Publications

2025

• Initialization Matters: Unraveling the Impact of Pre-Training on Federated Learning
  • Divyansh Jhunjhunwala, Pranay Sharma, Zheng Xu, Gauri Joshi
  • preprint


• The Cost of Shuffling in Private Gradient-Based Optimization
  • Shuli Jiang, Pranay Sharma, Steven Wu, Gauri Joshi
  • preprint


• Federated Communication-Efficient Multi-Objective Optimization
  • Baris Askin, Pranay Sharma, Carlee Joe-Wong and Gauri Joshi
  • International Conference on Artificial Intelligence and Statistics (AISTATS), May 2025


• High-probability Convergence Bounds for Nonlinear Stochastic Gradient Descent Under Heavy-tailed Noise
  • Aleksandar Armacki, Shuhua Yu, Pranay Sharma, Gauri Joshi, Dragana Bajovic, Dusan Jakovetic, Soummya Kar
  International Conference on Artificial Intelligence and Statistics (AISTATS), May 2025


• Debiasing Federated Learning with Correlated Client Participation
  • Zhenyu Sun, Ziyang Zhang, Zheng Xu, Gauri Joshi, Pranay Sharma, Ermin Wei
  • International Conference on Learning Representations (ICLR), Apr 2025


• The Blessing of Heterogeneity in Federated Q-learning: Linear Speedup and Beyond
  • Jiin Woo, Gauri Joshi, and Yuejie Chi
  Journal on Machine Learning Research (JMLR), Feb 2025

2024

• FedECADO: A Dynamical System Model of Federated Learning
  • Aayushya Agarwal, Gauri Joshi, Larry Pileggi
  • preprint


• Nonlinear Stochastic Gradient Descent and Heavy-tailed Noise: A Unified Framework and High-probability Guarantees
  • Aleksandar Armacki, Shuhua Yu, Pranay Sharma, Gauri Joshi, Dragana Bajovic, Dusan Jakovetic, Soummya Kar
  preprint


• Job Assignment in Machine Learning Inference Systems with Accuracy Constraints
  • Tuhinangshu Choudhury, Weina Wang, Gauri Joshi
  • Performance Evaluation Journal, Elvesier, Dec 2024


• Optimized Tradeoffs for Private Prediction with Majority Ensembling
  • Shuli Jiang, Qiuyu Zhang, Gauri Joshi
  • Transaction on Machine Learning Research (TMLR), 2024


• Heterogeneous LoRA for Federated Fine-tuning of On-device Foundation Models
  • Yae Jee Cho, Luyang Liu, Zheng Xu, Aldi Fahrezi, Matt Barnes, Gauri Joshi
  • Conference on Empirical Methods in Natural Language Processing (EMNLP), Nov 2024
  
  
  • shorter version in Workshop on Federated Learning in the Age of Foundation Models, Neural Information Processing Systems (NeurIPS), Dec 2023


• Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices
  • Jiin Woo, Laixi Shi, Gauri Joshi, and Yuejie Chi
  • International Conference on Machine Learning (ICML), July 2024


• FedAST: Federated Asynchronous Simultaneous Training
  • Baris Askin, Pranay Sharma, Carlee Joe-Wong and Gauri Joshi
  • Conference on Uncertainty in Artificial Intelligence (UAI), July 2024


• Erasure Coded Neural Network Inference via Fisher Averaging
  • Divyansh Jhunjhunwala, Neharika Jali, Gauri Joshi and Shiqiang Wang,
  International Symposium on Information Theory (ISIT), July 2024


• On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data
  • Jianyu Wang, Rudrajit Das, Gauri Joshi, Satyen Kale, Zheng Xu, Tong Zhang
  Transactions of Machine Learning Research (TMLR), June 2024


• Efficient Reinforcement Learning for Routing Jobs in Heterogeneous Queueing Systems
  • Neharika Jali, Guannan Qu, Weina Wang, and Gauri Joshi
  International Conference on Artificial Intelligence and Statistics (AISTATS), May 2024


• FedFisher: Leveraging Fisher Information for One-Shot Federated Learning
  • Divyansh Jhunjhunwala, Shiqiang Wang, and Gauri Joshi
  International Conference on Artificial Intelligence and Statistics (AISTATS), May 2024


