Bio

Ivana Maric received her B.S. degree from the University of Novi Sad, Serbia. She received her M.S and Ph.D. from Rutgers University. From 2006 to 2010 she was a postdoctoral scholar at Stanford University. From 2010 to 2013 she was with Aviat Networks, Santa Clara, CA. From 2013 to 2017 she was at Ericsson Research, Santa Clara, CA. During Spring 2016 she was an adjunct faculty at Santa Clara University. Since 2017, she is a Research Scientist at the Prematurity Research Center at Stanford University, School of Medicine.

Her research focuses on applying machine learning to improving maternal and perinatal health. Previously, her research has focused on information theory, a mathematical discipline tightly related to statistics and machine learning. She co-edited and co-authored a book, a monograph, two book chapters and multiple journal and conference papers on the topic. She served as an Associate Editor for the IEEE Communications Letters from 2009 to 2012, for the Trans. on Emerging Telecommunications Technologies from 2016 to 2018. She is a co-recipient of the 2021 Rosenkranz Prize and the 2013 IEEE Communications Society Best Tutorial Paper Award.

Honors & Awards

  • The Rosenkranz Prize, Freeman Spogli Institute for International Studies and Stanford Health Policy, Stanford University (2021)
  • IEEE Communications Society Best Tutorial Paper Award, IEEE (2013)

Contact

  • Academic
    ivanam@stanford.edu
    University - Academic staff Department: Pediatrics - Neonatology Position: Sr Res Scientist-Basic Life

Additional Info

  • Mail Code: 5731

Links

All Publications

  • Data-Driven Modeling of Pregnancy-Related Complications. Trends in molecular medicine Espinosa, C. n., Becker, M. n., Marić, I. n., Wong, R. J., Shaw, G. M., Gaudilliere, B. n., Aghaeepour, N. n., Stevenson, D. K. 2021

    Abstract

    A healthy pregnancy depends on complex interrelated biological adaptations involving placentation, maternal immune responses, and hormonal homeostasis. Recent advances in high-throughput technologies have provided access to multiomics biological data that, combined with clinical and social data, can provide a deeper understanding of normal and abnormal pregnancies. Integration of these heterogeneous datasets using state-of-the-art machine-learning methods can enable the prediction of short- and long-term health trajectories for a mother and offspring and the development of treatments to prevent or minimize complications. We review advanced machine-learning methods that could: provide deeper biological insights into a pregnancy not yet unveiled by current methodologies; clarify the etiologies and heterogeneity of pathologies that affect a pregnancy; and suggest the best approaches to address disparities in outcomes affecting vulnerable populations.

    View details for DOI 10.1016/j.molmed.2021.01.007

    View details for PubMedID 33573911

  • Mortality Risk Among Patients With COVID-19 Prescribed Selective Serotonin Reuptake Inhibitor Antidepressants. JAMA network open Oskotsky, T., Maric, I., Tang, A., Oskotsky, B., Wong, R. J., Aghaeepour, N., Sirota, M., Stevenson, D. K. 2021; 4 (11): e2133090

