Michael W. Jack

1.8k total citations
72 papers, 1.3k citations indexed

About

Michael W. Jack is a scholar working on Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering and Molecular Biology. According to data from OpenAlex, Michael W. Jack has authored 72 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Atomic and Molecular Physics, and Optics, 24 papers in Electrical and Electronic Engineering and 14 papers in Molecular Biology. Recurrent topics in Michael W. Jack's work include Smart Grid Energy Management (15 papers), Cold Atom Physics and Bose-Einstein Condensates (12 papers) and Building Energy and Comfort Optimization (11 papers). Michael W. Jack is often cited by papers focused on Smart Grid Energy Management (15 papers), Cold Atom Physics and Bose-Einstein Condensates (12 papers) and Building Energy and Comfort Optimization (11 papers). Michael W. Jack collaborates with scholars based in New Zealand, Japan and United States. Michael W. Jack's co-authors include M. J. Collett, Ramsey I. Kamar, Janet Stephenson, Randall G. Hulet, Guthrie B. Partridge, Kevin E. Strecker, D. F. Walls, Imran Khan, Makoto Yamashita and M. Imroz Sohel and has published in prestigious journals such as Physical Review Letters, Renewable and Sustainable Energy Reviews and Bioresource Technology.

In The Last Decade

Michael W. Jack

67 papers receiving 1.3k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Michael W. Jack New Zealand 20 700 237 176 169 136 72 1.3k
Yijun Tang China 11 379 0.5× 104 0.4× 44 0.3× 92 0.5× 42 0.3× 27 734
Ralf Klein Belgium 16 113 0.2× 60 0.3× 42 0.2× 73 0.4× 39 0.3× 32 1.1k
Zui Tao China 27 523 0.7× 739 3.1× 129 0.7× 232 1.4× 113 0.8× 61 2.3k
Wei Mao China 20 261 0.4× 961 4.1× 37 0.2× 197 1.2× 61 0.4× 174 1.7k
Yingwen Zhang China 24 918 1.3× 281 1.2× 575 3.3× 567 3.4× 20 0.1× 93 1.9k
S. Sankararaman India 19 73 0.1× 172 0.7× 64 0.4× 346 2.0× 82 0.6× 143 1.1k
Ke Liu China 24 631 0.9× 1.0k 4.3× 166 0.9× 463 2.7× 19 0.1× 122 2.0k
Hongkai Chen China 15 76 0.1× 109 0.5× 35 0.2× 50 0.3× 95 0.7× 104 787
Xing Li China 23 506 0.7× 372 1.6× 21 0.1× 87 0.5× 57 0.4× 127 1.9k
Zhiming Zheng China 25 107 0.2× 1.4k 5.9× 118 0.7× 44 0.3× 72 0.5× 82 2.4k

Countries citing papers authored by Michael W. Jack

Since Specialization
Citations

This map shows the geographic impact of Michael W. Jack's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael W. Jack with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael W. Jack more than expected).

Fields of papers citing papers by Michael W. Jack

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael W. Jack. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael W. Jack. The network helps show where Michael W. Jack may publish in the future.

Co-authorship network of co-authors of Michael W. Jack

This figure shows the co-authorship network connecting the top 25 collaborators of Michael W. Jack. A scholar is included among the top collaborators of Michael W. Jack based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michael W. Jack. Michael W. Jack is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Jack, Michael W. & Mahesh Bandi. (2025). Extreme value statistics of peak residential electricity demand: Effect of aggregation and moving-average smoothing. Sustainable Energy Grids and Networks. 42. 101674–101674.
2.
Jack, Michael W., et al.. (2025). Estimating the seasonal variation in electricity demand of future electric vehicle fleets. Energy. 333. 137089–137089. 1 indexed citations
3.
Jack, Michael W., et al.. (2022). An inverse-problem approach to simulating smart control of domestic electric hot water cylinders using electricity demand time-series data.. Energy and Buildings. 278. 112644–112644. 3 indexed citations
4.
Jack, Michael W., et al.. (2022). Nonequilibrium master equation for interacting Brownian particles in a deep-well periodic potential. Physical review. E. 105(5). 54150–54150. 1 indexed citations
5.
Jack, Michael W., et al.. (2020). Lightening the load: quantifying the potential for energy-efficient lighting to reduce peaks in electricity demand. Energy Efficiency. 13(6). 1105–1118. 18 indexed citations
6.
Jack, Michael W., et al.. (2020). Thermodynamic uncertainty relations and molecular-scale energy conversion. Physical review. E. 101(6). 62123–62123. 11 indexed citations
7.
Suomalainen, Kiti, David Eyers, Rebecca Ford, et al.. (2018). Detailed comparison of energy-related time-use diaries and monitored residential electricity demand. Energy and Buildings. 183. 418–427. 15 indexed citations
8.
Anderson, Ben, et al.. (2018). Electrifying Heat: Patterns of electricity consumption in electrically heated households in the UK and New Zealand. ePrints Soton (University of Southampton).
9.
Anderson, Ben, David Eyers, Rebecca Ford, et al.. (2018). New Zealand grid household electricity demand study 2014-2018. ePrints Soton (University of Southampton). 18 indexed citations
10.
Jack, Michael W., et al.. (2018). Analysing single-molecule trajectories to reconstruct free-energy landscapes of cyclic motor proteins. Journal of Theoretical Biology. 462. 321–328. 6 indexed citations
11.
Nguyen, Phuong, et al.. (2016). Local discretization method for overdamped Brownian motion on a potential with multiple deep wells. Physical review. E. 94(5). 52127–52127. 4 indexed citations
12.
Nguyen, Phuong, et al.. (2016). Tight-binding approach to overdamped Brownian motion on a bichromatic periodic potential. Physical review. E. 93(2). 22124–22124. 4 indexed citations
13.
Jack, Michael W., et al.. (2013). Thermal fluctuation statistics in a molecular motor described by a multidimensional master equation. Physical Review E. 88(6). 62136–62136. 7 indexed citations
14.
Jack, Michael W., et al.. (2013). Tight-binding approach to overdamped Brownian motion on a multidimensional tilted periodic potential. Physical Review E. 87(5). 52102–52102. 15 indexed citations
15.
Newman, Roger H., Alankar A. Vaidya, M. Imroz Sohel, & Michael W. Jack. (2012). Optimizing the enzyme loading and incubation time in enzymatic hydrolysis of lignocellulosic substrates. Bioresource Technology. 129. 33–38. 24 indexed citations
16.
Sohel, M. Imroz & Michael W. Jack. (2010). Efficiency improvements by geothermal heat integration in a lignocellulosic biorefinery. Bioresource Technology. 101(23). 9342–9347. 10 indexed citations
17.
Sohel, M. Imroz & Michael W. Jack. (2010). Thermodynamic analysis of lignocellulosic biofuel production via a biochemical process: Guiding technology selection and research focus. Bioresource Technology. 102(3). 2617–2622. 31 indexed citations
18.
Jack, Michael W.. (2009). Scaling laws and technology development strategies for biorefineries and bioenergy plants. Bioresource Technology. 100(24). 6324–6330. 33 indexed citations
19.
Jack, Michael W., et al.. (2007). ChemiCal modifiCation of timber deCking : assessing the Parameters of aCCePtability. New Zealand journal of forestry science. 37(3). 412–434. 1 indexed citations
20.
Jack, Michael W.. (2002). Decoherence due to Three-Body Loss and its Effect on the State of a Bose-Einstein Condensate. Physical Review Letters. 89(14). 140402–140402. 47 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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