• Maximizing Global Model Appeal in Federated Learning
  • Yae Jee Cho, Divyansh Jhunjhunwala, Tian Li, Virginia Smith, Gauri Joshi
  • Transactions on Machine Learning Research (TMLR), Apr 2024


• On Improved Distributed Random Reshuffling Over Networks
  • Pranay Sharma, Jiarui Li, and Gauri Joshi
  International Conference on Acoustics, Speech, and Signal Processing (ICASSP), April 2024

2023

• Correlation aware Sparsified Mean Estimation Using Random Projection
  • Shuli Jiang, Pranay Sharma, and Gauri Joshi
  Neural Information Processing Systems (NeurIPS), Dec 2023


• Federated Minimax Optimization with Client Heterogeneity
  • Pranay Sharma, Rohan Panda, Gauri Joshi
  Transactions on Machine Learning Research (TMLR), Dec 2023


• Local or Global: Selective Knowledge Assimilation for Federated Learning with Limited Labels
  • Yae Jee Cho, Gauri Joshi, and Dimitrios Dimitriadis
  International Conference on Computer Vision (ICCV), Oct 2023


• Towards a Theoretical and Practical Understanding of One-Shot Federated Learning with Fisher Information
  • Divyansh Jhunjhunwala, Shiqiang Wang, and Gauri Joshi
  Federated Learning and Analytics workshop at ICML, July 2023


• The Blessing of Heterogeneity in Federated Q-learning: Linear Speedup and Beyond
  • Jiin Woo, Gauri Joshi, and Yuejie Chi
  International Conference on Machine Learning (ICML), July 2023


• On the Convergence of Federated Averaging with Cyclic Client Participation
  • Yae Jee Cho, Pranay Sharma, Gauri Joshi, Zheng Xu, Satyen Kale, Tong Zhang
  International Conference on Machine Learning (ICML), July 2023


• FedExP: Speeding up Federated Averaging via Extrapolation
  • Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi
  • International Conference on Learning Representations (ICLR), May 2023
  • Selected for a Spotlight presentation (top 25% of accepted papers)


• Federated Learning under Distributed Concept Drift
  • Ellango Jothimurugesan, Kevin Hsieh, Jianyu Wang, Gauri Joshi, Phillip B. Gibbons
  • International Conference on Artificial Intelligence and Statistics (AISTATS), Apr 2023
  • Selected for an Oral presentation (top 6% of accepted papers)
    
    
  • short version presented at the Workshop on Distribution Shifts at Neural Information Processing Systems, Dec 2022


• Communication-Efficient and Model-Heterogeneous Personalized Federated Learning via Clustered Knowledge Transfer
  • Yae Jee Cho, Jianyu Wang, Tarun Chiruvolu, Gauri Joshi
  • IEEE Journal of Selected Topics in Signal Processing, Jan 2023

2022

• Optimization Algorithms for Distributed Machine Learning
  • Gauri Joshi
  • Spring Nature Synthesis Lectures on Learning, Networking and Algorithms, Dec 2022


• To Federate or Not To Federate: Incentivizing Client Participation in Federated Learning
  • Yae Jee Cho, Divyansh Jhunjhunwala, Tian Li, Virginia Smith, Gauri Joshi
  • FedML Workshop at Neural Information Processing Systems, Dec 2022
  • Selected for an oral presentation


• Rateless Sum Recovery Codes for Distributed Non-linear Computations
  • Ankur Mallick and Gauri Joshi
  • Information Theory Workshop (ITW), Nov 2022


• Multi-Model Federated Learning with Provable Guarantees
  • Neelkamal Bhuyan, Sharayu Moharir, Gauri Joshi
  • EAI Valuetools, Nov 2022


• MATCHA: A Matching-Based Link Scheduling Strategy to Speed up Distributed Optimization
  • Jianyu Wang, Anit Sahu, Gauri Joshi, Soummya Kar
  • IEEE Transactions on Signal Processing, Oct 2022


• Tackling Heterogeneous Traffic in Multi-access Systems via Erasure Coded Servers
  • Tuhinangshu Choudhury, Weina Wang, Gauri Joshi
  • ACM MobiHoc, International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, Oct 2022
  • Best Paper Award


