This annual award launched by IKDD in 2022, recognizes the best doctoral dissertation(s) in the broad areas of Data Science, Artificial Intelligence, Machine Learning, Data Mining, Knowledge Discovery and applications of Data-driven techniques. The IKDD Doctoral Dissertation Award winner and up to two runners-up will be recognized at the annual CODS-COMAD conference, and their dissertations will have the opportunity to be published on the IKDD Web site (https://ikdd.acm.org/). The award winner will receive a plaque and a cheque for INR 1,00,000. The runners-up will receive a plaque and a cheque of INR 50,000. The winner and runners-up will also receive a free registration to attend the CODS-COMAD conference and will be invited to present their work in a special session at the conference.

Nomination Deadline: August 31, 2023

Eligibility

Nominated candidates must be from a PhD granting institute in India. Further, the nominated candidate should have successfully defended his/her thesis between August 8, 2022 and August 31, 2023 (i.e., in the period between last year’s deadline and this year’s deadline for application). Every PhD granting institute in India will be allowed to nominate 1 candidate from across all disciplines working in relevant areas. Institutes that produce more than 10 dissertations in relevant areas during the one year period under consideration can nominate 2 students. Institutes should self-declare in case they are nominating 2 students and furnish supporting evidence.

Important Dates

• Submission Deadline: August 31, 2023
• Notification of Awards: December 31, 2023
• Award Presentation at CODS-COMAD 2024

Nomination Requirements

Nominations must be made by the doctoral advisor. All nomination materials must be in English and in PDF format. Late submissions will not be accepted. A nomination must include:

1. Nomination letter by thesis advisor. This letter must include:
   1. The name, address, phone number and email address of the advisor
   2. The name, mailing address and email address of the candidate
   3. A one-page (200-300 words) nomination statement addressing why the nominee should receive the award. The nomination should explain the significance of the work in the context of Data Science. In particular, the nomination should focus on the significance of the work and not just repeat the contents of the abstract of the thesis.
   4. A concise statement (maximum of 25 words) describing the key technical or professional accomplishment for which the nominee merits this award. This would serve as the suggested citation for the award, in case the nominee is selected. Note that the final wording for awardees will be at the discretion of the Awards Committee.
2. An endorsement letter by the department head or a suitable substitute (in case of a conflict of interest).
3. At least 3, and not more than 5, supporting letters from experts in the field who can provide additional insights or evidence of the dissertation’s impact. The nominator/advisor may not write a letter of support. Each letter should include the name, address, and telephone number of the supporter.
4. One copy of the thesis in English in electronic (PDF) format
5. A copy of the thesis review comments given by the external examiners.
6. A list of publications in conferences and journals based on the work reported in the dissertation, along with their citations if any. The nomination should also include all the reviews received during the publication process.
7. A copyright transfer form signed by the appropriate authority in the candidate’s parent institute giving permission for the dissertation to appear on ikdd.acm.org website if the dissertation is selected as an award recipient

The dissertation can be nominated in parallel for other national and global awards, such as the ACM, the ACM India and the SIGKDD Doctoral Dissertation awards.

Submission Procedure

All nomination materials must be submitted using this Easy Chair link. All required documents must be uploaded as a zip file.

All nomination materials must be submitted electronically to IKDDOffice@gmail.com:. Please use "[IKDD Dissertation Award]" in your subject line. All required documents must be attached in a single email.

• Chair

  • Prof. Pushpak Bhattacharyya IIT Bombay

  Members

  • Mausam IIT Delhi
  • Manish Gupta Google Research India
  • Balaraman Ravindran IIT Madras
  • Hema A. Murthy IIT Madras
  • C. V. Jawahar IIIT Hyderabad

2023 Award Winners

Winner

Thesis: Robustness, Evaluation and Adaptation of Machine Learning Models in the Wild

Institute: IIT Bombay

IKDD congratulates Vihari Piratla for his work on tackling the critical challenge of handling distributional drifts in ML deployment, and making impactful contributions in generalization, adaptation, and evaluation of models under changing domains.

Runner-Up

Thesis: Towards and Beyond Continually Learning Neural Networks

Institute: IIT Hyderabad

IKDD congratulates Joseph K J for making impactful contributions to continual learning in computer vision, and going beyond to establish newer settings such as open-world object detection and novel class discovery without forgetting, which have real-world applications in autonomous navigation and marine biology

Runner-Up

Thesis: Self-Supervised Domain Adaptation Frameworks for Computer Vision Tasks

Institute: IISc Bangalore

IKDD congratulates Jogendra Nath Kundu for making groundbreaking contributions to unsupervised domain adaptation and self-supervised learning techniques for structured prediction based vision tasks, advancing the practical deployment of intelligent machines in real-world scenarios.