Ramesh Johari

All Publications

• The adaptation of a single institution diabetes care platform into a nationally available turnkey solution. NPJ digital medicine Kim, G. Y., Rostosky, R., Bishop, F. K., Watson, K., Prahalad, P., Vaidya, A., Lee, S., Diana, A., Beacock, C., Chu, B., Yadav, G., Rochford, K., Carter, C., Ferstad, J. O., Pang, E., Kurtzig, J., Arbiter, B., Look, H., Johari, R., Maahs, D. M., Scheinker, D. 2024; 7 (1): 311

  Abstract

  Digital decision support and remote patient monitoring may improve outcomes and efficiency, but rarely scale beyond a single institution. Over the last 5 years, the platform Timely Interventions for Diabetes Excellence (TIDE) has been associated with reduced care provider screen time and improved, equitable type 1 diabetes care and outcomes for 268 patients in a heterogeneous population as part of the Teamwork, Targets, Technology, and Tight Control (4T) Study (NCT03968055, NCT04336969). Previous efforts to deploy TIDE at other institutions continue to face delays. In partnership with the diabetes technology non-profit, Tidepool, we developed Tidepool-TIDE, a clinic-agnostic, turnkey solution available to any clinic in the United States. We present how we overcame common technical and operational barriers specific to scaling digital health technology from one site to many. The concepts described are broadly applicable for institutions interested in facilitating broader adoption of digital technology for population-level management of chronic health conditions.

  View details for DOI 10.1038/s41746-024-01319-x

  View details for PubMedID 39506045

• Equitable implementation of a precision digital health program for glucose management in individuals with newly diagnosed type 1 diabetes. Nature medicine Prahalad, P., Scheinker, D., Desai, M., Ding, V. Y., Bishop, F. K., Lee, M. Y., Ferstad, J., Zaharieva, D. P., Addala, A., Johari, R., Hood, K., Maahs, D. M. 2024

  Abstract

  Few young people with type 1 diabetes (T1D) meet glucose targets. Continuous glucose monitoring improves glycemia, but access is not equitable. We prospectively assessed the impact of a systematic and equitable digital-health-team-based care program implementing tighter glucose targets (HbA1c < 7%), early technology use (continuous glucose monitoring starts <1 month after diagnosis) and remote patient monitoring on glycemia in young people with newly diagnosed T1D enrolled in the Teamwork, Targets, Technology, and Tight Control (4T Study 1). Primary outcome was HbA1c change from 4 to 12 months after diagnosis; the secondary outcome was achieving the HbA1c targets. The 4T Study 1 cohort (36.8% Hispanic and 35.3% publicly insured) had a mean HbA1c of 6.58%, 64% with HbA1c < 7% and mean time in the range (70-180 mg dl-1) of 68% at 1 year after diagnosis. Clinical implementation of the 4T Study 1 met the prespecified primary outcome and improved glycemia without unexpected serious adverse events. The strategies in the 4T Study 1 can be used to implement systematic and equitable care for individuals with T1D and translate to care for other chronic diseases. ClinicalTrials.gov registration: NCT04336969 .

  View details for DOI 10.1038/s41591-024-02975-y

  View details for PubMedID 38702523

  View details for PubMedCentralID 9764665

• Smart Start - Designing Powerful Clinical Trials Using Pilot Study Data. NEJM evidence Ferstad, J. O., Prahalad, P., Maahs, D. M., Zaharieva, D. P., Fox, E., Desai, M., Johari, R., Scheinker, D. 2024; 3 (2): EVIDoa2300164

  Abstract

  Using Pilot Study Data to Design Clinical TrialsDigital health interventions are often studied in a pilot trial before full evaluation in a randomized controlled trial. The authors introduce Smart Start, a framework for using pilot study data to optimize the intervention and design the subsequent randomized controlled trial to maximize the chance of success.

  View details for DOI 10.1056/EVIDoa2300164

  View details for PubMedID 38320487

• Quality Selection in Two-Sided Markets: A Constrained Price Discrimination Approach OPERATIONS RESEARCH Light, B., Johari, R., Weintraub, G. 2024

  View details for DOI 10.1287/opre.2020.0754

  View details for Web of Science ID 001141887100001

• The evolving role of data & amp; safety monitoring boards for real-world clinical trials JOURNAL OF CLINICAL AND TRANSLATIONAL SCIENCE Bunning, B. J., Hedlin, H., Chen, J. H., Ciolino, J. D., Ferstad, J., Fox, E., Garcia, A., Go, A., Johari, R., Lee, J., Maahs, D. M., Mahaffey, K. W., Opsahl-Ong, K., Perez, M., Rochford, K., Scheinker, D., Spratt, H., Turakhia, M. P., Desai, M. 2023; 7 (1)

  View details for DOI 10.1017/cts.2023.582

  View details for Web of Science ID 001054146900001

• The evolving role of data & safety monitoring boards for real-world clinical trials. Journal of clinical and translational science Bunning, B. J., Hedlin, H., Chen, J. H., Ciolino, J. D., Ferstad, J. O., Fox, E., Garcia, A., Go, A., Johari, R., Lee, J., Maahs, D. M., Mahaffey, K. W., Opsahl-Ong, K., Perez, M., Rochford, K., Scheinker, D., Spratt, H., Turakhia, M. P., Desai, M. 2023; 7 (1): e179