• Correlated Combinatorial Bandits for Online Resource Allocation
  • Samarth Gupta, Jinhang Zuo, Carlee Joe-Wong, Gauri Joshi, Osman Yagan
  • ACM MobiHoc, International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, Oct 2022
  • Best Poster Award for a short version presented at SIGMETRICS 2022


• FedVARP: Tackling the Variance Due to Partial Client Participation in Federated Learning
  • Divyansh Jhunjhunwala, Pranay Sharma, Aushim Nagarkatti, Gauri Joshi
  • Conference on Uncertainty in Artificial Intelligence (UAI), Aug 2022


• Federated Reinforcement Learning: Communication-Efficient Algorithms and Convergence Analysis
  • Sajad Khodadadian, Pranay Sharma, Gauri Joshi, Siva Theja Maguluri
  International Conference on Machine Learning (ICML), July 2022
  • selected for a long presentation (2.1% of submitted papers)


• Federated Minimax Optimization: Improved Convergence Analyses and Algorithms
  • Pranay Sharma, Rohan Panda, Gauri Joshi, Pramod K. Varshney
  International Conference on Machine Learning (ICML), July 2022


• Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning
  • Yae Jee Cho, Andre Manoel, Gauri Joshi, Robert Sim, and Dimitrios Dimitriadis
  • International Joint Conference on Artificial Intelligence (IJCAI), July 2022


• Chapter on Communication-Efficient Distributed Optimization Algorithms
  • Shiqiang Wang and Gauri Joshi
  • in the Book on "Federated Learning: A Comprehensive Overview of Methods and Applications", edited by Heiko Ludwig and Nathalie Baracaldo
  • Springer Publications, July 2022


• Rateless Codes for Near-Perfect Load Balancing in Distributed Matrix-vector Multiplication
  • Ankur Mallick, Malhar Chaudhari, Ganesh Palanikumar, Utsav Sheth, Gauri Joshi
  • featured as a Research Highlight in the Communications of the ACM, May 2022


• Matchmaker: Data Drift Mitigation in Machine Learning for Large-Scale Systems
  • Ankur Mallick, Kevin Hsieh, Behnaz Arzani, Gauri Joshi
  • Conference on Machine Learning and Systems (MLSys), Aug 2022


• A Dynamic Reweighting Strategy for Fair Federated Learning
  • Zhiyuan Zhao and Gauri Joshi
  International Conference on Acoustics, Speech, and Signal Processing (ICASSP), May 2022


• Client Selection in Federated Learning: Convergence Analysis and Power-of-Choice Selection Strategies
  • Yae Jee Cho, Jianyu Wang, Gauri Joshi
  • International Conference on Artificial Intelligence and Statistics (AISTATS), March 2022

2021

• Local Adaptivity in Federated Learning: Convergence and Consistency
  • Jianyu Wang, Zheng Xu, Zachary Garrett, Zachary Charles, Luyang Liu, Gauri Joshi
  • preprint, 2021


• FedLite: A Scalable Approach for Federated Learning on Resource-constrained Clients
  • Jianyu Wang, Hang Qi, Ankit Singh Rawat, Sashank Reddi, Sagar Waghmare, Felix X. Yu, Gauri Joshi
  preprint, 2021


• Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation
  • Divyansh Jhunjhunwala, Ankur Mallick, Advait Gadhikar, Swanand Kadhe, Gauri Joshi
  • Neural Information Processing Systems (NeurIPS), Dec 2021


• Runtime estimation for machine learning tasks
  • Parijat Dube, Gauri Joshi, Priya Ashok Nagpurkar, Stefania Costache, Diana Jeanne Arroyo, Zehra Noman Sura
  • US Patent number 11200512, Dec 2021


• Adaptive learning rate schedule in distributed stochastic gradient descent
  • Parijat Dube, Sanghamitra Dutta, Gauri Joshi, Priya A Nagpurkar
  • US Patent number 11182689, Nov 2021


• Service Rate Region: A New Aspect of Coded Distributed System Design
  • Mehmet Aktas, Gauri Joshi, Swanand Kadhe, Fatemeh Kazemi, Emina Soljanin
  • IEEE Transactions on Information Theory, Oct 2021


• Rateless Codes for Distributed Non-linear Computations
  • Ankur Mallick, Sophie Smith, Gauri Joshi
  • International Symposium on Topics in Coding, Sept 2021


