Publications (58)
High-Throughput SAT Sampling
Arash Ardakani, Minwoo Kang, Kevin He +2
In this work, we present a novel technique for GPU-accelerated Boolean satisfiability (SAT) sampling. Unlike conventional sampling algorithms that directly operate on conjunctive n…
An Experiment on Network Density and Sequential Learning
Krishna Dasaratha, Kevin He
We conduct a sequential social-learning experiment where subjects each guess a hidden state based on private signals and the guesses of a subset of their predecessors. A network de…
Matching methods for obtaining survival functions to estimate the effect of a time-dependent treatment
Yun Li, Douglas E. Schaubel, Kevin He
In observational studies of survival time featuring a binary time-dependent treatment, the hazard ratio (an instantaneous measure) is often used to represent the treatment effect.…
Payoff Information and Learning in Signaling Games
Drew Fudenberg, Kevin He
We add the assumption that players know their opponents' payoff functions and rationality to a model of non-equilibrium learning in signaling games. Agents are born into player rol…
Seamless high-Q microwave cavities for multimode circuit QED
Srivatsan Chakram, Andrew E. Oriani, Ravi K. Naik +5
Multimode cavity quantum electrodynamics ---where a two-level system interacts simultaneously with many cavity modes---provides a versatile framework for quantum information proces…
Mislearning from Censored Data: The Gambler's Fallacy and Other Correlational Mistakes in Optimal-Stopping Problems
Kevin He
I study endogenous learning dynamics for people who misperceive intertemporal correlations in random sequences. Biased agents face an optimal-stopping problem. They are uncertain a…
Dynamic Information Design with Diminishing Sensitivity Over News
Jetlir Duraj, Kevin He
A Bayesian agent experiences gain-loss utility each period over changes in belief about future consumption ("news utility"), with diminishing sensitivity over the magnitude of news…
Generative AI in K-12 Classrooms: A Midyear Implementation Report
Lief Esbenshade, Alex Liu, Michael Xiao +6
This mid-year report summarizes teacher use of Colleague AI across 12 Washington State school districts from September 1 to December 31, 2025. Produced jointly by Colleague AI and…
Private Private Information
Kevin He, Fedor Sandomirskiy, Omer Tamuz
Private signals model noisy information about an unknown state. Although these signals are called "private," they may still carry information about each other. Our paper introduces…
AI as a Teaching Partner: Early Lessons from Classroom Codesign with Secondary Teachers
Alex Liu, Lief Esbenshade, Shawon Sarkar +6
This report presents a comprehensive account of the Colleague AI Classroom pilot, a collaborative design (co-design) study that brought generative AI technology directly into real…
Efficient quantum tomography of a polynomial subspace
Yat Wong, Ming Yuan, Kevin He +4
Quantum tomography is crucial for characterizing the quantum states of multipartite systems, but its practicality is often limited by the exponentially large dimension of the Hilbe…
Player-Compatible Learning and Player-Compatible Equilibrium
Drew Fudenberg, Kevin He
Player-Compatible Equilibrium (PCE) imposes cross-player restrictions on the magnitudes of the players' "trembles" onto different strategies. These restrictions capture the idea th…
Cox-nnet v2.0: improved neural-network based survival prediction extended to large-scale EMR dataset
Di Wang, Kevin He, Lana X Garmire
Cox-nnet is a neural-network based prognosis prediction method, originally applied to genomics data. Here we propose the version 2 of Cox-nnet, with significant improvement on effi…
Incorporating External Risk Information with the Cox Model under Population Heterogeneity: Applications to Trans-Ancestry Polygenic Hazard Scores
Di Wang, Wen Ye, Ji Zhu +5
Polygenic hazard score (PHS) models designed for European ancestry (EUR) individuals provide ample information regarding survival risk discrimination. Incorporating such informatio…
Human-LLM Collaborative Inductive Coding for Conceptualizing K-12 Educator AI Use
Alex Liu, Min Sun, Lief Esbenshade +4