  Abstract

  Clinical trials provide the "gold standard" evidence for advancing the practice of medicine, even as they evolve to integrate real-world data sources. Modern clinical trials are increasingly incorporating real-world data sources - data not intended for research and often collected in free-living contexts. We refer to trials that incorporate real-world data sources as real-world trials. Such trials may have the potential to enhance the generalizability of findings, facilitate pragmatic study designs, and evaluate real-world effectiveness. However, key differences in the design, conduct, and implementation of real-world vs traditional trials have ramifications in data management that can threaten their desired rigor.Three examples of real-world trials that leverage different types of data sources - wearables, medical devices, and electronic health records are described. Key insights applicable to all three trials in their relationship to Data and Safety Monitoring Boards (DSMBs) are derived.Insight and recommendations are given on four topic areas: A. Charge of the DSMB; B. Composition of the DSMB; C. Pre-launch Activities; and D. Post-launch Activities. We recommend stronger and additional focus on data integrity.Clinical trials can benefit from incorporating real-world data sources, potentially increasing the generalizability of findings and overall trial scale and efficiency. The data, however, present a level of informatic complexity that relies heavily on a robust data science infrastructure. The nature of monitoring the data and safety must evolve to adapt to new trial scenarios to protect the rigor of clinical trials.

  View details for DOI 10.1017/cts.2023.582

  View details for PubMedID 37745930

  View details for PubMedCentralID PMC10514684

• A quantitative model to ensure capacity sufficient for timely access to care in a remote patient monitoring program. Endocrinology, diabetes & metabolism Chang, A., Gao, M. Z., Ferstad, J. O., Dupenloup, P., Zaharieva, D. P., Maahs, D. M., Prahalad, P., Johari, R., Scheinker, D. 2023: e435

  Abstract

  Algorithm-enabled remote patient monitoring (RPM) programs pose novel operational challenges. For clinics developing and deploying such programs, no standardized model is available to ensure capacity sufficient for timely access to care. We developed a flexible model and interactive dashboard of capacity planning for whole-population RPM-based care for T1D.Data were gathered from a weekly RPM program for 277 paediatric patients with T1D at a paediatric academic medical centre. Through the analysis of 2 years of observational operational data and iterative interviews with the care team, we identified the primary operational, population, and workforce metrics that drive demand for care providers. Based on these metrics, an interactive model was designed to facilitate capacity planning and deployed as a dashboard.The primary population-level drivers of demand are the number of patients in the program, the rate at which patients enrol and graduate from the program, and the average frequency at which patients require a review of their data. The primary modifiable clinic-level drivers of capacity are the number of care providers, the time required to review patient data and contact a patient, and the number of hours each provider allocates to the program each week. At the institution studied, the model identified a variety of practical operational approaches to better match the demand for patient care.We designed a generalizable, systematic model for capacity planning for a paediatric endocrinology clinic providing RPM for T1D. We deployed this model as an interactive dashboard and used it to facilitate expansion of a novel care program (4 T Study) for newly diagnosed patients with T1D. This model may facilitate the systematic design of RPM-based care programs.

  View details for DOI 10.1002/edm2.435

  View details for PubMedID 37345227

• Disparities in Hemoglobin A1c Levels in the First Year After Diagnosis Among Youths With Type 1 Diabetes Offered Continuous Glucose Monitoring. JAMA network open Addala, A., Ding, V., Zaharieva, D. P., Bishop, F. K., Adams, A. S., King, A. C., Johari, R., Scheinker, D., Hood, K. K., Desai, M., Maahs, D. M., Prahalad, P. 2023; 6 (4): e238881

  Abstract

  Continuous glucose monitoring (CGM) is associated with improvements in hemoglobin A1c (HbA1c) in youths with type 1 diabetes (T1D); however, youths from minoritized racial and ethnic groups and those with public insurance face greater barriers to CGM access. Early initiation of and access to CGM may reduce disparities in CGM uptake and improve diabetes outcomes.To determine whether HbA1c decreases differed by ethnicity and insurance status among a cohort of youths newly diagnosed with T1D and provided CGM.This cohort study used data from the Teamwork, Targets, Technology, and Tight Control (4T) study, a clinical research program that aims to initiate CGM within 1 month of T1D diagnosis. All youths with new-onset T1D diagnosed between July 25, 2018, and June 15, 2020, at Stanford Children's Hospital, a single-site, freestanding children's hospital in California, were approached to enroll in the Pilot-4T study and were followed for 12 months. Data analysis was performed and completed on June 3, 2022.All eligible participants were offered CGM within 1 month of diabetes diagnosis.To assess HbA1c change over the study period, analyses were stratified by ethnicity (Hispanic vs non-Hispanic) or insurance status (public vs private) to compare the Pilot-4T cohort with a historical cohort of 272 youths diagnosed with T1D between June 1, 2014, and December 28, 2016.The Pilot-4T cohort comprised 135 youths, with a median age of 9.7 years (IQR, 6.8-12.7 years) at diagnosis. There were 71 boys (52.6%) and 64 girls (47.4%). Based on self-report, participants' race was categorized as Asian or Pacific Islander (19 [14.1%]), White (62 [45.9%]), or other race (39 [28.9%]); race was missing or not reported for 15 participants (11.1%). Participants also self-reported their ethnicity as Hispanic (29 [21.5%]) or non-Hispanic (92 [68.1%]). A total of 104 participants (77.0%) had private insurance and 31 (23.0%) had public insurance. Compared with the historical cohort, similar reductions in HbA1c at 6, 9, and 12 months postdiagnosis were observed for Hispanic individuals (estimated difference, -0.26% [95% CI, -1.05% to 0.43%], -0.60% [-1.46% to 0.21%], and -0.15% [-1.48% to 0.80%]) and non-Hispanic individuals (estimated difference, -0.27% [95% CI, -0.62% to 0.10%], -0.50% [-0.81% to -0.11%], and -0.47% [-0.91% to 0.06%]) in the Pilot-4T cohort. Similar reductions in HbA1c at 6, 9, and 12 months postdiagnosis were also observed for publicly insured individuals (estimated difference, -0.52% [95% CI, -1.22% to 0.15%], -0.38% [-1.26% to 0.33%], and -0.57% [-2.08% to 0.74%]) and privately insured individuals (estimated difference, -0.34% [95% CI, -0.67% to 0.03%], -0.57% [-0.85% to -0.26%], and -0.43% [-0.85% to 0.01%]) in the Pilot-4T cohort. Hispanic youths in the Pilot-4T cohort had higher HbA1c at 6, 9, and 12 months postdiagnosis than non-Hispanic youths (estimated difference, 0.28% [95% CI, -0.46% to 0.86%], 0.63% [0.02% to 1.20%], and 1.39% [0.37% to 1.96%]), as did publicly insured youths compared with privately insured youths (estimated difference, 0.39% [95% CI, -0.23% to 0.99%], 0.95% [0.28% to 1.45%], and 1.16% [-0.09% to 2.13%]).The findings of this cohort study suggest that CGM initiation soon after diagnosis is associated with similar improvements in HbA1c for Hispanic and non-Hispanic youths as well as for publicly and privately insured youths. These results further suggest that equitable access to CGM soon after T1D diagnosis may be a first step to improve HbA1c for all youths but is unlikely to eliminate disparities entirely.ClinicalTrials.gov Identifier: NCT04336969.