• Slow and Stale Gradients Can Win the Race
  • Sanghamitra Dutta, Jianyu Wang and Gauri Joshi
  • Journal on Selected Areas of Information Theory (JSAIT) Special Issue, 2021


• A Novel Framework for the Analysis and Design of Heterogeneous Federated Learning
  • Jianyu Wang, Qinghua Liu, Hao Liang, Gauri Joshi and H. Vincent Poor
  • IEEE Transactions on Signal Processing, Sept 2021


• A Field Guide to Federated Optimization
  • 53 authors including primary editors Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi and H. Brendan McMahan
  • Technical Report, July 2021


• Adaptive Quantization of Model Updates for Communication-Efficient Federated Learning
  • Divyansh Jhunjhunwala, Advait Gadhikar, Gauri Joshi, Yonina C. Eldar
  • International Conference on Acoustics, Speech, and Signal Processing (ICASSP), June 2021


• Cooperative SGD: A Unified Framework for the Analysis of Local-Update SGD
  • Jianyu Wang, Gauri Joshi
  • Journal of Machine Learning Research (JMLR), 2021


• Advances and Open Problems in Federated Learning
  • 58 authors, including Peter Kairouz, Brendan McMahan, Jianyu Wang and Gauri Joshi
  • Foundations and Trends in Machine Learning, 2021


• Machine Learning on Volatile Instances
  • Xiaoxi Zhang, Jianyu Wang, Li-Feng Lee, Tom Yang, Akansha Kalra, Gauri Joshi, Carlee Joe-Wong
  • IEEE/ACM Transactions on Networking, Sept 2021


• Synergy via Redundancy: Adaptive Replication Strategies and Fundamental Limits
  • Gauri Joshi and Dhruva Kaushal
  • IEEE ACM/Transactions on Networking, 2021


• Job Dispatching Policies for Queueing Systems with Unknown Service Rates
  • Tuhinangshu Choudhury, Gauri Joshi, Weina Wang and Sanjay Shakkottai
  • ACM MobiHoc, July 2021


• Best-arm Identification in Correlated Multi-armed Bandits
  • Samarth Gupta, Gauri Joshi, Osman Yagan
  • Journal on Selected Areas of Information Theory (JSAIT) Special Issue on Sequential, Active, and Reinforcement Learning, 2021


• Multi-armed Bandits with Correlated Arms
  • Samarth Gupta, Shreyas Chaudhari, Gauri Joshi, Osman Yagan
  • IEEE Transactions on Information Theory, May 2021
  
  
  • shorter version appeared in the ICML Workshop on Theoretical Foundations of RL, July 2020


• A Unified Approach to Translate Classic Bandit Algorithms to the Structured Bandit Setting
  • Samarth Gupta, Shreyas Chaudhari, Subhojyoti Mukherjee, Gauri Joshi, Osman Yagan
  • Journal on Selected Areas of Information Theory (JSAIT) Special Issue on Estimation and Inference, 2021
  
  
  • shorter version in International Conference on Acoustics, Speech, and Signal Processing (ICASSP), June 2021


• Deep Probabilistic Kernels for Sample Efficient Learning
  • Ankur Mallick, Chaitanya Dwivedi, Bhavya Kailkhura, Gauri Joshi, T. Yong-Jin Han
  • Conference on Uncertainty in Artificial Intelligence (UAI), July 2021
  • Selected for an Oral Presentation
    
    
  • shorter version in the ICLR From Shallow to Deep: Overcoming Limited and Adverse Data (S2D-OLAD) Workshop, May 2021

2020

• Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization
  • Jianyu Wang, Qinghua Liu, Hao Liang, Gauri Joshi, H. Vincent Poor
  • Neural Information Processing Systems (NeurIPS), Dec 2020
  • Best Poster Award at the NSF TRIPODS workshop on communication-efficient distributed optimization


• Bandit-based Communication-Efficient Client Selection Strategies for Federated Learning
  • Yae Jee Cho, Samarth Gupta, Gauri Joshi, Osman Yagan
  • Asilomar Conference, Nov 2020


• Exploring the Error-Runtime Trade-off in Decentralized Optimization
  • Jianyu Wang, Anit Sahu, Gauri Joshi, Soummya Kar
  • Asilomar Conference, Nov 2020