Qualitative researchers increasingly encounter interaction corpora whose scale exceeds what manual coding alone can address, and large language models (LLMs) are frequently propose…
Creating and Evaluating K-12 GenAI Assessment Graders Through Context Engineering
Zewei Tian, Alex Liu, Lief Esbenshade +6
The integration of large language models (LLMs) into educational assessment represents a transformative shift in classroom grading practices. While automated scoring systems and ma…
Implementation Considerations for Automated AI Grading of Student Work
Zewei Tian, Alex Liu, Lief Esbenshade +4
This study explores the classroom implementation of an AI-powered grading platform in K-12 settings through a co-design pilot with 19 teachers. We combine platform usage logs, surv…
Training-Aware Risk Control for Intensity Modulated Radiation Therapies Quality Assurance with Conformal Prediction
Kevin He, David Adam, Sarah Han-Oh +1
Measurement quality assurance (QA) practices play a key role in the safe use of Intensity Modulated Radiation Therapies (IMRT) for cancer treatment. These practices have reduced me…
The Outer Halo of the Milky Way as Probed by RR Lyr Variables from the Palomar Transient Facility
Judith Cohen, Branimir Sesar, Sophianna Bahnolzer +5
RR Lyr stars are ideal massless tracers that can be used to study the total mass and dark matter content of the outer halo of the Milky Way. This is because they are easy to find i…
Bregman Divergence-Based Data Integration with Application to Polygenic Risk Score (PRS) Heterogeneity Adjustment
Qinmengge Li, Matthew T. Patrick, Haihan Zhang +9
Polygenic risk scores (PRS) have recently received much attention for genetics risk prediction. While successful for the Caucasian population, the PRS based on the minority populat…
Evolutionarily Stable (Mis)specifications: Theory and Applications
Kevin He, Jonathan Libgober
Toward explaining the persistence of biased inferences, we propose a framework to evaluate competing (mis)specifications in strategic settings. Agents with heterogeneous (mis)speci…
A digitally controlled silicon quantum processing unit
Members of the HRL Quantum Team, Collaborators, : +255
Commercially-relevant quantum computers will require large numbers of high-performing qubits that can be manufactured, integrated, and controlled at scale. Silicon exchange-only (E…
Agreement Is Not Quality: Blind Expert Verification of Human and LLM Qualitative Coding When Human Consensus Is Not Ground Truth
Alex Liu, Lief Esbenshade, Michael Xiao +4
Evaluations of LLM-assisted qualitative coding almost universally measure model performance as agreement with human coders, a practice that presumes human coding is the standard to…
Niobium coaxial cavities with internal quality factors exceeding 1.5 billion for circuit quantum electrodynamics
Andrew E. Oriani, Fang Zhao, Tanay Roy +6
Group-V materials such as niobium and tantalum have become popular choices for extending the performance of circuit quantum electrodynamics (cQED) platforms allowing for quantum pr…
Composite Scores for Transplant Center Evaluation: A New Individualized Empirical Null Method
Nicholas Hartman, Joseph M. Messana, Jian Kang +3
Risk-adjusted quality measures are used to evaluate healthcare providers while controlling for factors beyond their control. Existing healthcare provider profiling approaches typic…
Emerging Patterns of GenAI Use in K-12 Science and Mathematics Education
Lief Esbenshade, Shawon Sarkar, Drew Nucci +10
In this report, we share findings from a nationally representative survey of US public school math and science teachers, examining current generative AI (GenAI) use, perceptions, c…
SurvBoost: An R Package for High-Dimensional Variable Selection in the Stratified Proportional Hazards Model via Gradient Boosting
Emily Morris, Kevin He, Yanming Li +2
High-dimensional variable selection in the proportional hazards (PH) model has many successful applications in different areas. In practice, data may involve confounding variables…
Classification with Ultrahigh-Dimensional Features
Yanming Li, Hyokyoung Hong, Jian Kang +3
Although much progress has been made in classification with high-dimensional features \citep{Fan_Fan:2008, JGuo:2010, CaiSun:2014, PRXu:2014}, classification with ultrahigh-dimensi…
Attention and Social Learning
