73 citations · 118 across the 24 of their papers we have counts for
26 papers
The Iceberg Index: Measuring Skills-centered Exposure in the AI Economy
Ayush Chopra, Santanu Bhattacharya, DeAndrea Salvador +7
Artificial Intelligence is reshaping America's $9.4 trillion labor market, with cascading effects that extend far beyond visible technology sectors. When AI transforms quality con…
Ripple Effect Protocol: Coordinating Agent Populations
Ayush Chopra, Aman Sharma, Feroz Ahmad +3
Modern AI agents can exchange messages using protocols such as A2A and ACP, yet these mechanisms emphasize communication over coordination. As agent populations grow, this limitati…
Upgrade or Switch: Do We Need a Next-Gen Trusted Architecture for the Internet of AI Agents?
Ramesh Raskar, Pradyumna Chari, Jared James Grogan +11
The emerging Internet of AI Agents challenges existing web infrastructure designed for human-scale, reactive interactions. Unlike traditional web resources, autonomous AI agents in…
A High-Resolution, US-scale Digital Similar of Interacting Livestock, Wild Birds, and Human Ecosystems with Applications to Multi-host Epidemic Spread
Abhijin Adiga, Ayush Chopra, Mandy L. Wilson +8
One Health issues, such as the spread of highly pathogenic avian influenza~(HPAI), present significant challenges at the human-animal-environmental interface. Recent H5N1 outbreaks…
On the limits of agency in agent-based models
Ayush Chopra, Shashank Kumar, Nurullah Giray-Kuru +2
Agent-based modeling (ABM) offers powerful insights into complex systems, but its practical utility has been limited by computational constraints and simplistic agent behaviors, es…
Private Agent-Based Modeling
Ayush Chopra, Arnau Quera-Bofarull, Nurullah Giray-Kuru +2
The practical utility of agent-based models in decision-making relies on their capacity to accurately replicate populations while seamlessly integrating real-world data streams. Ye…
First 100 days of pandemic; an interplay of pharmaceutical, behavioral and digital interventions -- A study using agent based modeling
Gauri Gupta, Ritvik Kapila, Ayush Chopra +1
Pandemics, notably the recent COVID-19 outbreak, have impacted both public health and the global economy. A profound understanding of disease progression and efficient response str…
SARC: Soft Actor Retrospective Critic
Sukriti Verma, Ayush Chopra, Jayakumar Subramanian +4
The two-time scale nature of SAC, which is an actor-critic algorithm, is characterised by the fact that the critic estimate has not converged for the actor at any given time, but s…
Bayesian calibration of differentiable agent-based models
Arnau Quera-Bofarull, Ayush Chopra, Anisoara Calinescu +2
Agent-based modelling (ABMing) is a powerful and intuitive approach to modelling complex systems; however, the intractability of ABMs' likelihood functions and the non-differentiab…
Differentiable Agent-based Epidemiology
Ayush Chopra, Alexander Rodríguez, Jayakumar Subramanian +4
Mechanistic simulators are an indispensable tool for epidemiology to explore the behavior of complex, dynamic infections under varying conditions and navigate uncertain environment…
On Conditioning the Input Noise for Controlled Image Generation with Diffusion Models
Vedant Singh, Surgan Jandial, Ayush Chopra +3
Conditional image generation has paved the way for several breakthroughs in image editing, generating stock photos and 3-D object generation. This continues to be a significant are…
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.…
DeepABM: Scalable, efficient and differentiable agent-based simulations via graph neural networks
Ayush Chopra, Esma Gel, Jayakumar Subramanian +5
We introduce DeepABM, a framework for agent-based modeling that leverages geometric message passing of graph neural networks for simulating action and interactions over large agent…
ZFlow: Gated Appearance Flow-based Virtual Try-on with 3D Priors
Ayush Chopra, Rishabh Jain, Mayur Hemani +1
Image-based virtual try-on involves synthesizing perceptually convincing images of a model wearing a particular garment and has garnered significant research interest due to its im…
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.…
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…
MixBoost: Synthetic Oversampling with Boosted Mixup for Handling Extreme Imbalance
Anubha Kabra, Ayush Chopra, Nikaash Puri +4
Training a classification model on a dataset where the instances of one class outnumber those of the other class is a challenging problem. Such imbalanced datasets are standard in…
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…
SAC: Semantic Attention Composition for Text-Conditioned Image Retrieval
Surgan Jandial, Pinkesh Badjatiya, Pranit Chawla +3
The ability to efficiently search for images is essential for improving the user experiences across various products. Incorporating user feedback, via multi-modal inputs, to naviga…
Retrospective Loss: Looking Back to Improve Training of Deep Neural Networks
Surgan Jandial, Ayush Chopra, Mausoom Sarkar +3
Deep neural networks (DNNs) are powerful learning machines that have enabled breakthroughs in several domains. In this work, we introduce a new retrospective loss to improve the tr…
SimPropNet: Improved Similarity Propagation for Few-shot Image Segmentation
Siddhartha Gairola, Mayur Hemani, Ayush Chopra +1
Few-shot segmentation (FSS) methods perform image segmentation for a particular object class in a target (query) image, using a small set of (support) image-mask pairs. Recent deep…
Apps Gone Rogue: Maintaining Personal Privacy in an Epidemic
Ramesh Raskar, Isabel Schunemann, Rachel Barbar +29
Containment, the key strategy in quickly halting an epidemic, requires rapid identification and quarantine of the infected individuals, determination of whom they have had close co…