUs) and tensor processing units (TPUs) over the past two decades, have made deep learning (DL) one of the most powerful tools in the field of artificial intelligence. DL has been successfully and effectively applied in many cutting edge applications including Automation, Robotics, Natural Language Processing, Computer Vision, Speech Recognition, Object Detection, Drug Discovery etc. Present day DL has amazed everyone with their human level accuracy in classification, generating life-like images and videos and even beating world-champions at their own games. As the quest continues, deep learning has emerged out to be the most sought after skill in today's industrial scenario, right from the Tech Giants to Startups. DL basically uses deep neural network architecture with multiple layers to represent data with increasing abstraction and can be applied to supervised, unsupervised, as well as reinforcement learning.

The Workshop on Advances in Deep Learning and Applications (WADLA) was formally formalized in 2021 to give the participants hands-on experience, right from the foundations, from some of the leading experts in the fields. Based on the past experience and suggestions of the participants and expert speakers, this time we have officially created an organizing committee consisting of expert people from all over the world. This expert committee is continuously monitoring the activities of this workshop and has finalized the topics covered in the program schedule which reflects the recent trends in deep learning.

Area to be covered

This workshop will cover the foundations of deep learning, advances in deep learning, tools, libraries, and applications of deep learning. Participants will learn how to use/implement tools/libraries and successfully lead deep learning academia and industry projects through hands-on sessions. The topics to be covered in this workshop are as follows:

• Pre-Deep Learning Essentials (Neural Network, Feature Learning, Regularization, etc. )


• Foundations of Deep Learning(CNN, RNN, LSTM, Generative Models, etc.)


• Deep learning frameworks and packages (Tensorflow, Keras, Caffe, PyTorch etc.)


• Advanced topics in Deep Learning (Transfer Learning, Attention Transformers, Reinforcement Learning etc.)


• Recent trends in Deep Learning (Light networks, High performance computing, Deep Cognition, Deep Graph Learning, Edge computing, Explainable AI, Interpretability)


• Deep learning Applications (Defence, Governance, Remote Sensing, Computer Vision, Natural Language Processing, Finance, Enterprise personalization, Agriculture, etc.)


• Hands-on Sessions (Generative networks , Network pruning, Transfer Learning, Transformers, HPC, etc. )


• Trends in Deep Learning research, and Many More.

Special Sessions

Although this workshop will cover the foundation and advances of deep learning, we also plan to arrange special sessions as per the demand of participants. For example, if some participants are interested in in-depth research on transfer learning, multi-task learning, satellite image processing and other research topics, we will also keep special sessions apart from this workshop. The special sessions topic include

• Transfer Learning
• Multi-Task Learning
• Brain Computing
• Computer Vision
• Remote Sensing
• Data Analytics

Intended Participants

• Research Students(MS/PhD/Equivalent)
• Faculties and Educators
• R & D and Industry Persons

The goal of This workshop is to

• Provides a strong understanding of deep learning basics and advancements along with practical insights
• Familiarisation of edge computing and deployment of DL models on edge devices
• Encourage the academia industry interactions through participation of leaders from diverse fields
• Demonstrate deep learning capabilities through industry-led hands-on sessions for participants