Krishna Dasaratha, Kevin He
In an incentivized laboratory experiment, we study how people account for and respond to others' incentives for paying attention. Participants learn a binary state from an attentio…
Direct Collocation for Quantum Optimal Control
Aaron Trowbridge, Aditya Bhardwaj, Kevin He +2
We present an adaptation of direct collocation -- a trajectory optimization method commonly used in robotics and aerospace applications -- to quantum optimal control (QOC); we refe…
Covariance-Insured Screening
Kevin He, Jian Kang, Hyokyoung Grace Hong +5
Modern bio-technologies have produced a vast amount of high-throughput data with the number of predictors far greater than the sample size. In order to identify more novel biomarke…
Minorization-Maximization-based Steepest Ascent for Large-scale Survival Analysis with Time-Varying Effects: Application to the National Kidney Transplant Dataset
Kevin He, Ji Zhu, Jian Kang +1
The time-varying effects model is a flexible and powerful tool for modeling the dynamic changes of covariate effects. However, in survival analysis, its computational burden increa…
Kullback-Leibler-Based Discrete Failure Time Models for Integration of Published Prediction Models with New Time-To-Event Dataset
Di Wang, Wen Ye, Randall Sung +4
Prediction of time-to-event data often suffers from rare event rates, small sample sizes, high dimensionality and low signal-to-noise ratios. Incorporating published prediction mod…
Efficient multimode Wigner tomography
Kevin He, Ming Yuan, Yat Wong +4
Advancements in quantum system lifetimes and control have enabled the creation of increasingly complex quantum states, such as those on multiple bosonic cavity modes. When characte…
Human Misperception of Generative-AI Alignment: A Laboratory Experiment
Kevin He, Ran Shorrer, Mengjia Xia
We conduct an incentivized laboratory experiment to study people's perception of generative artificial intelligence (GenAI) alignment in the context of economic decision-making. Us…
Misspecified learning and evolutionary stability
Kevin He, Jonathan Libgober
We extend the indirect evolutionary approach to the selection of (possibly misspecified) models. Agents with different models match in pairs to play a stage game, where models defi…
Accounting for total variation and robustness in profiling health care providers
Lu Xia, Kevin He, Yanming Li +1
Monitoring outcomes of health care providers, such as patient deaths, hospitalizations and hospital readmissions, helps in assessing the quality of health care. We consider a large…
Learning from Viral Information
Krishna Dasaratha, Kevin He
Motivated by social media, we study an equilibrium model of agents interacting with and learning from each other's signals. Rational agents arrive sequentially, observe a signal (c…
Screening -Hackers: Dissemination Noise as Bait
Federico Echenique, Kevin He
We show that adding noise before publishing data effectively screens -hacked findings: spurious explanations produced by fitting many statistical models (data mining). Noise cre…
Multimode photon blockade
Srivatsan Chakram, Kevin He, Akash V. Dixit +7
Interactions are essential for the creation of correlated quantum many-body states. While two-body interactions underlie most natural phenomena, three- and four-body interactions a…
KL-divergence Based Deep Learning for Discrete Time Model
Li Liu, Xiangeng Fang, Di Wang +2
Neural Network (Deep Learning) is a modern model in Artificial Intelligence and it has been exploited in Survival Analysis. Although several improvements have been shown by previou…
Observability, Dominance, and Induction in Learning Models
Daniel Clark, Drew Fudenberg, Kevin He
Learning models do not in general imply that weakly dominated strategies are irrelevant or justify the related concept of "forward induction," because rational agents may use domin…
Searching for Dark Matter with a Superconducting Qubit
Akash V. Dixit, Srivatsan Chakram, Kevin He +4
Detection mechanisms for low mass bosonic dark matter candidates, such the axion or hidden photon, leverage potential interactions with electromagnetic fields, whereby the dark mat…
Robust Privacy-Preserving Models for Cluster-Level Confounding: Recognizing Disparities in Access to Transplantation