  View details for DOI 10.1001/jamanetworkopen.2023.8881

  View details for PubMedID 37074715

  View details for PubMedCentralID PMC10116368

• Sammy: smoothing video traffic to be a friendly internet neighbor Spang, B., Kunamalla, S., Teixeira, R., Huang, T., Armitage, G., Johari, R., McKeown, N., ACM ASSOC COMPUTING MACHINERY. 2023: 754-768

  View details for DOI 10.1145/3603269.3604839

  View details for Web of Science ID 001116971100051

• A model to design financially sustainable algorithm-enabled remote patient monitoring for pediatric type 1 diabetes care. Frontiers in endocrinology Dupenloup, P., Pei, R. L., Chang, A., Gao, M. Z., Prahalad, P., Johari, R., Schulman, K., Addala, A., Zaharieva, D. P., Maahs, D. M., Scheinker, D. 2022; 13: 1021982

  Abstract

  Population-level algorithm-enabled remote patient monitoring (RPM) based on continuous glucose monitor (CGM) data review has been shown to improve clinical outcomes in diabetes patients, especially children. However, existing reimbursement models are geared towards the direct provision of clinic care, not population health management. We developed a financial model to assist pediatric type 1 diabetes (T1D) clinics design financially sustainable RPM programs based on algorithm-enabled review of CGM data.Data were gathered from a weekly RPM program for 302 pediatric patients with T1D at Lucile Packard Children's Hospital. We created a customizable financial model to calculate the yearly marginal costs and revenues of providing diabetes education. We consider a baseline or status quo scenario and compare it to two different care delivery scenarios, in which routine appointments are supplemented with algorithm-enabled, flexible, message-based contacts delivered according to patient need. We use the model to estimate the minimum reimbursement rate needed for telemedicine contacts to maintain revenue-neutrality and not suffer an adverse impact to the bottom line.The financial model estimates that in both scenarios, an average reimbursement rate of roughly $10.00 USD per telehealth interaction would be sufficient to maintain revenue-neutrality. Algorithm-enabled RPM could potentially be billed for using existing RPM CPT codes and lead to margin expansion.We designed a model which evaluates the financial impact of adopting algorithm-enabled RPM in a pediatric endocrinology clinic serving T1D patients. This model establishes a clear threshold reimbursement value for maintaining revenue-neutrality, as well as an estimate of potential RPM reimbursement revenue which could be billed for. It may serve as a useful financial-planning tool for a pediatric T1D clinic seeking to leverage algorithm-enabled RPM to provide flexible, more timely interventions to its patients.

  View details for DOI 10.3389/fendo.2022.1021982

  View details for PubMedID 36440201

  View details for PubMedCentralID PMC9691757

• A New Technology-Enabled Care Model for Pediatric Type 1 Diabetes. NEJM catalyst innovations in care delivery Scheinker, D., Prahalad, P., Johari, R., Maahs, D. M., Majzun, R. 2022; 3 (5)

  Abstract

  In July 2018, pediatric type 1 diabetes (T1D) care at Stanford suffered many of the problems that plague U.S. health care. Patient outcomes lagged behind those of peer European nations, care was delivered primarily on a fixed cadence rather than as needed, continuous glucose monitors (CGMs) were largely unavailable for individuals with public insurance, and providers' primary access to CGM data was through long printouts. Stanford developed a new technology-enabled, telemedicine-based care model for patients with newly diagnosed T1D. They developed and deployed Timely Interventions for Diabetes Excellence (TIDE) to facilitate as-needed patient contact with the partially automated analysis of CGM data and used philanthropic funding to facilitate full access to CGM technology for publicly insured patients, for whom CGM is not readily available in California. A study of the use of CGM for patients with new-onset T1D (pilot Teamwork, Targets, and Technology for Tight Control [4T] study), which incorporated the use of TIDE, was associated with a 0.5%-point reduction in hemoglobin A1c compared with historical controls and an 86% reduction in screen time for providers reviewing patient data. Based on this initial success, Stanford expanded the use of TIDE to a total of 300 patients, including many outside the pilot 4T study, and made TIDE freely available as open-source software. Next steps include expanding the use of TIDE to support the care of approximately 1,000 patients, improving TIDE and the associated workflows to scale their use to more patients, incorporating data from additional sensors, and partnering with other institutions to facilitate their deployment of this care model.

