Sotabase

Career

· Member Of Technical Staff, Amazon2025–
· Senior Applied Scientist, Amazon2023–2025
· Applied Scientist II, Amazon2021–2023
· Research Intern And Student Researcher At Cloud AI, Google2017–2018
· Doctor of Philosophy - PhD, University of Illinois at Urbana-Champaign2017–2022
· at University of Illinois, Urbana-Champaign2017–2022
· Software Engineering Intern In Research, Google2016–2016
· Graduate Research Assistant, Coordinated Science Laboratory at University of Illinois2014–2021
· Master’s Degree, University of Illinois at Urbana-Champaign2014–2017
· at University of Illinois, Urbana-Champaign2014–2017
· Bachelor’s Degree, Indian Institute of Technology, Madras2010–2014

Publications (32)

Attention-based Graph Neural Network for Semi-supervised Learning
arXiv.org · 2018
370
cited
Efficient Algorithms for Smooth Minimax Optimization
Neural Information Processing Systems · 2019
201
cited
InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs
International Conference on Machine Learning · 2019
102
cited
Robustness of Conditional GANs to Noisy Labels
Neural Information Processing Systems · 2018
87
cited
Learning from Comparisons and Choices
Journal of machine learning research · 2017
42
cited
InfoGAN-CR: Disentangling Generative Adversarial Networks with Contrastive Regularizers
International Conference on Machine Learning · 2019
37
cited
Lifted Primal-Dual Method for Bilinearly Coupled Smooth Minimax Optimization
International Conference on Artificial Intelligence and Statistics · 2022
34
cited
Collaboratively Learning Preferences from Ordinal Data
Neural Information Processing Systems · 2015
28
cited
Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method
Neural Information Processing Systems · 2020
26
cited
Sample Efficient Linear Meta-Learning by Alternating Minimization
arXiv.org · 2021
25
cited
Efficient Algorithms for Federated Saddle Point Optimization
arXiv.org · 2021
24
cited
Statistically and Computationally Efficient Linear Meta-representation Learning
Neural Information Processing Systems · 2021
23
cited
Bring Your Own Algorithm for Optimal Differentially Private Stochastic Minimax Optimization
Neural Information Processing Systems · 2022
22
cited
DPZero: Private Fine-Tuning of Language Models without Backpropagation
International Conference on Machine Learning · 2023
22
cited
FedChain: Chained Algorithms for Near-optimal Communication Cost in Federated Learning
International Conference on Learning Representations · 2021
15
cited
Combinatorial Resource Allocation Using Submodularity of Waterfilling
IEEE Transactions on Wireless Communications · 2016
14
cited
DPZero: Dimension-Independent and Differentially Private Zeroth-Order Optimization
arXiv.org · 2023
12
cited
Accelerating Sinkhorn Algorithm with Sparse Newton Iterations
International Conference on Learning Representations · 2024
10
cited
Reducing the Communication Cost of Federated Learning through Multistage Optimization
arXiv.org · 2021
8
cited
FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information Gain
International Conference on Machine Learning · 2025
6
cited
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Kivanc Thekumparampil | Researcher Profile | Sotabase | Sotabase