Nicholas Hartman, Kevin He
In applications where the study data are collected within cluster units (e.g., patients within transplant centers), it is often of interest to estimate and perform inference on the…
Aggregative Efficiency of Bayesian Learning in Networks
Krishna Dasaratha, Kevin He
When individuals in a social network learn about an unknown state from private signals and neighbors' actions, the network structure often causes information loss. We consider rati…
Latent Gaussian Mixture Models for Nationwide Kidney Transplant Center Evaluation
Lanfeng Pan, Yehua Li, Kevin He +2
Five year post-transplant survival rate is an important indicator on quality of care delivered by kidney transplant centers in the United States. To provide a fair assessment of ea…
How K-12 Educators Use AI: LLM-Assisted Qualitative Analysis at Scale
Alex Liu, Lief Esbenshade, Shawon Sarkar +4
This study investigates how K-12 educators use generative AI tools in real-world instructional contexts and how large language models (LLMs) can support scalable qualitative analys…
Understanding the dynamic impact of COVID-19 through competing risk modeling with bivariate varying coefficients
Wenbo Wu, John D. Kalbfleisch, Jeremy M. G. Taylor +2
The coronavirus disease 2019 (COVID-19) pandemic has exerted a profound impact on patients with end-stage renal disease relying on kidney dialysis to sustain their lives. Motivated…
Stimulated emission of signal photons from dark matter waves
Ankur Agrawal, Akash V. Dixit, Tanay Roy +5
The manipulation of quantum states of light has resulted in significant advancements in both dark matter searches and gravitational wave detectors [1-4]. Current dark matter search…
Learning and Type Compatibility in Signaling Games
Drew Fudenberg, Kevin He
Which equilibria will arise in signaling games depends on how the receiver interprets deviations from the path of play. We develop a micro-foundation for these off-path beliefs, an…
Recurrent CircuitSAT Sampling for Sequential Circuits
Arash Ardakani, Kevin He, John Wawrzynek
In this work, we introduce a novel GPU-accelerated circuit satisfiability (CircuitSAT) sampling technique for sequential circuits. This work is motivated by the requirement in cons…
DEMOTIC: A Differentiable Sampler for Multi-Level Digital Circuits
Arash Ardakani, Minwoo Kang, Kevin He +4
Efficient sampling of satisfying formulas for circuit satisfiability (CircuitSAT), a well-known NP-complete problem, is essential in modern front-end applications for thorough test…
Survival Analysis via Ordinary Differential Equations
Weijing Tang, Kevin He, Gongjun Xu +1
This paper introduces an Ordinary Differential Equation (ODE) notion for survival analysis. The ODE notion not only provides a unified modeling framework, but more importantly, als…
Bayesian Posteriors For Arbitrarily Rare Events
Drew Fudenberg, Kevin He, Lorens Imhof
We study how much data a Bayesian observer needs to correctly infer the relative likelihoods of two events when both events are arbitrarily rare. Each period, either a blue die or…
Network Structure and Naive Sequential Learning
Krishna Dasaratha, Kevin He
We study a sequential-learning model featuring a network of naive agents with Gaussian information structures. Agents apply a heuristic rule to aggregate predecessors' actions. The…
GenAI for Systems: Recurring Challenges and Design Principles from Software to Silicon
Arya Tschand, Chenyu Wang, Zishen Wan +21
Generative AI is reshaping how computing systems are designed, optimized, and built, yet research remains fragmented across software, architecture, and chip design communities. Thi…
Steering the Herd: A Framework for LLM-based Control of Social Learning
Raghu Arghal, Kevin He, Shirin Saeedi Bidokhti +1
Algorithms increasingly serve as information mediators--from social media feeds and targeted advertising to the increasing ubiquity of LLMs. This engenders a joint process where ag…
Teacher-Authored Prompts for Configuring Student-AI Dialogue: K-12 Classroom Implementation
Alex Liu, Min Sun, Lief Esbenshade +3
GenAI has rapidly entered instructional and learning settings as a teaching assistant or AI tutor. However, less is known about how pedagogical intent connects to the learning gene…