  View details for DOI 10.1056/CAT.21.0438

  View details for PubMedID 36544715

• Experimental Design in Two-Sided Platforms: An Analysis of Bias MANAGEMENT SCIENCE Johari, R., Li, H., Liskovich, I., Weintraub, G. Y. 2022

  View details for DOI 10.1287/mnsc.2021.4247

  View details for Web of Science ID 000747541300001

• Interference, Bias, and Variance in Two-Sided Marketplace Experimentation: Guidance for Platforms Li, H., Zhao, G., Johari, R., Weintraub, G. Y., ACM ASSOC COMPUTING MACHINERY. 2022: 182-192

  View details for DOI 10.1145/3485447.3512063

  View details for Web of Science ID 000852713000021

• Teamwork, Targets, Technology, and Tight Control in Newly Diagnosed Type 1 Diabetes: Pilot 4T Study. The Journal of clinical endocrinology and metabolism Prahalad, P., Ding, V. Y., Zaharieva, D. P., Addala, A., Johari, R., Scheinker, D., Desai, M., Hood, K., Maahs, D. M. 2021

  Abstract

  CONTEXT: Youth with type 1 diabetes (T1D) do not meet hemoglobin A1c (HbA1c) targets.OBJECTIVE: To assess HbA1c outcomes in children with new onset T1D enrolled in the Teamwork, Targets, Technology and Tight Control (4T) Study.METHOD: HbA1c levels were compared between the 4T and Historical cohorts. HbA1c differences between cohorts were estimated using locally estimated scatter plot smoothing (LOESS). The change from nadir HbA1c (month 4) to 12 months post-diagnosis was estimated by cohort using a piecewise mixed effects regression model accounting for age at diagnosis, sex, ethnicity, and insurance type.SETTING AND PARTICIPANTS: We recruited 135 youth with newly diagnosed T1D at Stanford Children's Health.INTERVENTION: Starting July 2018, all youth within the first month of T1D diagnosis were offered continuous glucose monitoring (CGM) initiation and remote CGM data review was added in March 2019.MAIN OUTCOME MEASURE: HbA1c.RESULTS: HbA1c at 6, 9, and 12 months post-diagnosis was lower in the 4T cohort than in the Historic cohort (-0.54%, -0.52%, and -0.58%, respectively). Within the 4T cohort, HbA1c at 6, 9, and 12 months post-diagnosis was lower in those patients with Remote Monitoring than those without (-0.14%, -0.18%, -0.14%, respectively). Multivariable regression analysis showed that the 4T cohort experienced a significantly lower increase in HbA1c between months 4 and 12 (p < 0.001).CONCLUSIONS: A technology-enabled team-based approach to intensified new onset education involving target setting, CGM initiation, and remote data review significantly decreased HbA1c in youth with T1D 12 months post-diagnosis.

  View details for DOI 10.1210/clinem/dgab859

  View details for PubMedID 34850024

• Always Valid Inference: Continuous Monitoring of A/B Tests OPERATIONS RESEARCH Johari, R., Koomen, P., Pekelis, L., Walsh, D. 2021

  View details for DOI 10.1287/opre.2021.2135

  View details for Web of Science ID 000708967000001

• Population-level management of Type 1 diabetes via continuous glucose monitoring and algorithm-enabled patient prioritization: Precision health meets population health. Pediatric diabetes Ferstad, J. O., Vallon, J. J., Jun, D., Gu, A., Vitko, A., Morales, D. P., Leverenz, J., Lee, M. Y., Leverenz, B., Vasilakis, C., Osmanlliu, E., Prahalad, P., Maahs, D. M., Johari, R., Scheinker, D. 2021

  Abstract

  OBJECTIVE: To develop and scale algorithm-enabled patient prioritization to improve population-level management of type 1 diabetes (T1D) in a pediatric clinic with fixed resources, using telemedicine and remote monitoring of patients via continuous glucose monitor (CGM) data review.RESEARCH DESIGN AND METHODS: We adapted consensus glucose targets for T1D patients using CGM to identify interpretable clinical criteria to prioritize patients for weekly provider review. The criteria were constructed to manage the number of patients reviewed weekly and identify patients who most needed provider contact. We developed an interactive dashboard to display CGM data relevant for the patients prioritized for review.RESULTS: The introduction of the new criteria and interactive dashboard was associated with a 60% reduction in the mean time spent by diabetes team members who remotely and asynchronously reviewed patient data and contacted patients, from 3.2±0.20 to 1.3±0.24minutes per patient per week. Given fixed resources for review, this corresponded to an estimated 147% increase in weekly clinic capacity. Patients who qualified for and received remote review (n=58) have associated 8.8 percentage points (pp) (95% CI=0.6-16.9pp) greater time-in-range (70-180mg/dL) glucoses compared to 25 control patients who did not qualify at twelve months after T1D onset.CONCLUSIONS: An algorithm-enabled prioritization of T1D patients with CGM for asynchronous remote review reduced provider time spent per patient and was associated with improved time-in-range. This article is protected by copyright. All rights reserved.