    Abstract

    Antidepressant use may be associated with reduced levels of several proinflammatory cytokines suggested to be involved with the development of severe COVID-19. An association between the use of selective serotonin reuptake inhibitors (SSRIs)-specifically fluoxetine hydrochloride and fluvoxamine maleate-with decreased mortality among patients with COVID-19 has been reported in recent studies; however, these studies had limited power due to their small size.To investigate the association of SSRIs with outcomes in patients with COVID-19 by analyzing electronic health records (EHRs).This retrospective cohort study used propensity score matching by demographic characteristics, comorbidities, and medication indication to compare SSRI-treated patients with matched control patients not treated with SSRIs within a large EHR database representing a diverse population of 83 584 patients diagnosed with COVID-19 from January to September 2020 and with a duration of follow-up of as long as 8 months in 87 health care centers across the US.Selective serotonin reuptake inhibitors and specifically (1) fluoxetine, (2) fluoxetine or fluvoxamine, and (3) other SSRIs (ie, not fluoxetine or fluvoxamine).Death.A total of 3401 adult patients with COVID-19 prescribed SSRIs (2033 women [59.8%]; mean [SD] age, 63.8 [18.1] years) were identified, with 470 receiving fluoxetine only (280 women [59.6%]; mean [SD] age, 58.5 [18.1] years), 481 receiving fluoxetine or fluvoxamine (285 women [59.3%]; mean [SD] age, 58.7 [18.0] years), and 2898 receiving other SSRIs (1733 women [59.8%]; mean [SD] age, 64.7 [18.0] years) within a defined time frame. When compared with matched untreated control patients, relative risk (RR) of mortality was reduced among patients prescribed any SSRI (497 of 3401 [14.6%] vs 1130 of 6802 [16.6%]; RR, 0.92 [95% CI, 0.85-0.99]; adjusted P = .03); fluoxetine (46 of 470 [9.8%] vs 937 of 7050 [13.3%]; RR, 0.72 [95% CI, 0.54-0.97]; adjusted P = .03); and fluoxetine or fluvoxamine (48 of 481 [10.0%] vs 956 of 7215 [13.3%]; RR, 0.74 [95% CI, 0.55-0.99]; adjusted P = .04). The association between receiving any SSRI that is not fluoxetine or fluvoxamine and risk of death was not statistically significant (447 of 2898 [15.4%] vs 1474 of 8694 [17.0%]; RR, 0.92 [95% CI, 0.84-1.00]; adjusted P = .06).These results support evidence that SSRIs may be associated with reduced severity of COVID-19 reflected in the reduced RR of mortality. Further research and randomized clinical trials are needed to elucidate the effect of SSRIs generally, or more specifically of fluoxetine and fluvoxamine, on the severity of COVID-19 outcomes.

    View details for DOI 10.1001/jamanetworkopen.2021.33090

    View details for PubMedID 34779847

  • Decreased Mortality Rate Among COVID-19 Patients Prescribed Statins: Data From Electronic Health Records in the US Frontiers in Medicine Maric, I., Oskotsky, T., Kosti, I., Le, B., Wong, R. J., Shaw, G. M., Sirota, M., Stevenson, D. K. 2021; 8

    View details for DOI 10.3389/fmed.2021.639804

  • Towards personalized medicine in maternal and child health: integrating biologic and social determinants. Pediatric research Stevenson, D. K., Wong, R. J., Aghaeepour, N., Maric, I., Angst, M. S., Contrepois, K., Darmstadt, G. L., Druzin, M. L., Eisenberg, M. L., Gaudilliere, B., Gibbs, R. S., Gotlib, I. H., Gould, J. B., Lee, H. C., Ling, X. B., Mayo, J. A., Moufarrej, M. N., Quaintance, C. C., Quake, S. R., Relman, D. A., Sirota, M., Snyder, M. P., Sylvester, K. G., Hao, S., Wise, P. H., Shaw, G. M., Katz, M. 2020

    View details for DOI 10.1038/s41390-020-0981-8

    View details for PubMedID 32454518

  • Early Prediction of Preeclampsia via Machine Learning American Journal of Obstetrics & Gynecology MFM Maric, I., Tsur, A., Aghaeepour, N., Montanari, A., Stevenson, D. K., Shaw, G. M., Winn, V. D. 2020; 2 (2)
  • Multiomics Characterization of Preterm Birth in Low- and Middle-Income Countries (vol 3, e2029655, 2020) JAMA NETWORK OPEN Jehan, F., Sazawal, S., Baqui, A. H. 2021; 4 (2)

    View details for DOI 10.1001/jamanetworkopen.2021.0399

    View details for Web of Science ID 000617274100003

  • PERSISTENT BACTERIAL VAGINOSIS AND RISK FOR SPONTANEOUS PRETERM BIRTH Blumenfeld, Y. J., Maric, I., Stevenson, D. K., Shaw, G. M. BMJ PUBLISHING GROUP. 2021: 127–28

    View details for DOI 10.1136/jim-2021-WRMC.58

    View details for Web of Science ID 000608729100076

  • DECREASED MORTALITY RATE AMONG COVID-19 PATIENTS USING STATINS: DATA FROM US ELECTRONIC HEALTH RECORDS Oskotsky, T., Maric, I., Kosti, I., Le, B. L., Wong, R. J., Shaw, G. M., Sirota, M., Stevenson, D. K. BMJ PUBLISHING GROUP. 2021: 219–20

