Anit Kumar Sahu

PhD from CMU working in ML/AI

Research Expertise

Federated Learning
Stochastic Optimization
Data Selection
Electrical and Electronic Engineering
Signal Processing
Applied Mathematics
Information Systems
Computer Networks and Communications
Library and Information Sciences
Computer Science Applications
Artificial Intelligence
Cognitive Neuroscience
Theoretical Computer Science
Software
Materials Chemistry
Electrochemistry
Energy Engineering and Power Technology
Control and Optimization
Mechanical Engineering
Mechanics of Materials

About

Anit Kumar Sahu is a highly accomplished researcher and engineer in the field of Electrical and Computer Engineering. He earned his PhD from Carnegie Mellon University in 2018, where he focused his research on statistical machine learning. During his time at CMU, he received the A.G. Jordan award for outstanding thesis. After completing his PhD, Anit joined Amazon Services LLC as a Senior Applied Scientist, where he works on developing innovative solutions for complex business problems using machine learning and artificial intelligence. Prior to joining Amazon, Anit worked at Bosch Center for Artificial Intelligence as a Machine Learning Research Scientist, where he developed cutting-edge algorithms for adversarial machine learning. He is currently Principal AI Scientist at GE Healthcare AI, where he is responsible for leading research and development efforts in the healthcare sector. With his extensive education and experience in both academia and industry, Anit has become a leading expert in the field of machine learning, computer vision, and artificial intelligence. He has published numerous research papers in top conferences and journals, and his work has been widely cited by other researchers in the field. Apart from his professional accomplishments, Anit is also passionate about mentoring and teaching the next generation of engineers and scientists. In his free time, Anit enjoys hiking, trying new restaurants, and traveling to new places. He also actively participates in various volunteer activities and is dedicated to giving back to his community.

