AI Machine Learning Summer School
Organised By: Odisha Corporate Foundation (OCF) and Odias in Machine Learning (OdiaML)
About
At AI for Global Goals, we (OCF-OdiaML) aim to provide nextGEN participants with best-in-class training on a broad range of advanced topics and developments in artificial intelligence (AI), machine learning (ML) -- including deep learning (DL).
Although several training and development programs (webinars, conferences, seminars) are organized by OCF-Odisha.ML, the AI Machine Learning Summer School is the first in its kind in Odisha focusing on the graduate and master's students aspirants to build their careers in AI and Machine Learning. The program is designed by the OCF-Odisha.ML Core team members who have decades of experience in teaching, industry, and research from world-class universities, top companies, and the best research institutions.
The program is planned for the summer holiday in Odisha (June-July 2022) and will be in virtual mode considering teaching by many international experts. The participants will be based on registration considering the eligibility and background of the participants. The maximum number of participants will be 100. The AI ML Summer School is a five days program and will be conducted on weekends (Saturday and Sunday) only with 3 lecturer sessions per day and each session will be 1.5 hours (1-hour Theory, 30 minutes Demo) except first and last sessions. However, students can execute the assigned mini-project on other days at their convenient time in groups.
Eligibility
Computer Science (CS), Information Technology (IT) Engineering, MCA, BCA Students. Students entering into 2nd Year to Final Year Students can participate in this training program. However, students from any branch including passout can participate in this training program.
Course
Keynote Talk
Lecturers
Mr. Pradeepta Mishra, Director of AI, Fosfor- LTI, Bangalore, India
Dr. Shantipriya Parida, Senior AI Scientist, Silo AI, Helsinki, Finland
Dr. Satya Ranjan Dash, Assoc. Professor, KIIT University, Bhubaneswar, India
Dr. Damodar Sahu, Mentor & Global Strategist, Wipro, USA
Dr. Kirti Sundar Sahu, Post Doctoral Fellow, University of Waterloo, Canada
Mr. Abhijeet Parida, Data Scientist, Childrens National, USA
Dr. Ravi Shankar Prasad, Postdoc, Idiap Research Institute, Switzerland
Mr. Santanoo Patnaik, CEO, Sansoftech, New Delhi, India
Prof. Peeta Basa Pati, Professor, Amrita Vishwa Vidyapeetham, Bangalore, India
Mr. Anjan Kumar Panda, Founder Odias in Machine Learning, USA
Mr. Prabhu Teja, PhD Scholar, EPFL, Switzerland & Research Assistant Idiap Research Institute, Switzerland
Mr. Soumendra Kumar Sahoo, Technical Lead, Freshworks
Mr. Manish Bisoi, Consultant, Ernst & Young
Schedule
Mini-Project
All the participants will be formed into groups to exercise a mini-project. Each group can select a mini-project from the list of mini-projects or they can come up with their idea. Each group has to present their mini-project on the last day during the evaluation session. The best three teams (1st, 2nd, and 3rd) will be announced by the experts. The group formation (total number of groups, and number of participants in each group) will be decided based on the number of registration. A list of mentors (topic-wise) will be provided who will help during the execution of the mini-projects. A communication channel (discord) has already been established for participant-mentor communication.
Mini-Project Mentors
Mr. Soumendra Sahoo (NLP)
Mr. Subhadadarshi Panda (NLP - Machine Translation)
Dr. Shantipriya Parida (NLP - Machine Translation, Topic Modeling, Text Summarization, Language Detection)
Mrs. Kusumlata Patiyal (NLP - Mention Detection, Co-reference Resoultion)
Mr. Sambit Sekhar (NLP - Recommendation Engine)
Mr. Abhijeet Parida (Computer Vision)
Dr. Ketan Kotwal (Computer Vision)
Prof. Peeta Basa Pati (Image Processing)
Dr. Ravi Shankar Prasad (Speech Processing)
Mr. Sakyasingha Mahapatra (Robotics)
Mr. Prabhu Teja (Deep Learning)
Dr. Kirti Sundar Sahu (Data Science)
Mr. Aditya Kumar (Ad Insertion Platform)
The mini-project details (general guidelines, environment setup, problem statement, repositories, etc) can be found in the Github repositories.
Fee
There will be no registration or training fee for the participants. The event is completely sponsored by the Odisha Corporate Foundation and Odias in Machine Learning. However, the number of participants will be limited to 100.
Certificate
Certificates will be issued to the participants who attend all the five days sessions and mini-project. Please inform the organizers in case of absence in any training session.
Registration
Please use the registration form to provide your details. The selection of participants is based on their eligibility and background information.
Important Dates
June 07, 2022 - Registration Open
June 15, 2022 - Registration Close
June 16, 2022 - Acceptance Notification
June 18,19,25,26 - July 2 - AI Machine Learning Summer school
Note: The calendar timing are as per Indian Standard Time (IST)
Latest Update
The registration process is completed. All the participants selected to attend the summer school will be notified on 17th June 2022.
The participants selected for the exercise mini-project participation will be notified separately.
Program Committee
Prof (Col) Aditya Parida, PhD (Retd)
Professor(Retd) from Luleå University of Technology, Sweden.
Senior AI Scientist, Silo AI, Finland
Founder, Odias in Machine Learning, USA
CEO, Sansoft, New Delhi, India
Director of AI, Fosfor- LTI, Bangalore, India
Assoc. Prof. Satya Ranjan Dash
KIIT University, Bhubaneswar, India
Mentor & Global Strategist, Wipro, USA
Co-Founder, Odias in Machine Learning, New Delhi, India
Sponsors
Partners
Contact Us
If you are interested in attending the summer school, discussing sponsorship/partnership opportunities, or participating as a volunteer or expert, please send us an e-mail : odiaml@outlook.com
You can follow #OdishaMLSchool22 on Twitter for the latest update.
Feedback
We love to know your thoughts and suggestions about the AI ML Summer school for possible improvement. Please use the below link to provide your feedback.