| Machine learning for perovskites' reap-rest-recovery cycle JM Howard, EM Tennyson, BRA Neves, MS Leite Joule 3 (2), 325-337, 2019 | 73 | 2019 |
| Machine learning roadmap for perovskite photovoltaics M Srivastava, JM Howard, T Gong, M Rebello Sousa Dias, MS Leite The Journal of Physical Chemistry Letters 12 (32), 7866-7877, 2021 | 58 | 2021 |
| Humidity-induced photoluminescence hysteresis in variable Cs/Br ratio hybrid perovskites JM Howard, EM Tennyson, S Barik, R Szostak, E Waks, MF Toney, ... The Journal of Physical Chemistry Letters 9 (12), 3463-3469, 2018 | 58 | 2018 |
| Mesoscale functional imaging of materials for photovoltaics EM Tennyson, JM Howard, MS Leite ACS Energy Letters 2 (8), 1825-1834, 2017 | 48 | 2017 |
| Imaging metal halide perovskites material and properties at the nanoscale JM Howard, R Lahoti, MS Leite Advanced Energy Materials 10 (26), 1903161, 2020 | 27 | 2020 |
| NIST Language Recognition Evaluation-Past and Future. AF Martin, CS Greenberg, JM Howard, GR Doddington, JJ Godfrey Odyssey, 2014 | 19 | 2014 |
| Photovoltage tomography in polycrystalline solar cells EM Tennyson, JA Frantz, JM Howard, WB Gunnarsson, JD Myers, ... ACS Energy Letters 1 (5), 899-905, 2016 | 16 | 2016 |
| Quantitative predictions of moisture-driven photoemission dynamics in metal halide perovskites via machine learning JM Howard, Q Wang, M Srivastava, T Gong, E Lee, A Abate, MS Leite The Journal of Physical Chemistry Letters 13 (9), 2254-2263, 2022 | 15 | 2022 |
| The effects of incident photon energy on the time-dependent voltage response of lead halide perovskites EM Tennyson, JM Howard, B Roose, JL Garrett, JN Munday, A Abate, ... Chemistry of Materials 31 (21), 8969-8976, 2019 | 14 | 2019 |
| Results of The 2015 NIST Language Recognition Evaluation. H Zhao, D Bansé, GR Doddington, CS Greenberg, J Hernández-Cordero, ... INTERSPEECH, 3206-3210, 2016 | 10 | 2016 |
| Summary of the 2015 nist language recognition i-vector machine learning challenge AN Tong, CS Greenberg, AF Martin, D Banse, JM Howard, ... Audrey N. Tong, Craig S. Greenberg, Alvin F. Martin, Desire Banse, John M …, 2016 | 9 | 2016 |
| Nist language recognition evaluation—plans for 2015 AF Martin, CS Greenberg, JM Howard, D Bansé, GR Doddington, ... Sixteenth Annual Conference of the International Speech Communication …, 2015 | 8 | 2015 |
| Process parameter effects on cellular structured materials using hollow glass spheres J Park, JM Howard, A Edery, M DeMay, N Wereley Materials and Manufacturing Processes 34 (9), 1026-1034, 2019 | 6 | 2019 |
| Quantitative predictions of photo-emission dynamics in metal halide perovskites via machine learning JM Howard, Q Wang, E Lee, R Lahoti, T Gong, M Srivastava, A Abate, ... arXiv preprint arXiv:2010.03702, 2020 | 5 | 2020 |
| Performance factor analysis for the 2012 NIST speaker recognition evaluation. AF Martin, CS Greenberg, VM Stanford, JM Howard, GR Doddington, ... INTERSPEECH, 1135-1138, 2014 | 4 | 2014 |
| Effects of the New Testing Paradigm of the 2012 NIST Speaker Recognition Evaluation. AF Martin, CS Greenberg, JM Howard, GR Doddington, JJ Godfrey, ... Odyssey, 2014 | 3 | 2014 |
| Bilayer glass foams with tunable energy absorption via localized void clusters J Park, JM Howard, A Edery, M DeMay, N Wereley Advanced Engineering Materials 23 (9), 2100105, 2021 | 2 | 2021 |
| Analysis of the second phase of the 2013-2014 i-vector machine learning challenge. D Bansé, GR Doddington, D Garcia-Romero, JJ Godfrey, CS Greenberg, ... INTERSPEECH, 3041-3045, 2015 | 2 | 2015 |
| Visco-Elastic Honeycomb Structures with Increased Energy Absorption and Shape Recovery Performance Using Buckling Initiators CM Murray, M Mao, J Park, J Howard, NM Wereley Polymers 15 (16), 3350, 2023 | 1 | 2023 |
| Tunable Energy Absorbing Property of Bilayer Amorphous Glass Foam via Dry Powder Printing J Park, J Howard, A Edery, M DeMay, N Wereley Materials 15 (24), 9080, 2022 | 1 | 2022 |
Marina S. LeiteUniversity of California, DavisVerified email at ucdavis.edu