  View details for DOI 10.1111/pedi.13256

  View details for PubMedID 34374183

• Managing Congestion in Matching Markets M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT Arnosti, N., Johari, R., Kanoria, Y. 2021; 23 (3): 620-636

  View details for DOI 10.1287/msom.2020.0927

  View details for Web of Science ID 000653675200007

• Designing Informative Rating Systems: Evidence from an Online Labor Market M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT Garg, N., Johari, R. 2021; 23 (3): 589-605

  View details for DOI 10.1287/msom.2020.0921

  View details for Web of Science ID 000653675200005

• Matching While Learning OPERATIONS RESEARCH Johari, R., Kamble, V., Kanoria, Y. 2021; 69 (2): 655–81

  View details for DOI 10.1287/opre.2020.2013

  View details for Web of Science ID 000631703600016

• Studying Undergraduate Course Consideration at Scale AERA OPEN Chaturapruek, S., Dalberg, T., Thompson, M. E., Giebel, S., Harrison, M. H., Johari, R., Stevens, M. L., Kizilcec, R. F. 2021; 7

  View details for DOI 10.1177/2332858421991148

  View details for Web of Science ID 000620611500001

• Learning Unknown Service Rates in Queues: A Multiarmed Bandit Approach OPERATIONS RESEARCH Krishnasamy, S., Sen, R., Johari, R., Shakkottai, S. 2021; 69 (1): 315–30

  View details for DOI 10.1287/opre.2020.1995

  View details for Web of Science ID 000615320600020

• Adaptive Experimental Design with Temporal Interference: A Maximum Likelihood Approach Glynn, P., Johari, R., Rasouli, M., Larochelle, H., Ranzato, M., Hadsell, R., Balcan, M. F., Lin, H. NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2020

  View details for Web of Science ID 000627697000035

• Multi-Service Battery Operation with Cloud Electricity Storage Rasouli, M., Sun, T., Pache, C., Panciatici, P., Maeght, J., Johari, R., Rajagopal, R., IEEE IEEE. 2020

  View details for Web of Science ID 000679246600133

• Competition and Efficiency of Coalitions in Cournot Games With Uncertainty IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS Zhang, B., Johari, R., Rajagopal, R. 2019; 6 (2): 884–96

  View details for DOI 10.1109/TCNS.2018.2880302

  View details for Web of Science ID 000469874200037

• Semi-Parametric Dynamic Contextual Pricing Shah, V., Blanchet, J., Johari, R., Wallach, H., Larochelle, H., Beygelzimer, A., d'Alche-Buc, F., Fox, E., Garnett, R. NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2019

  View details for Web of Science ID 000534424302037

• Optimal Testing in the Experiment-rich Regime Schmit, S., Shah, V., Johari, R., Chaudhuri, K., Sugiyama, M. MICROTOME PUBLISHING. 2019: 626–33

  View details for Web of Science ID 000509687900065

• Designing Optimal Binary Rating Systems Garg, N., Johari, R., Chaudhuri, K., Sugiyama, M. MICROTOME PUBLISHING. 2019

  View details for Web of Science ID 000509687901101

• Bandit Learning with Positive Externalities Shah, V., Blanchet, J., Johari, R., Bengio, S., Wallach, H., Larochelle, H., Grauman, K., CesaBianchi, N., Garnett, R. NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2018

  View details for Web of Science ID 000461823304089

• On Learning the c mu Rule in Single and Parallel Server Networks Krishnasamy, S., Arapostathis, A., Johari, R., Shakkottai, S., IEEE IEEE. 2018: 153–54

  View details for Web of Science ID 000461021200022

• Pricing and referrals in diffusion on networks GAMES AND ECONOMIC BEHAVIOR Leduc, M. V., Jackson, M. O., Johari, R. 2017; 104: 568–94

  View details for DOI 10.1016/j.geb.2017.05.011

  View details for Web of Science ID 000408296200034

• The Importance of Exploration in Online Marketplaces IEEE INTERNET COMPUTING Banerjee, S., Johari, R., Zhou, Z. 2016; 20 (1): 20-26

  View details for Web of Science ID 000367944200004

• Competition and Coalition Formation of Renewable Power Producers IEEE TRANSACTIONS ON POWER SYSTEMS Zhang, B., Johari, R., Rajagopal, R. 2015; 30 (3): 1624-1632

  View details for DOI 10.1109/TPWRS.2014.2385869

  View details for Web of Science ID 000353641000054

• Equilibria of dynamic games with many players: Existence, approximation, and market structure JOURNAL OF ECONOMIC THEORY Adlakha, S., Johari, R., Weintraub, G. Y. 2015; 156: 269-316

  View details for DOI 10.1016/j.jet.2013.07.002

  View details for Web of Science ID 000349728700010

• Can I Take a Peek? Continuous Monitoring of Online A/B Tests Johari, R., ACM ASSOC COMPUTING MACHINERY. 2015: 915

  View details for DOI 10.1145/2740908.2743061

  View details for Web of Science ID 000382666600213

• Mean Field Equilibria of Dynamic Auctions with Learning MANAGEMENT SCIENCE Iyer, K., Johari, R., Sundararajan, M. 2014; 60 (12): 2949-2970

  View details for DOI 10.1287/mnsc.2014.2018

  View details for Web of Science ID 000346204900005

• Information Aggregation and Allocative Efficiency in Smooth Markets MANAGEMENT SCIENCE Iyer, K., Johari, R., Moallemi, C. C. 2014; 60 (10): 2509-2524

  View details for DOI 10.1287/mnsc.2014.1929

  View details for Web of Science ID 000343421800009

• A Buffer-Based Approach to Rate Adaptation: Evidence from a Large Video Streaming Service SIGCOMM Conference Huang, T., Johari, R., McKeown, N., Trunnell, M., Watson, M. ASSOC COMPUTING MACHINERY. 2014: 187–98

