Best Research Paper Award
Complexity-Adaptive Gaussian Process Model Inference for Large-Scale Data
Fabian Berns, University of Münster, Germany
Christian Beecks, University of Münster, Germany
Best Application Paper Award
Graph-based Reinforcement Learning for Active Learning in Real Time: An Application in Modeling River Networks
Xiaowei Jia, University of Pittsburgh, U.S.
Beiyu Lin, University of Texas Rio Grande Valley, U.S
Jacob Zwart, U.S. Geological Survey, U.S.
Jeffrey Sadler, U.S. Geological Survey, U.S.
Alison Appling, U.S. Geological Survey, U.S.
Samantha Oliver, U.S. Geological Survey, U.S.
Jordan Read, U.S. Geological Survey, U.S.
IBM Early Career Data Mining Research Award
2020 IBM Early Career Award - Dr. Leman Akoglu
2021 IBM Early Career Award - Dr. Jing Gao
This annual award recognizes one individual in the field of data science who has made outstanding, influential, and lasting contributions to the field within 10 years of having received a PhD.
About the Award: The SDM/IBM Early Career Data Mining Researcher Award for Excellence in Data Analytics seeks to recognize one individual (no runner up/ honorable mention) who has made outstanding and influential contributions in the field of data analysis and who will be within 10 years of having received their PhD degree as of the calendar year prior to the year of the award. For example, an award winner in 2020 should have received their PhD no earlier than 2009. An award winner in 2021 should have received their PhD no earlier than 2010.
Since SDM 2020 was deferred due to the pandemic, this year we are accepting nominations for both 2020 and 2021. Applications for 2020 should include achievements (publications, etc.) dated no later than March 30, 2020.
Nominations: A candidate may be nominated by any member of the community except members of the Award Selection Committee. An individual may nominate at most one candidate for this award in a specific year. In this competition, an individual may nominate at most one candidate for 2020 and at most one candidate for 2021. One candidate can be nominated for both 2020 and 2021 as long as the candidate is eligible for both years. Nominations must be submitted to the Award Selection Committee Co-Chairs by email at [email protected] and [email protected] with “SDM/IBM Research Award [2020 or 2021]” as the subject. Please send one nomination per email and specify whether the nomination is for year 2020 or 2021 in the subject of the email.
A nomination application (a single PDF file) should contain the following:
- Name/email of nominator (self-nominations are not permitted).
- Name/email of candidate being nominated.
- A statement by the nominator (maximum of 500 words) as to why the nominee is highly deserving of the award. Note that since the award is for outstanding contributions, the statement and supporting letters should address what the contributions are and why they are both outstanding, significant, and influential. The nomination should also list the names and email addresses of up to 3 persons who will provide letters supporting the nomination.
- CV of the nominee (the CV must clearly indicate date of degree received)
- Up to three support letters. The letters should be collected by the nominator and included in the nomination. The letter writers may not be the nominator nor Award Selection Committee members.
- Nomination Deadline: March 12, 2021
- Results Notification: April 15, 2021
Award Selection Committee:
Sanjay Chawla, Qatar Computing Research Institute (Co-Chair)
Jian Pei, Simon Fraser University (Co-Chair)
Zoran Obradovic, Temple University (Steering Committee Representative)
Note that members of the selection committee cannot be nominators or provide support letters. Also note that the intent is to select exactly one awardee (one for 2020 and one for 2021) – re-nominations for subsequent years are permissible as long as the individuals continue to maintain eligibility. The committee at its discretion may elect not to make an award in a particular year.
Doctoral Student Forum Participants and Student Travel Scholarship Applications
The SDM Doctoral Forum is a unique opportunity for PhD students in data science (including data mining, machine learning, databases, and pattern recognition) to present their doctoral dissertation in poster format and get feedback from SDM participants and senior leaders in the field. The SDM doctoral forum will be held in a plenary poster session alongside posters from the main conference, allowing for an interesting cross fertilization of ideas. Past participants have benefited significantly from this plenary session.
Applications to the Doctoral Forum at the 2021 SIAM International Conference on Data Mining (SDM21)
We invite doctoral students in data science (including data mining, machine learning, databases, and pattern recognition) to present their doctoral dissertation (including ongoing and future work) in poster format at the Doctoral Forum of the 2021 SIAM International Conference on Data Mining (SDM21), which will be held virtually April 29-May 1, 2021.
The forum is held in a plenary poster session alongside posters from the main conference, allowing for an interesting cross fertilization of ideas.
