354 citations · 600 across the 29 of their papers we have counts for
31 papers
Dealing Doubt: Unveiling Threat Models in Gradient Inversion Attacks under Federated Learning, A Survey and Taxonomy
Yichuan Shi, Olivera Kotevska, Viktor Reshniak +2
Federated Learning (FL) has emerged as a leading paradigm for decentralized, privacy preserving machine learning training. However, recent research on gradient inversion attacks (G…
DecentNeRFs: Decentralized Neural Radiance Fields from Crowdsourced Images
Zaid Tasneem, Akshat Dave, Abhishek Singh +4
Neural radiance fields (NeRFs) show potential for transforming images captured worldwide into immersive 3D visual experiences. However, most of this captured visual data remains si…
CoDream: Exchanging dreams instead of models for federated aggregation with heterogeneous models
Abhishek Singh, Gauri Gupta, Ritvik Kapila +5
Federated Learning (FL) enables collaborative optimization of machine learning models across decentralized data by aggregating model parameters. Our approach extends this concept b…
Scalable Collaborative Learning via Representation Sharing
Frédéric Berdoz, Abhishek Singh, Martin Jaggi +1
Privacy-preserving machine learning has become a key conundrum for multi-party artificial intelligence. Federated learning (FL) and Split Learning (SL) are two frameworks that enab…
Learning to Censor by Noisy Sampling
Ayush Chopra, Abhinav Java, Abhishek Singh +2
Point clouds are an increasingly ubiquitous input modality and the raw signal can be efficiently processed with recent progress in deep learning. This signal may, often inadvertent…
Decouple-and-Sample: Protecting sensitive information in task agnostic data release
Abhishek Singh, Ethan Garza, Ayush Chopra +3
We propose sanitizer, a framework for secure and task-agnostic data release. While releasing datasets continues to make a big impact in various applications of computer vision, its…
AdaSplit: Adaptive Trade-offs for Resource-constrained Distributed Deep Learning
Ayush Chopra, Surya Kant Sahu, Abhishek Singh +4
Distributed deep learning frameworks like federated learning (FL) and its variants are enabling personalized experiences across a wide range of web clients and mobile/IoT devices.…
Vaccination Worldwide: Strategies, Distribution and Challenges
Chirag Samal, Kasia Jakimowicz, Krishnendu Dasgupta +26
The Coronavirus 2019 (Covid-19) pandemic caused by the SARS-CoV-2 virus represents an unprecedented crisis for our planet. It is a bane of the über connected world that we live in…
Can Self Reported Symptoms Predict Daily COVID-19 Cases?
Parth Patwa, Viswanatha Reddy, Rohan Sukumaran +6
The COVID-19 pandemic has impacted lives and economies across the globe, leading to many deaths. While vaccination is an important intervention, its roll-out is slow and unequal ac…
Automatic calibration of time of flight based non-line-of-sight reconstruction
Subhash Chandra Sadhu, Abhishek Singh, Tomohiro Maeda +4
Time of flight based Non-line-of-sight (NLOS) imaging approaches require precise calibration of illumination and detector positions on the visible scene to produce reasonable resul…
Safepaths: Vaccine Diary Protocol and Decentralized Vaccine Coordination System using a Privacy Preserving User Centric Experience
Abhishek Singh, Ramesh Raskar, Anna Lysyanskaya
In this early draft, we present an end-to-end decentralized protocol for the secure and privacy preserving workflow of vaccination, vaccination status verification, and adverse rea…
Mobile Apps Prioritizing Privacy, Efficiency and Equity: A Decentralized Approach to COVID-19 Vaccination Coordination
Joseph Bae, Rohan Sukumaran, Sheshank Shankar +8
In this early draft, we describe a decentralized, app-based approach to COVID-19 vaccine distribution that facilitates zero knowledge verification, dynamic vaccine scheduling, cont…
MIT SafePaths Card (MiSaCa): Augmenting Paper Based Vaccination Cards with Printed Codes
Joseph Bae, Rohan Sukumaran, Sheshank Shankar +19
In this early draft, we describe a user-centric, card-based system for vaccine distribution. Our system makes use of digitally signed QR codes and their use for phased vaccine dist…
Spatial K-anonymity: A Privacy-preserving Method for COVID-19 Related Geospatial Technologies
Rohan Iyer, Regina Rex, Kevin P. McPherson +4
There is a growing need for spatial privacy considerations in the many geo-spatial technologies that have been created as solutions for COVID-19-related issues. Although effective…
COVID-19 Outbreak Prediction and Analysis using Self Reported Symptoms
Rohan Sukumaran, Parth Patwa, T V Sethuraman +9
It is crucial for policymakers to understand the community prevalence of COVID-19 so combative resources can be effectively allocated and prioritized during the COVID-19 pandemic.…
COVID-19 Tests Gone Rogue: Privacy, Efficacy, Mismanagement and Misunderstandings
Manuel Morales, Rachel Barbar, Darshan Gandhi +27
COVID-19 testing, the cornerstone for effective screening and identification of COVID-19 cases, remains paramount as an intervention tool to curb the spread of COVID-19 both at loc…
Verifiable Proof of Health using Public Key Cryptography
Abhishek Singh, Ramesh Raskar
In the current pandemic, testing continues to be the most important tool for monitoring and curbing the disease spread and early identification of the disease to perform health-rel…
Digital Landscape of COVID-19 Testing: Challenges and Opportunities
Darshan Gandhi, Rohan Sukumaran, Priyanshi Katiyar +23
The COVID-19 Pandemic has left a devastating trail all over the world, in terms of loss of lives, economic decline, travel restrictions, trade deficit, and collapsing economy inclu…
DISCO: Dynamic and Invariant Sensitive Channel Obfuscation for deep neural networks
Abhishek Singh, Ayush Chopra, Vivek Sharma +4
Recent deep learning models have shown remarkable performance in image classification. While these deep learning systems are getting closer to practical deployment, the common assu…
Clinical Landscape of COVID-19 Testing: Difficult Choices
Darshan Gandhi, Sanskruti Landage, Joseph Bae +12
The coronavirus disease 2019 (COVID-19) pandemic has spread rapidly across the world, leading to enormous amounts of human death and economic loss. Until definitive preventive or c…
Proximity Inference with Wifi-Colocation during the COVID-19 Pandemic
Mikhail Dmitrienko, Abhishek Singh, Patrick Erichsen +1
In this work we propose a WiFi colocation methodology for digital contact tracing. The approach works by having a device scan and store nearby access point information to perform p…
Target Privacy Threat Modeling for COVID-19 Exposure Notification Systems
Ananya Gangavarapu, Ellie Daw, Abhishek Singh +4
The adoption of digital contact tracing (DCT) technology during the COVID-19pandemic has shown multiple benefits, including helping to slow the spread of infectious disease and to…
Proximity Sensing: Modeling and Understanding Noisy RSSI-BLE Signals and Other Mobile Sensor Data for Digital Contact Tracing
Sheshank Shankar, Rishank Kanaparti, Ayush Chopra +6
As we await a vaccine, social-distancing via efficient contact tracing has emerged as the primary health strategy to dampen the spread of COVID-19. To enable efficient digital cont…
NoPeek: Information leakage reduction to share activations in distributed deep learning
Praneeth Vepakomma, Abhishek Singh, Otkrist Gupta +1
For distributed machine learning with sensitive data, we demonstrate how minimizing distance correlation between raw data and intermediary representations reduces leakage of sensit…