  View details for DOI 10.1145/2619239.2626296

  View details for Web of Science ID 000350564600039

• Mean Field Equilibrium in Dynamic Games with Strategic Complementarities OPERATIONS RESEARCH Adlakha, S., Johari, R. 2013; 61 (4): 971-989

  View details for DOI 10.1287/opre.2013.1192

  View details for Web of Science ID 000323931800013

• Dynamics in tree formation games GAMES AND ECONOMIC BEHAVIOR Arcaute, E., Dyagilev, K., Johari, R., Mannor, S. 2013; 79: 1-29

  View details for DOI 10.1016/j.geb.2013.01.002

  View details for Web of Science ID 000317711400001

• Mean Field Equilibria of Multi Armed Bandit Games 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton) Gummadi, R., Johari, R., Yu, J. Y. IEEE. 2013: 1110–1110

  View details for Web of Science ID 000320654000151

• Economic Modeling in Networking: A Primer. Foundations and Trends in Networking Berry, R., Johari , R. NOW Publishers.. 2013: 1
• Heavy Traffic Approximation of Equilibria in Resource Sharing Games IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS Wu, Y., Loc Bui, L., Johari, R. 2012; 30 (11): 2200-2209

  View details for DOI 10.1109/JSAC.2012.121212

  View details for Web of Science ID 000311673200012

• Traffic Engineering With Semiautonomous Users: A Game-Theoretic Perspective IEEE-ACM TRANSACTIONS ON NETWORKING DiPalantino, D., Johari, R. 2012; 20 (6): 1938-1949

  View details for DOI 10.1109/TNET.2012.2208475

  View details for Web of Science ID 000313661000020

• Resource management with semiautonomous users. To appear in IEEE/ACM Transactions on Networking. DiPalantino, D., Johari, R. 2012
• Mean field equilibria of multiarmed bandit games. Gummadi, R., Johari, R., Yu , J.-Y. 2012
• Information and the value of execution guarantees. Iyer, K., Johari, R., Moallemi , C., C. 2012
• Mean Field Equilibria of Dynamic Auctions with Learning SI GECOM EXCHANGES Iyer, K., Johari, R., Sundararajan, M. 2011; 10 (3): 10–14

  View details for Web of Science ID 000218516100003

• Bilateral and Multilateral Exchanges for Peer-Assisted Content Distribution IEEE-ACM TRANSACTIONS ON NETWORKING Aperjis, C., Johari, R., Freedman, M. J. 2011; 19 (5): 1290-1303

  View details for DOI 10.1109/TNET.2011.2114898

  View details for Web of Science ID 000296014000004

• Parameterized Supply Function Bidding: Equilibrium and Efficiency OPERATIONS RESEARCH Johari, R., Tsitsiklis, J. N. 2011; 59 (5): 1079-1089

  View details for DOI 10.1287/opre.1110.0980

  View details for Web of Science ID 000297164900002

• Competition and contracting in service industries OPERATIONS RESEARCH LETTERS DiPalantino, D., Johari, R., Weintraub, G. Y. 2011; 39 (5): 390-396

  View details for DOI 10.1016/j.orl.2011.06.011

  View details for Web of Science ID 000295712400019

• How Many Tiers? Pricing in the Internet Transit Market COMPUTER COMMUNICATION REVIEW Valancius, V., Lumezanu, C., Feamster, N., Johari, R., Vazirani, V. V. 2011; 41 (4): 194-205

  View details for DOI 10.1145/2043164.2018459

  View details for Web of Science ID 000302124800017

• Uncoupled Potentials for Proportional Allocation Markets 50th IEEE Conference of Decision and Control (CDC)/European Control Conference (ECC) Nadav, U., Johari, R., Roughgarden, T. IEEE. 2011: 4479–4484

  View details for Web of Science ID 000303506205016

• Economic Modeling in Networking: A Primer FOUNDATIONS AND TRENDS IN NETWORKING Berry, R. A., Johari, R. 2011; 6 (3): 165–286

  View details for DOI 10.1561/1300000011

  View details for Web of Science ID 000420146100001

• Heavy traffic approximation of equilibria in resource sharing games. Wu, Y., Bui, L., Johari, R. 2011
• Committing bandits. Bui, L., Johari, R., Mannor, S.  2011
• How many tiers? Pricing in the Internet transit market. Valancius, V., Lumezanu, C., Feamster, N., Johari, R., Vazirani, V. 2011
• Mean field equilibria of dynamic auctions with learning. Iyer, K., Johari, R., Sundararajan, M. 2011
• Investment and Market Structure in Industries with Congestion OPERATIONS RESEARCH Johari, R., Weintraub, G. Y., Van Roy, B. 2010; 58 (5): 1303-1317

  View details for DOI 10.1287/opre.1100.0827

  View details for Web of Science ID 000283244800003

• Designing Aggregation Mechanisms for Reputation Systems in Online Marketplaces SI GECOM EXCHANGES Aperjis, C., Johari, R. 2010; 9 (1)

  View details for Web of Science ID 000218499400003

• Optimal Windows for Aggregating Ratings in Electronic Marketplaces MANAGEMENT SCIENCE Aperjis, C., Johari, R. 2010; 56 (5): 864-880

  View details for DOI 10.1287/mnsc.1090.1145

  View details for Web of Science ID 000277653900008

• Demand-Aware Content Distribution on the Internet IEEE-ACM TRANSACTIONS ON NETWORKING Shakkottai, S., Johari, R. 2010; 18 (2): 476-489

  View details for DOI 10.1109/TNET.2009.2035047

  View details for Web of Science ID 000276685300011

• Information-Theoretic Operating Regimes of Large Wireless Networks IEEE TRANSACTIONS ON INFORMATION THEORY Ozgur, A., Johari, R., Tse, D. N., Leveque, O. 2010; 56 (1): 427-437