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Publications

Federated Learning: Challenges, Methods, and Future Directions
IEEE Signal Processing Magazine
2020
FedDANE: A Federated Newton-Type Method
2019 53rd Asilomar Conference on Signals, Systems, and Computers
2019
MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling
2019 Sixth Indian Control Conference (ICC)
2019
Learning representations in Bayesian Confidence Propagation neural networks
2020 International Joint Conference on Neural Networks (IJCNN)
2020
Distributed stochastic optimization with gradient tracking over strongly-connected networks
2019 IEEE 58th Conference on Decision and Control (CDC)
2019
Convergence Rates for Distributed Stochastic Optimization Over Random Networks
2018 IEEE Conference on Decision and Control (CDC)
2018
Distributed Zeroth Order Optimization Over Random Networks: A Kiefer-Wolfowitz Stochastic Approximation Approach
2018 IEEE Conference on Decision and Control (CDC)
2018
Distributed Constrained Recursive Nonlinear Least-Squares Estimation: Algorithms and Asymptotics
IEEE Transactions on Signal and Information Processing over Networks
2016
Federated Learning Challenges and Opportunities: An Outlook
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
2022
Simple and Efficient Hard Label Black-box Adversarial Attacks in Low Query Budget Regimes
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining
2021
About the social role of child and adolescent psychiatrists in times of epidemic
IACAPAP ArXiv
2020
Recursive Distributed Detection for Composite Hypothesis Testing: Nonlinear Observation Models in Additive Gaussian Noise
IEEE Transactions on Information Theory
2017
NON-ASYMPTOTIC RATES FOR COMMUNICATION EFFICIENT DISTRIBUTED ZEROTH ORDER STRONGLY CONVEX OPTIMIZATION
2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)
2018
$\mathcal {CIRFE}$: A Distributed Random Fields Estimator
IEEE Transactions on Signal Processing
2018
CREDO: A Communication-Efficient Distributed Estimation Algorithm
2018 IEEE International Symposium on Information Theory (ISIT)
2018
ActPerFL: Active Personalized Federated Learning
Proceedings of the First Workshop on Federated Learning for Natural Language Processing (FL4NLP 2022)
2022
Decentralized Zeroth-Order Constrained Stochastic Optimization Algorithms: Frank–Wolfe and Variants With Applications to Black-Box Adversarial Attacks
Proceedings of the IEEE
2020
Data-driven Thermal Model Inference with ARMAX, in Smart Environments, based on Normalized Mutual Information
2018 Annual American Control Conference (ACC)
2018
Partial model averaging in Federated Learning: Performance guarantees and benefits
Neurocomputing
2023
Nonlinear Gradient Mappings and Stochastic Optimization: A General Framework with Applications to Heavy-Tail Noise
SIAM Journal on Optimization
2023
Matcha: A Matching-Based Link Scheduling Strategy to Speed up Distributed Optimization
IEEE Transactions on Signal Processing
2022
Communication efficient distributed weighted non-linear least squares estimation
EURASIP Journal on Advances in Signal Processing
2018
ILASR: Privacy-Preserving Incremental Learning for Automatic Speech Recognition at Production Scale
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
2022
Dist-Hedge: A partial information setting based distributed non-stochastic sequence prediction algorithm
2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP)
2017
Exploring the Error-Runtime Trade-off in Decentralized Optimization
2020 54th Asilomar Conference on Signals, Systems, and Computers
2020
Deep Active Learning with Noisy Oracle in Object Detection
Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
2024
Communication Efficient Distributed Estimation Over Directed Random Graphs
IEEE EUROCON 2019 -18th International Conference on Smart Technologies
2019
Field performance analysis of solar cell designs
Journal of Power Sources Advances
2024
Federated Self-Learning with Weak Supervision for Speech Recognition
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
2023
Distributed empirical risk minimization over directed graphs
2019 53rd Asilomar Conference on Signals, Systems, and Computers
2019
arXiv
100 Years of Math Milestones
2019
Large Deviations for Products of Non-Identically Distributed Network Matrices With Applications to Communication-Efficient Distributed Learning and Inference
IEEE Transactions on Signal Processing
2023
Inertial Projection Method for Solving Monotone Operator Equations
2022 12th International Conference on Information Science and Technology (ICIST)
2022
Scientometric engineering: Exploring citation dynamics via arXiv eprints
Quantitative Science Studies
2022
Large Deviations for Products of Non-I.i.d. Stochastic Matrices with Application to Distributed Detection
2018 IEEE International Symposium on Information Theory (ISIT)
2018
Distributed sequence prediction: A consensus+innovations approach
2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP)
2016
Distributed generalized likelihood ratio tests: Fundamental limits and tradeoffs
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
2016
Distributed Recursive Estimation under Heavy-Tail Communication Noise
SIAM Journal on Control and Optimization
2023
Preprint repository arXiv achieves milestone million uploads
Physics Today
2014
Distributed recursive composite hypothesis testing: Imperfect communication
2016 IEEE International Symposium on Information Theory (ISIT)
2016
On Arxiv Moderation System
Unknown Venue
2023
Fine Tuning Auto Regressive LLMs for Long Document Abstractive Summarization
2023 IEEE 2nd International Conference on Industrial Electronics: Developments & Applications (ICIDeA)
2023
Federated Representation Learning for Automatic Speech Recognition
3rd Symposium on Security and Privacy in Speech Communication
2023
Code2Drive: A Code-based Interactive and Educational Driving Environment for Improving the Youth Driving Learning and Training using Machine Learning
Machine Learning & Applications
2023
What Learned Representations and Influence Functions Can Tell Us About Adversarial Examples
Findings of the Association for Computational Linguistics: IJCNLP-AACL 2023 (Findings)
2023
Learning When to Trust Which Teacher for Weakly Supervised ASR
INTERSPEECH 2023
2023
Token Selection from Multiple Input Places
Asset Analytics
2023
Velocimeter LIDAR-Based Multiplicative Extended Kalman Filter for Terrain Relative Navigation App...
Unknown Venue
2022
Proceedings of the First Workshop on Federated Learning for Natural Language Processing (FL4NLP 2022)
Unknown Venue
2022
Optimization of Federated Learning Communications with Heterogeneous Quantization
2022 IEEE 22nd International Conference on Communication Technology (ICCT)
2022
Optimization for Data-Driven Learning and Control
Proceedings of the IEEE
2020
Distributed recursive testing of composite hypothesis in multi-agent networks
Data Fusion in Wireless Sensor Networks: A statistical signal processing perspective
2019
Carnegie Mellon University
The Grants Register 2018
2018
Queue-based broadcast gossip algorithm for consensus
2016 54th Annual Allerton Conference on Communication, Control, and Computing (Allerton)
2016
Attack Resilient Distributed Estimation: A Consensus+Innovations Approach
2018 Annual American Control Conference (ACC)
2018
Guest Editorial Inference and Learning over Networks
IEEE Transactions on Signal and Information Processing over Networks
2016
Distributed Sequential Detection for Gaussian Shift-in-Mean Hypothesis Testing
IEEE Transactions on Signal Processing
2016
Distributed sequential detection for Gaussian binary hypothesis testing: Heterogeneous networks
2014 48th Asilomar Conference on Signals, Systems and Computers
2014

Education

Carnegie Mellon University

PhD, Electrical and Computer Engineering / December, 2018

Pittsburgh, Pennsylvania, United States of America

Experience

Amazon Services LLC

Senior Applied Scientist / October, 2020August, 2024

Bosch Center for Artificial Intelligence

Machine Learning Research Scientist / January, 2019October, 2020

GE Healthcare AI

Principal AI Scientist / August, 2024Present

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