Twenty-Sixth AAAI/SIGAI Doctoral Consortium

February 2-3, 2021
Collocated with the Thirty-Fifth Conference on Artificial Intelligence (AAAI-21)
External site:

The Twenty-Sixth AAAI/SIGAI Doctoral Consortium (DC) provides an opportunity for a group of Ph.D. students to discuss and explore their research interests and career objectives in an interdisciplinary workshop together with a panel of established researchers. The eighteen students accepted to participate in this program will also participate in the AAAI-21 Poster Sessions on Thursday, February 4 (see accepted list below). All interested AAAI-21 student registrants are invited to observe the presentations.

The full Doctoral Consortium schedule is available at

AAAI and SIGAI gratefully acknowledge the generous grant from the National Science Foundation, which makes this program possible.


AAAI-21 Doctoral Consortium Accepted Papers

DC-79: AI for Social Good: Between My Research and the Real World
Zheyuan Ryan Shi

DC-118: Effective Clustering of scRNA-seq Data to Identify Biomarkers without User Input
Hussain A. Chowdhury

DC-127: Verification and Repair of Neural Networks
Dario Guidotti

DC-169: Towards Fair, Equitable, and Efficient Peer Review
Ivan Stelmakh

DC-200: Creating Interpretable Data-Driven Approaches for Remote Health Monitoring
Alireza Ghods

DC-246: Distributed Situation Awareness for Multi-Agent Mission in Dynamic En-vironments: A Case Study of Multi-UAVs Wildfires Searching
Sagir Muhammad Yusuf, Chris Baber

DC-260: On Learning Deep Models with Imbalanced Data Distribution
Puspita Majumdar, Richa Singh, Mayank Vatsa

DC-276: A Computational Approach to Sign Language Understanding
Tejaswini Ananthanarayana

DC-281: Artificial Intelligence and Machine Learning for Autonomous Agents that Learn to Plan and Operate in Unpredictable Dynamic Environments
Leonardo Lamanna

DC-304: How Human Centered AI Will Contribute Towards Intelligent Gaming Systems
Yilei Zeng

DC-311: Perception beyond Sensors under Uncertainty
Masha Itkina

DC-314: Robots that Help Humans Build Better Mental Models of Robots
Preeti Ramaraj

DC-317: Constraint-Driven Learning of Logic Programs
Rolf Morel

DC-318: Screening for Depressed Individuals by Using Multimodal Social Media Data
Paulo Mann, Aline Paes, Elton H. Matsushima

DC-340: Multi-Agent Reinforcement Learning for Decentralized Coalition Formation Games
Kshitija Taywade

DC-415: Transfer Learning of Engagement Recognition within Robot-Assisted Therapy for Children with Autism
Nazerke Rakhymbayeva, Anara Sandygulova

DC-423: Relational Learning to Capture the Dynamics and Sparsity of Knowledge Graphs
Mehrnoosh Mirtaheri

DC-429: Safety Assurance for Systems with Machine Learning Components
Chelsea Sidrane

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