  View details for DOI 10.1109/TIT.2009.2034819

  View details for Web of Science ID 000273134100030

• Mean field equilibrium in dynamic games with complementarities. Adlakha, S., Johari, R. 2010
• Information aggregation in smooth markets. Iyer, K., Johari, R., Moallemi, C., C. 2010
• Congestible services and network effects. Johari, R., Kumar, S. 2010
• Information theoretic operating regimes of large wireless networks. IEEE Transactions on Information Theory Ozgur, A., Johari, R., Tse, D., Leveque, O. 2010; 1 (56): 427-437
• Mean field analysis for large population stochastic games. Adlakha, S., Johari, R., Weintraub, G., Y., Goldsmith, A. 2010
• On Oblivious Equilibrium in Large Population Stochastic Games 49th IEEE Conference on Decision and Control (CDC) Adlakha, S., Johari, R., Weintraub, G. Y., Goldsmith, A. IEEE. 2010: 3117–3124

  View details for Web of Science ID 000295049103092

• Mean Field Equilibrium in Dynamic Games with Complementarities 49th IEEE Conference on Decision and Control (CDC) Adlakha, S., Johari, R. IEEE. 2010: 6633–6638

  View details for Web of Science ID 000295049107080

• Network Formation: Bilateral Contracting and Myopic Dynamics IEEE TRANSACTIONS ON AUTOMATIC CONTROL Arcaute, E., Johari, R., Mannor, S. 2009; 54 (8): 1765-1778

  View details for DOI 10.1109/TAC.2009.2024564

  View details for Web of Science ID 000268756200003

• Efficiency of Scalar-Parameterized Mechanisms 43rd Annual Allerton Conference on Communication, Control and Computing Johari, R., Tsitsiklis, J. N. INFORMS. 2009: 823–39

  View details for DOI 10.1287/opre.1080.0638

  View details for Web of Science ID 000270032800003

• Traffic Engineering, Content Distribution, and Continuous Potential Games International Conference on Game Theory for Networks DiPalantino, D., Johari, R. IEEE. 2009: 98–99

  View details for Web of Science ID 000274558900014

• Network formation: bilateral contracting and myopic dynamics. IEEE Transactions on Automatic Control Arcaute, E., Johari, R., Mannor, S. 2009; 8 (54): 1765-1778
• Comparing Multilateral and Bilateral Exchange Models for Content Distribution IEEE Information Theory Workshop on Networking and Information Theory Aperjis, C., Freedman, M. J., Johari, R. IEEE. 2009: 145–146

  View details for Web of Science ID 000273966100031

• Oblivious Equilibrium: An Approximation to Large Population Dynamic Games with Concave Utility International Conference on Game Theory for Networks Adlakha, S., Johari, R., Weintraub, G., Goldsmith, A. IEEE. 2009: 68–69

  View details for Web of Science ID 000274558900009

• A Mean Field Approach to Competition in Large Scale Wireless Systems MobiHoc S3 Workshop Adlakha, S., Johari, R., Weintraub, G., Goldsmith, A. ASSOC COMPUTING MACHINERY. 2009: 13–15

  View details for Web of Science ID 000282529000004

• Supermodular Network Games 47th Annual Allerton Conference on Communication, Control, and Computing Manshadi, V. H., Johari, R. IEEE. 2009: 1369–1376

  View details for Web of Science ID 000279627100187

• Traffic Engineering vs. Content Distribution: A Game Theoretic Perspective IEEE INFOCOM Conference 2009 DiPalantino, D., Johari, R. IEEE. 2009: 540–548

  View details for Web of Science ID 000275366200061

• Lump-Sum Markets for Air Traffic Flow Control with Competitive Airlines PROCEEDINGS OF THE IEEE Waslander, S. L., Roy, K., Johari, R., Tomlin, C. J. 2008; 96 (12): 2113-2130

  View details for DOI 10.1109/JPROC.2008.2006197

  View details for Web of Science ID 000262934800015

• Information Theoretic Operating Regimes of Large Wireless Networks IEEE International Symposium on Information Theory Oezguer, A., Johari, R., Tse, D., Leveque, O. IEEE. 2008: 186–190

  View details for Web of Science ID 000260364400038

• Local myopic dynamics in network formation games. Arcaute, E., Johari, R., Mannor, S. 2008
• Peer-assisted content distribution with prices. Aperjis, C., Freedman, M., J., Johari, R. 2008
• Oblivious equilibrium for general stochastic games with unbounded costs. Adlakha, S., Johari, R., Weintraub, G., Y., Goldsmith , A. 2008
• Oblivious equilibrium for general stochastic games with concave costs. Adlakha, S., Johari, R., Weintraub, G., Y., Goldsmith , A. 2008
• A comparison of bilateral and multilateral exchanges for peer-assisted content distribution. Aperjis, C., Freedman, M., J., Johari, R. 2008
• Prices are right: aligning incentives for peer-assisted content distribution. Freedman, M., J., Aperjis, C., Johari, R. 2008
• A comparison of bilateral and multilateral exchanges for peer-assisted content distribution. Aperjis, C., Freedman, M., J., Johari, R. 2008
• Local Dynamics for Network Formation Games 46th Annual Allerton Conference on Communication, Control and Computing Arcaute, E., Johari, R., Mannor, S. IEEE. 2008: 937–938

  View details for Web of Science ID 000268229600132

• Oblivious Equilibrium for Stochastic Games with Concave Utility 46th Annual Allerton Conference on Communication, Control and Computing Adlakha, S., Johari, R., Weintraub, G., Goldsmith, A. IEEE. 2008: 1304–1308