    View details for DOI 10.1136/jim-2021-WRMC.262

    View details for Web of Science ID 000608729100280

  • Integration of mechanistic immunological knowledge into a machine learning pipeline improves predictions NATURE MACHINE INTELLIGENCE Culos, A., Tsai, A. S., Stanley, N., Becker, M., Ghaemi, M. S., McIlwain, D. R., Fallahzadeh, R., Tanada, A., Nassar, H., Espinosa, C., Xenochristou, M., Ganio, E., Peterson, L., Han, X., Stelzer, I. A., Ando, K., Gaudilliere, D., Phongpreecha, T., Maric, I., Chang, A. L., Shaw, G. M., Stevenson, D. K., Bendall, S., Davis, K. L., Fantl, W., Nolan, G. P., Hastie, T., Tibshirani, R., Angst, M. S., Gaudilliere, B., Aghaeepour, N. 2020

    View details for DOI 10.1038/s42256-020-00232-8

    View details for Web of Science ID 000579336000001

  • Changes in pregnancy-related serum biomarkers early in gestation are associated with later development of preeclampsia. PloS one Hao, S. n., You, J. n., Chen, L. n., Zhao, H. n., Huang, Y. n., Zheng, L. n., Tian, L. n., Maric, I. n., Liu, X. n., Li, T. n., Bianco, Y. K., Winn, V. D., Aghaeepour, N. n., Gaudilliere, B. n., Angst, M. S., Zhou, X. n., Li, Y. M., Mo, L. n., Wong, R. J., Shaw, G. M., Stevenson, D. K., Cohen, H. J., Mcelhinney, D. B., Sylvester, K. G., Ling, X. B. 2020; 15 (3): e0230000

    Abstract

    Placental protein expression plays a crucial role during pregnancy. We hypothesized that: (1) circulating levels of pregnancy-associated, placenta-related proteins throughout gestation reflect the temporal progression of the uncomplicated, full-term pregnancy, and can effectively estimate gestational ages (GAs); and (2) preeclampsia (PE) is associated with disruptions in these protein levels early in gestation; and can identify impending PE. We also compared gestational profiles of proteins in the human and mouse, using pregnant heme oxygenase-1 (HO-1) heterozygote (Het) mice, a mouse model reflecting PE-like symptoms.Serum levels of placenta-related proteins-leptin (LEP), chorionic somatomammotropin hormone like 1 (CSHL1), elabela (ELA), activin A, soluble fms-like tyrosine kinase 1 (sFlt-1), and placental growth factor (PlGF)-were quantified by ELISA in blood serially collected throughout human pregnancies (20 normal subjects with 66 samples, and 20 subjects who developed PE with 61 samples). Multivariate analysis was performed to estimate the GA in normal pregnancy. Mean-squared errors of GA estimations were used to identify impending PE. The human protein profiles were then compared with those in the pregnant HO-1 Het mice.An elastic net-based gestational dating model was developed (R2 = 0.76) and validated (R2 = 0.61) using serum levels of the 6 proteins measured at various GAs from women with normal uncomplicated pregnancies. In women who developed PE, the model was not (R2 = -0.17) associated with GA. Deviations from the model estimations were observed in women who developed PE (P = 0.01). The model developed with 5 proteins (ELA excluded) performed similarly from sera from normal human (R2 = 0.68) and WT mouse (R2 = 0.85) pregnancies. Disruptions of this model were observed in both human PE-associated (R2 = 0.27) and mouse HO-1 Het (R2 = 0.30) pregnancies. LEP outperformed sFlt-1 and PlGF in differentiating impending PE at early human and late mouse GAs.Serum placenta-related protein profiles are temporally regulated throughout normal pregnancies and significantly disrupted in women who develop PE. LEP changes earlier than the well-established biomarkers (sFlt-1 and PlGF). There may be evidence of a causative action of HO-1 deficiency in LEP upregulation in a PE-like murine model.

    View details for DOI 10.1371/journal.pone.0230000

    View details for PubMedID 32126118

  • VoPo leverages cellular heterogeneity for predictive modeling of single-cell data. Nature communications Stanley, N. n., Stelzer, I. A., Tsai, A. S., Fallahzadeh, R. n., Ganio, E. n., Becker, M. n., Phongpreecha, T. n., Nassar, H. n., Ghaemi, S. n., Maric, I. n., Culos, A. n., Chang, A. L., Xenochristou, M. n., Han, X. n., Espinosa, C. n., Rumer, K. n., Peterson, L. n., Verdonk, F. n., Gaudilliere, D. n., Tsai, E. n., Feyaerts, D. n., Einhaus, J. n., Ando, K. n., Wong, R. J., Obermoser, G. n., Shaw, G. M., Stevenson, D. K., Angst, M. S., Gaudilliere, B. n., Aghaeepour, N. n. 2020; 11 (1): 3738