• Probabilistic Neighbourhood Component Analysis: Sample-Efficient Uncertainty Estimation in Deep Learning
  • Ankur Mallick, Chaitanya Dwivedi, Bhavya Kailkhura, Gauri Joshi, T. Yong-Jin Han
  • ICML Workshop on Uncertainty and Robustness in Deep Learning, July 2020


• Rateless Codes for Near-Perfect Load Balancing in Distributed Matrix-vector Multiplication
  • Ankur Mallick, Malhar Chaudhari, Ganesh Palanikumar, Utsav Sheth, Gauri Joshi
  • ACM SIGMETRICS, June 2020
  • Best Paper Award


• Correlated Multi-armed Bandits with a Latent Random Source
  • Samarth Gupta, Gauri Joshi, Osman Yagan
  • International Conference on Acoustics, Speech, and Signal Processing (ICASSP), May 2020


• Overlap Local-SGD: An Algorithmic Approach to Hide Communication Delays in Distributed SGD
  • Jianyu Wang, Hao Liang, Gauri Joshi
  • International Conference on Acoustics, Speech, and Signal Processing (ICASSP), May 2020


• Machine Learning on Volatile Instances
  • Xiaoxi Zhang, Jianyu Wang, Gauri Joshi, Carlee Joe-Wong
  • IEEE Intl. Conf. on Computer Communications (INFOCOM), April 2020


• Accelerating Deep Learning by Focusing on the Biggest Losers
  • Angela H. Jiang, Daniel L.-K. Wong, Giulio Zhou, David G. Andersen, Jeffrey Dean, Gregory R. Ganger, Gauri Joshi, Michael Kaminksy, Michael Kozuch, Zachary C. Lipton, Padmanabhan Pillai
  • preprint

2019

• MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling
  • Jianyu Wang, Anit Sahu, Gauri Joshi, Soummya Kar
  • NeurIPS workshop of Federated Learning for Data Privacy and Confidentiality, Dec 2019
  • Distinguished Student Paper Award


• Cooperative SGD: A Unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms
  • Jianyu Wang, Gauri Joshi
  • International Conf. on Machine Learning (ICML) CodML Workshop, June 2019


• Rateless Codes for Distributed Computations with Sparse Compressed Matrices
  • Ankur Mallick, Gauri Joshi
  • international Symposium on Information Theory (ISIT), July 2019


• Fast and Efficient Distributed Matrix-Vector Multiplication Using Rateless Fountain Codes
  • Ankur Mallick, Malhar Chaudhari, Gauri Joshi
  • International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2019


• Adaptive Communication Strategies to Achieve the Best Error-Runtime Trade-off in Local-Update SGD
  • Jianyu Wang, Gauri Joshi
  • SysML Conference, March 2019


• Efficient Straggler Replication in Large-scale Parallel Computing
  • Da Wang, Gauri Joshi, and Gregory Wornell,
  • ACM Trans. on Modeling and Perf. Eval. of Comp. Systems, 2019

2018

• Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD
  • Sanghamitra Dutta, Gauri Joshi, Soumyadip Ghosh, Parijat Dube, Priya Nagpurkar,
  • International Conference on Artificial Intelligence and Statistics (AISTATS), Apr 2018


• Active Distribution Learning from Indirect Samples
  • Samarth Gupta, Gauri Joshi, Osman Yagan
  • Allerton Conference on Communication, Control and Computing, Oct 2018


• Service Capacity Region of Content Access from Erasure Coded Storage
  • Sarah E. Anderson, Ann Johnston, Gauri Joshi, Gretchen L. Matthews, Carolyn Mayer, and Emina Soljanin
  • IEEE Information Theory Workshop, Nov 2018


• Adaptive Communication Strategies to Achieve the Best Error-Runtime Trade-off in Local-Update SGD
  • Jianyu Wang, Gauri Joshi
  • NeurIPS MLSys Workshop, Dec 2018

2017

• Synergy via Redundancy: Boosting Service Capacity via Adaptive Task Replication
  • Gauri Joshi,
  • ACM/IFIP Performance, Nov 2017