  View details for Web of Science ID 000268229600185

• Local Two-Stage Myopic Dynamics for Network Formation Games 4th International Workshop on Internet and Network Economics Arcaute, E., Johari, R., Mannor, S. SPRINGER-VERLAG BERLIN. 2008: 263–277

  View details for Web of Science ID 000262046200024

• Oblivious Equilibrium for Large-Scale Stochastic Games with Unbounded Costs 47th IEEE Conference on Decision and Control Adlakha, S., Johari, R., Weintraub, G., Goldsmith, A. IEEE. 2008: 5531–5538

  View details for Web of Science ID 000307311605110

• Implications of autonomy for the expressiveness of policy routing IEEE-ACM TRANSACTIONS ON NETWORKING Feamster, N., Johari, R., Balakrishnan, H. 2007; 15 (6): 1266-1279

  View details for DOI 10.1109/TNET.2007.896531

  View details for Web of Science ID 000252125200005

• Partially optimal routing 40th Annual Conference on Information Sciences and Systems (CISS) Acemoglu, D., Johari, R., Ozdaglar, A. IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. 2007: 1148–60

  View details for DOI 10.1109/JSAC.2007.070809

  View details for Web of Science ID 000248352300009

• Network formation: Bilateral contracting and myopic dynamics 3rd International Workshop on Internet and Network Economics Arcaute, E., Johari, R., Mannor, S. SPRINGER-VERLAG BERLIN. 2007: 191–207

  View details for Web of Science ID 000252182500020

• Efficiency loss and the design of scalable resource allocation mechanisms. Algorithmic Game Theory Johari , R. edited by Nisan, N., Roughgarden, T., Tardos,  E. Cambridge University Press: Cambridge, United Kingdom.. 2007: 543–567
• Revenue management for content delivery. Shakkottai, S., Johari, R. 2007
• Network formation: bilateral contracting and myopic dynamics. Arcaute, E., Johari, R., Mannor, S. 2007
• Oblivious equilibrium for general stochastic games with many players. Abhishek, V., Adlakha, S., Johari, R., Weintraub, G., Y. 2007
• Dynamics and stability in network formation games with bilateral contracts 46th IEEE Conference on Decision and Control Arcaute, E., Dallal, E., Johari, R., Mannor, S. IEEE. 2007: 5871–5878

  View details for Web of Science ID 000255181703134

• A contract-based model for directed network formation GAMES AND ECONOMIC BEHAVIOR Johari, R., Mannor, S., Tsitsiklis, J. N. 2006; 56 (2): 201-224

  View details for DOI 10.1016/j.geb.2005.08.010

  View details for Web of Science ID 000238585500001

• A scalable network resource allocation mechanism with bounded efficiency loss IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS Johari, R., Tsitsikils, J. N. 2006; 24 (5): 992-999

  View details for DOI 10.1109/JSAC.2006.872880

  View details for Web of Science ID 000237401600006

• Paradoxes of traffic engineering with partially optimal routing 40th Annual Conference on Information Sciences and Systems (CISS) Acemoglu, D., Johari, R., Ozdaglar, A. IEEE. 2006: 661–667

  View details for Web of Science ID 000244721800125

• Positive externalities and optimal scale. Kumar, S., Johari, R. 2006
• A peer-to-peer system as an exchange economy. Aperjis, C., Johari, R. 2006
• Efficiency-loss in a network resource allocation game: The case of elastic supply IEEE TRANSACTIONS ON AUTOMATIC CONTROL Johari, R., Mannor, S., Tsitsiklis, J. N. 2005; 50 (11): 1712-1724

  View details for DOI 10.1109/TAC.2005.858687

  View details for Web of Science ID 000233442700006

• Implications of autonomy for the expressiveness of policy routing SIGCOMM/ACM Conference on Computer Communications Feamster, N., Johari, R., Balakrishnan, H. ASSOC COMPUTING MACHINERY. 2005: 25–36

  View details for Web of Science ID 000233120000004

• A game theoretic view of efficiency loss in resource allocation Symposium on Systems, Control, and Networks Johari, R., Tsitsiklis, J. N. BIRKHAUSER BOSTON. 2005: 203–223

  View details for Web of Science ID 000231525400012

• Communication requirements of VCG-like mechanisms in convex environments. Johari, R., Tsitsiklis, J., N. 2005
• Efficiency loss in a network resource allocation game: the case of elastic supply. IEEE Transactions on Automatic Control Johari, R., Mannor, S., Tsitsiklis, J., N. 2005; 11 (50): 1712-1724
• Efficiency loss in a network resource allocation game MATHEMATICS OF OPERATIONS RESEARCH Johari, R., Tsitsiklis, J. N. 2004; 29 (3): 407-435

  View details for Web of Science ID 000224311900001

• Efficiency loss in a resource allocation game: A single link in elastic supply 43rd IEEE Conference on Decision and Control Johari, R., Mannor, S., Tsitsiklis, J. N. IEEE. 2004: 4679–4683

  View details for Web of Science ID 000226745604028

• Routing and peering in a competitive Internet 43rd IEEE Conference on Decision and Control Johari, R., Tsitsiklis, J. N. IEEE. 2004: 1556–1561

  View details for Web of Science ID 000226745601073

• Network resource allocation and a congestion game: the single link case. Johari, R., Tsitsiklis, J., N. 2003
• End-to-end congestion control for the Internet: delays and stability. IEEE/ACM Transactions on Networking Johari, R., Tan, D., K.H. 2001; 6 (9): 818-832