    Abstract

    High-throughput single-cell analysis technologies produce an abundance of data that is critical for profiling the heterogeneity of cellular systems. We introduce VoPo (https://github.com/stanleyn/VoPo), a machine learning algorithm for predictive modeling and comprehensive visualization of the heterogeneity captured in large single-cell datasets. In three mass cytometry datasets, with the largest measuring hundreds of millions of cells over hundreds of samples, VoPo defines phenotypically and functionally homogeneous cell populations. VoPo further outperforms state-of-the-art machine learning algorithms in classification tasks, and identified immune-correlates of clinically-relevant parameters.

    View details for DOI 10.1038/s41467-020-17569-8

    View details for PubMedID 32719375

  • Increased Carbon Monoxide Washout Rates in Newborn Infants. Neonatology Stevenson, D. K., Wong, R. J., Ostrander, C. R., Maric, I., Vreman, H. J., Cohen, R. S. 2019: 1–5

    Abstract

    BACKGROUND: Endogenous carbon monoxide (CO) production is primarily due to heme degradation, which also results in the equimolar production of bilirubin. Thus, estimates of total body CO production can serve as indices of total body bilirubin formation. The elimination rate of CO from a person's body (CO washout rate) after exposure to an elevated ambient CO concentration is determined by a variety of factors, and is very different between babies and adults.OBJECTIVE: We determined CO washout rates for babies using a simplified technique to measure total body CO excretion rates (VeCO).METHODS: Using a simplified technique, we measured the times to reach an approximate steady state after a change in ambient CO concentration (decay time constant) and CO washout rates in normal newborn infants using non-linear least squares curve fitting.RESULTS: We found a mean CO washout time of 18.7 ± 4.2 min and a CO equilibration (decay time) constant of 0.12 ± 0.04/min (0.08-0.21) for newborn infants.CONCLUSIONS: We confirm that CO washout rates for babies are much faster than those for adults. Therefore, measurements of carboxyhemoglobin (COHb) or end-tidal CO (ETCO), corrected for ambient CO, (COHbc and ETCOc, respectively) can be used as surrogates for VeCO and can provide accurate estimates of endogenous CO (VCO) and bilirubin production rates under normal environmental conditions. Such measurements can be used to identify infants with severe hyperbilirubinemia due to hemolysis and thus at high risk for bilirubin neurotoxicity.

    View details for DOI 10.1159/000503635

    View details for PubMedID 31634890

  • Data-driven queries between medications and spontaneous preterm birth among 2.5 million pregnancies. Birth defects research Marić, I. n., Winn, V. D., Borisenko, E. n., Weber, K. A., Wong, R. J., Aziz, N. n., Blumenfeld, Y. J., El-Sayed, Y. Y., Stevenson, D. K., Shaw, G. M. 2019

    Abstract

    Our goal was to develop an approach that can systematically identify potential associations between medication prescribed in pregnancy and spontaneous preterm birth (sPTB) by mining large administrative "claims" databases containing hundreds of medications. One such association that we illustrate emerged with antiviral medications used for herpes treatment.IBM MarketScan® databases (2007-2016) were used. A pregnancy cohort was established using International Classification of Diseases (ICD-9/10) codes. Multiple hypothesis testing and the Benjamini-Hochberg procedure that limited false discovery rate at 5% revealed, among 863 medications, five that showed odds ratios (ORs) <1. The statistically strongest was an association between antivirals and sPTB that we illustrate as a real example of our approach, specifically for treatment of genital herpes (GH). Three groups of women were identified based on diagnosis of GH and treatment during the first 36 weeks of pregnancy: (a) GH without treatment; (b) GH treated with antivirals; (c) no GH or treatment.We identified 2,538,255 deliveries. 0.98% women had a diagnosis of GH. Among them, 60.0% received antiviral treatment. Women with treated GH had OR < 1, (OR [95% CI] = 0.91 [0.85, 0.98]). In contrast, women with untreated GH had a small increased risk of sPTB (OR [95% CI] =1.22 [1.14, 1.32]).Data-driven approaches can effectively generate new hypotheses on associations between medications and sPTB. This analysis led us to examine the association with GH treatment. While unknown confounders may impact these findings, our results indicate that women with untreated GH have a modest increased risk of sPTB.