• On the Service Capacity Region of Accessing Erasure Coded Content
  • Mehmet Aktas, Sarah E. Anderson, Ann Johnston, Gauri Joshi, Swanand Kadhe, Gretchen L. Matthews, Carolyn Mayer, and Emina Soljanin
  • Allerton Conference on Communication, Control, and Computing, Oct 2017


• Efficient Redundancy Techniques for Latency Reduction in Cloud Systems
  • Gauri Joshi, Emina Soljanin and Gregory Wornell,
  • ACM Trans. on Modeling and Perf. Eval. of Comp. Systems, vol. 2, no. 12, May 2017


• Boosting Service Capacity via Adaptive Task Replication
  • Gauri Joshi,
  • ACM Sigmetrics MAMA workshop, Jun 2017

2015-2016

• Efficient Redundancy Techniques to Reduce Delay in Cloud Systems
  • Doctoral Thesis, MIT, June 2016
  
  
• Efficient Replication of Queued Tasks to Reduce Latency in Cloud Systems
  • Gauri Joshi, Emina Soljanin, and Gregory Wornell,
  • Allerton Conference on Communication, Control and Computing, Oct 2015
  
  
• Queues with Redundancy: Latency-Cost Analysis
  • Gauri Joshi, Emina Soljanin, and Gregory Wornell,
  • Mathematical Modeling and Analysis (MAMA) Workshop, Jun 2015
  
  
• Using Straggler Replication to Reduce Latency in Large-scale Parallel Computing
  • Da Wang, Gauri Joshi, and Gregory Wornell,
  • Distributed Cloud Computing (DCC) Workshop, Jun 2015
  
  
• Playback Delay in On-Demand Streaming Communication with Feedback
  • Kaveh Mahadaviani, Ashish Khisti, Gauri Joshi, and Gregory Wornell,
  • International Symposium on Information Theory, July 2015

2014

• Efficient Job Replication for Fast Response Times in Parallel Computation
  • Da Wang, Gauri Joshi, and Gregory Wornell,
  • ACM Sigmetrics short paper Jun 2014
  
  
• Throughput-Smoothness Trade-offs in Multicasting an Ordered Packet Stream
  • Gauri Joshi, Yuval Kochman, and Gregory Wornell,
  • International Symposium on Network Coding, Jun 2014
  
  
• On the Delay-Storage Trade-off in Content Download from Distributed Storage
  • Gauri Joshi, Yanpei Liu, and Emina Soljanin,
  • IEEE Journal on Selected Areas of Communications, vol. 32, no. 5, May 2014


• Effect of Block-wise Feedback on the Throughput-Delay Trade-off in Streaming
  • Gauri Joshi, Yuval Kochman, and Gregory Wornell,
  • INFOCOM workshop on Contemporary Video, Apr 2014

2012-2013

• Round-robin Overlapping Generations Coding for Fast Content Download
  • Gauri Joshi and Emina Soljanin,
  • International Symposium on Information Theory, Jul 2013
  
  
• Coding for Fast Content Download
  • Gauri Joshi, Yanpei Liu, and Emina Soljanin,
  • Allerton Conference on Communication, Control and Computing, Oct 2012
  
  
• On Playback Delay in Streaming Communication
  • Gauri Joshi, Yuval Kochman, and Gregory Wornell,
  • International Symposium on Information Theory, Jul 2012
  
  
• On Playback Delay in Streaming Communication
  • Masters Thesis, MIT, May 2012,
  • William Martin Memorial Best Thesis Award

2010-2011

• Fountain Codes
  • Gauri Joshi, Joong Bum Rhim, John Sun, Da Wang
  • Project Report 6.451, Dec 2010


• Downlink Erlang Capacity of Cellular OFDMA
  • Gauri Joshi, Harshad Maral, and Abhay Karandikar,
  • National Conference on Communications, Jan 2011
  
  
• Optimal Relay Placement for Cellular Coverage Extension
  • Gauri Joshi and Abhay Karandikar,
  • National Conference on Communications, Jan 2011
  
  
• Performance Analysis of Active Handoff in CDMA2000 Femtocells
  • Gauri Joshi, Mehmet Yavuz, and Chirag Patel,
  • National Conference on Communications, Jan 2010


• On Relay-assisted Cellular Networks
  • Masters Thesis, IIT Bombay, June 2010