The forum is a unique opportunity for PhD students to get feedback from SDM participants and senior leaders in the field. It is also an exciting opportunity for networking and creating future collaborations. Past participants have benefited significantly from this plenary session. An award will be given to the best poster presentation.
In addition to the poster session, there will be a mentorship panel with senior leaders in the field, which will provide perspectives and tips for graduate studies and what comes after graduation.
Doctoral Forum Poster Prize Recipients
- Marie Roald, (Simula Metropolitan Center for Digital Engineering), Understanding the Dynamics of Complex Systems through Time-Evolving Data Mining
- Mayank Kakodkar, (Purdue University), Regeneration in Discrete State and Reversible Markov Chain Monte Carlo
Best Poster (runner-up):
- Moniba Keymanesh, (Ohio State University), Adaptive Summarization for Low-resource Domains and Algorithmic Fairness
- Tyler Derr (Vanderbilt University)
- Pravallika Devineni (Oak Ridge National Lab)
- Arlei Lopes de Silva (UCSB)
- Matteo Riondato (Amherst College)
- Application deadline: March 15, 2021
- Notification deadline: March 29, 2021
- Doctoral Forum: as part of SDM’21, April 29-May 1, 2021 (exact day TBA).
Please apply by filling the application form here.
We welcome submissions both from senior doctoral students who have a more concrete idea of their dissertation, as well as junior doctoral students who may not have a full plan for their dissertation yet but have a direction and can benefit from the feedback by the forum participants.
Limited support for students at U.S.-based institutions who are accepted to the Doctoral Forum is available thanks to a NSF grant. See the application form for details.
Additional travel support for students to attend SDM21, independent from their location and whether they attend the Doctoral forum, is available from SIAM, in the form of Student Travel Awards.
For additional information, please write to the Doctoral Forum Co-chairs:
Joyce Ho, Emory University ([email protected]) and Vagelis Papalexakis, University of California, Riverside ([email protected])
Doctoral Forum Posters
The Doctoral Forum Poster Session will take place on Saturday, May 1 at 3:30 PM Eastern Time.
The Conference Program will be posted here when available.
- Huan He, Emory University
Acceleration Algorithms for Machine Learning Methods
- Moniba Keymanesh, Ohio State University
Adapative Summarization for Low-resource Domains and Algorithmic Fairness
- Johannes Huegle, Hasso Plattner Institute
An Information-Theoretic Approach on Causal Structure Learning within Heterogeneous Data Characteristics of Real-World Scenarios
- Dongkuan Xu, Pennsylvania State University
Deep Models for Learning Temporal Patterns in Dynamic Networks
- Priya Mani, George Mason University
Exemplar-driven Learning for Data Clustering
- Sara Abdali, University of California, Riverside
Fake News Detection Using Tensor Embedding with Limited Supervision
- Yu Wang, Vanderbilt University
Graph Neural Networks and its applications
- Yushun Dong, University of Virginia
Individual Fairness for Graph Neural Networks: A Ranking based Approach
- George Panagopoulos, Ecole Polytechnique de Paris
Influence Representation Learning for Social Network Analysis
- Aritra Majumdar, Bournemouth University - CANCELLED
Injury Risk and Performance: Towards a Better Understanding of the Complexities and Intricacies of Load Monitoring within an Elite Football Club
- Balasubramaniam Srinivasan, Purdue University
Learning Invariant Representations of Sets, Graphs and Other Objects
- Joanna Stanislawek, Bournemouth University - CANCELLED
Machine Learning in Business and how Visualization can Increase its Value
- Idris Oumoussa, National Institute of Statistics and Applied Economics - CANCELLED
Microservices Integration using Event-Driven Orchestration
- Jing Ma, University of Virginia
Multi-Cause Effect Estimation with Disentangled Confounder Representation
- Christopher Hagedorn, Hasso Plattner Institute
Parallel Execution Strategies for Causal Structure Learning in Heterogeneous Computing Systems
- Hui Hu, University of Wyoming
Privacy-Preserving Fair Machine Learning
- Mayank Kakodkar, Purdue University
Regeneration in Discrete State and Reversible Markov Chain Monte Carlo
- Pratik Shrivastava, Madan Mohan Malaviya University Of Technology
Some Issues for Replication in Distributed Real Time Database Systems
- Ajay Kumar Gupta, Madan Mohan Malaviya University Of Technology
Some Issues in Location Dependent Information System Query for Mobile Environment
- Sneha Mehta, Virginia Tech - CANCELLED
Towards Explainable Event Detection and Extraction
- Marie Roald, Simula Metropolitan Center for Digital Engineering
Understanding the Dynamics of Complex Systems through Time-Evolving Data Mining