    View details for DOI 10.1002/bdr2.1580

    View details for PubMedID 31433567

  • Maternal Height and Risk of Preeclampsia among Race/Ethnic Groups. American journal of perinatology Maric, I., Mayo, J. A., Druzin, M. L., Wong, R. J., Winn, V. D., Stevenson, D. K., Shaw, G. M. 2018

    Abstract

    OBJECTIVE: Shorter maternal height has been associated with preeclampsia risk in several populations. It has been less evident whether an independent contribution to the risk exists from maternal height consistently across different races/ethnicities. We investigated associations between maternal height and risk of preeclampsia for different races/ethnicities.STUDY DESIGN: California singleton live births from 2007 to 2011 were analyzed. Logistic regression was used to estimate adjusted odds ratios for the association between height and preeclampsia after stratification by race/ethnicity. To determine the contribution of height that is as independent of body composition as possible, we performed one analysis adjusted for body mass index (BMI) and the other for weight. Additional analyses were performed stratified by parity, and the presence of preexisting/gestational diabetes and autoimmune conditions.RESULTS: Among 2,138,012 deliveries, 3.1% preeclampsia/eclampsia cases were observed. The analysis, adjusted for prepregnancy weight, revealed an inverse relation between maternal height and risk of mild and severe preeclampsia/eclampsia. When the analysis was adjusted for BMI, an inverse relation between maternal height was observed for severe preeclampsia/eclampsia. These associations were observed for each race/ethnicity.CONCLUSION: Using a large and diverse cohort, we demonstrated that shorter height, irrespective of prepregnancy weight or BMI, is associated with an increased risk of severe preeclampsia/eclampsia across different races/ethnicities.

    View details for PubMedID 30396225

  • Residential agricultural pesticide exposures and risks of preeclampsia ENVIRONMENTAL RESEARCH Shaw, G. M., Yang, W., Roberts, E. M., Aghaeepour, N., Mayo, J. A., Weber, K. A., Maric, I., Carmichael, S. L., Winn, V. D., Stevenson, D. K., English, P. B. 2018; 164: 546–55

    View details for DOI 10.1016/j.envres.2018.03.020

    View details for Web of Science ID 000431387100065

  • Capacity-Achieving Rate-Compatible Polar Codes for General Channels IEEE Wireless Communications and Networking Conference Workshops (WCNCW) Mondelli, M., Hassani, H., Marić, I., Hui, D., Hong, S. 2017

    View details for DOI 10.1109/WCNCW.2017.7919107

  • Capacity-Achieving Rate-Compatible Polar Codes IEEE Trans. Information Theory Hong, S., Hui, D., Maric, I. 2017; 63 (12): 7620-7632
  • Short Message Noisy Network Coding With Sliding-Window Decoding for Half-Duplex Multihop Relay Networks IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS Hong, S., Maric, I., Hui, D. 2016; 15 (10): 6676-6689

    View details for DOI 10.1109/TWC.2016.2587627

    View details for Web of Science ID 000386068800012

  • Capacity-Achieving Rate-Compatible Polar Codes 2016 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY Hong, S., Hui, D., Maric, I. 2016: 41-45

    View details for Web of Science ID 000390098700009

  • Diversity-Multiplexing Tradeoff for the Interference Channel With a Relay IEEE TRANSACTIONS ON INFORMATION THEORY Zahavi, D., Zhang, L., Maric, I., Dabora, R., Goldsmith, A. J., Cui, S. 2015; 61 (2): 963-982

    View details for DOI 10.1109/TIT.2014.2381664

    View details for Web of Science ID 000348298400020

  • Multihop Virtual Full-Duplex Relay Channels 2015 IEEE INFORMATION THEORY WORKSHOP (ITW) Hong, S., Maric, I., Hui, D., Caire, G. 2015

    View details for Web of Science ID 000381501800073

  • On the Achievable Rates of Multihop Virtual Full-Duplex Relay Channels 2015 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT) Hong, S., Maric, I., Hui, D., Caire, G. 2015: 2246-2250

    View details for Web of Science ID 000380904702060

  • Enhanced Relay Cooperation via Rate Splitting CONFERENCE RECORD OF THE 2014 FORTY-EIGHTH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS Maric, I., Hui, D. 2014: 225-229

    View details for Web of Science ID 000370964900041

  • Capacity Bounds and Exact Results for the Cognitive Z-Interference Channel IEEE TRANSACTIONS ON INFORMATION THEORY Liu, N., Maric, I., Goldsmith, A. J., Shamai (Shitz), S. 2013; 59 (2): 886-893

    View details for DOI 10.1109/TIT.2012.2225138

    View details for Web of Science ID 000313728800011

  • Low Latency Communications 2013 INFORMATION THEORY AND APPLICATIONS WORKSHOP (ITA) Maric, I. 2013

    View details for Web of Science ID 000321214400036

  • Capacity of Cognitive Radio Networks Multiantenna Channels: Principles of Cognitive Radio Goldsmith, A., Maric, I. Cambridge Press. 2013
  • Relaying in the Presence of Interference: Achievable Rates, Interference Forwarding, and Outer Bounds IEEE TRANSACTIONS ON INFORMATION THEORY Maric, I., Dabora, R., Goldsmith, A. J. 2012; 58 (7): 4342-4354

    View details for DOI 10.1109/TIT.2012.2191710

    View details for Web of Science ID 000305575000019

  • Multihop Analog Network Coding via Amplify-and-Forward: The High SNR Regime IEEE TRANSACTIONS ON INFORMATION THEORY Maric, I., Goldsmith, A., Medard, M. 2012; 58 (2): 793-803

    View details for DOI 10.1109/TIT.2011.2173721

    View details for Web of Science ID 000300246900020

  • Bandwidth and Power Allocation for Cooperative Strategies in Gaussian Relay Networks IEEE TRANSACTIONS ON INFORMATION THEORY Maric, I., Yates, R. D. 2010; 56 (4): 1880-1889

    View details for DOI 10.1109/TIT.2010.2040875

    View details for Web of Science ID 000275999500033

  • Breaking Spectrum Gridlock With Cognitive Radios: An Information Theoretic Perspective PROCEEDINGS OF THE IEEE Goldsmith, A., Jafar, S. A., Maric, I., Srinivasa, S. 2009; 97 (5): 894-914

    View details for DOI 10.1109/JPROC.2009.2015717

    View details for Web of Science ID 000266174300008

  • On the capacity of interference channels with one cooperating transmitter EUROPEAN TRANSACTIONS ON TELECOMMUNICATIONS Maric, I., Goldsmith, A., Kramer, G., Shamai (Shitz), S. 2008; 19 (4): 405-420

    View details for DOI 10.1002/ett.1298

    View details for Web of Science ID 000257012200006

  • Discrete memoryless interference and broadcast channels with confidential, messages: Secrecy rate regions IEEE Information Theory and Applications Workshop Liu, R., Maric, I., Spasojevic, P., Yates, R. D. IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. 2008: 2493–2507

    View details for DOI 10.1109/TIT.2008.921879

    View details for Web of Science ID 000258033700007

  • On the Capacity of the Interference Channel with a Relay IEEE International Symposium on Information Theory Marric, I., Dabora, R., Goldsmith, A. IEEE. 2008: 554–558

    View details for Web of Science ID 000260364400112

  • Capacity of interference channels with partial transmitter cooperation IEEE TRANSACTIONS ON INFORMATION THEORY Maric, I., Yates, R. D., Kramer, G. 2007; 53 (10): 3536-3548

    View details for DOI 10.1109/TIT.2007.904792

    View details for Web of Science ID 000249774000013

  • Joint relaying and network coding in wireless networks IEEE International Symposium on Information Theory Katti, S., Maric, I., Goldsmith, A., Katabi, D., Medard, M. IEEE. 2007: 1101–1105

    View details for Web of Science ID 000257010201052

  • Cooperative Communications Foundations and Trends in Networking Kramer, G., Maric, I., Yates, R. D. NOW Publishers Inc. 2006; 1
  • Cooperative multicast for maximum network lifetime IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS Maric, I., Yates, R. D. 2005; 23 (1): 127-135

    View details for DOI 10.1109/JSAC.2004.837343

    View details for Web of Science ID 000226063100012

  • Cooperative multihop broadcast for wireless networks IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS Maric, Yates, R. D. 2004; 22 (6): 1080–88

    View details for DOI 10.1109/JSAC.2004.830912

    View details for Web of Science ID 000223150700013