Trackademia

Welcome to Trackademia

The idea behind Trackademia is to build on existing academic databases like Google Scholar and OpenAlex so that you can trust the data and use it for whatever you want. That comes down to two things.

More data, and more ways to use it. We aggregate publication data from every major source into a single dataset and add information pulled from faculty CVs. Then we let you slice it however you want: choose which sources to build from, write your own formulas, weight journals, adjust for department size.

More accurate, and honest about where it isn’t. We focus on a smaller set of schools so we can verify everything carefully. Faculty lists come from department websites rather than being inferred from publication records, so we know who should be in the data before we go looking. When we can’t find data on someone, we record the gap instead of dropping them. Every number comes with a coverage rate you can check against ground truth.

Everything in Trackademia is built from seven units. AI merges duplicate records across sources and tags each publication so these categories hold up:

  • Publication — citation counts, authors, journal, peer review status, and more
  • Publication group — versions of the same work combined into one entity, such as a working paper and the article it became
  • Academic
  • Department
  • University
  • Field
  • Journal

There are two modes. In Database mode you browse the underlying records and filter by any of the seven units. In Analytics mode you get graphs and comparisons, and you switch views to compare two departments, compare one department against the average of the others, or see them all at once. Tabs let you focus on a particular level of the data.

Trackademia

Every graph on this site

Publications

  • Ranking Ranked table
    • Value: Citations, Weighted citations, Publications
    • Measure: Total, Mean per work, Median per work
  • Works published per year Lines over years
    • Measure: Total, Mean per academic, Median per academic
    • Calendar year or years since PhD
    • In each year or cumulative
  • Citations received per year Lines over years
    • Value: Citations, Weighted citations
    • Measure: Total, Mean per work, Median per work, Mean per academic, Median per academic
    • In each year or cumulative
  • Citation distribution Bars
    • Value: Citations, Weighted citations
  • Citations by age of work Lines over years
    • Value: Citations, Weighted citations
    • Measure: Total, Mean per work, Median per work
  • Publication type mix Ranked bars
    • Value: Citations, Weighted citations, Publications
  • Top venues Ranked bars
    • Value: Citations, Weighted citations, Publications

Academics

Departmentshere

  • Ranking Ranked table
    • Value: Citations, Weighted citations, Publications
    • Measure: Total, Mean per work, Median per work, Mean per academic, Median per academic, Formula
  • Publications over time Lines over years
    • Measure: Total, Mean per academic, Median per academic, Formula
    • Calendar year or years since PhD
    • In each year or cumulative
  • Citations over time Lines over years
    • Value: Citations, Weighted citations
    • Measure: Total, Mean per academic, Median per academic, Formula
    • In each year or cumulative
  • Makeup by tenure track Stacked bars
  • Output by rank Grouped bars
    • Value: Citations, Weighted citations, Publications
    • Measure: Total, Mean per work, Median per work, Mean per academic, Median per academic, Formula
  • Academics ranked against academics Grouped bars
    • Value: Citations, Weighted citations, Publications
    • How many ranks (opens on 5)
  • Years to promotion Grouped bars
  • Journals used Stacked bars
    • Value: Citations, Weighted citations, Publications

Journals

Fields

  • Ranking Ranked table
    • Value: Citations, Weighted citations, Publications
    • Measure: Total, Mean per work, Median per work, Mean per academic, Median per academic
  • Departments by field Bars
    • Measure: Total, Mean per work, Median per work, Mean per academic, Median per academic
  • University rollup Ranked bars
  • Coverage by field Ranked bars

Trackademia

Search the whole site

Search a person, a department, a journal or the title of a work. A person’s name brings up their profile, their publications, their department and the journals they publish in.
Trackademia
Value Measure

Departments

Mean citations per academic
1 Princeton Chemistry 12 academics 5,442
2 Harvard Chemistry 11 academics 3,360
3 Brown Chemistry 2 academics 2,086
4 Yale Chemistry 14 academics 2,026
5 Columbia Chemistry 17 academics 1,795
6 Penn Chemistry 20 academics 1,495
7 Dartmouth Chemistry 10 academics 1,202
8 Cornell Chemistry 25 academics 794

221,988 citations over 1,839 of 1,977 works (93% carry a count). 65 of 111 academics have at least one counted work. A work with no citation count is unknown here, never a zero.

Publications over time

Works published in each year
Measure X axis Each point

Brown ChemistryDartmouth ChemistryColumbia ChemistryCornell ChemistryHarvard ChemistryPenn ChemistryPrinceton ChemistryYale Chemistry

Every selected work, by the year it was published. An undated work is in no year.

What these filters select, per department not what the graph divided by
Department Academics CVScholarOpenAlex Works With a count
Cornell Chemistry 25 0/25 0.0% 12/25 0.48% 0/25 0.0% 305 282/305 0.9245901639344263%
Penn Chemistry 20 0/20 0.0% 13/20 0.65% 0/20 0.0% 380 363/380 0.9552631578947368%
Columbia Chemistry 17 0/17 0.0% 9/17 0.5294117647058824% 0/17 0.0% 339 308/339 0.9085545722713865%
Yale Chemistry 14 1/14 0.07142857142857142% 9/14 0.6428571428571429% 1/14 0.07142857142857142% 297 260/297 0.8754208754208754%
Princeton Chemistry 12 0/12 0.0% 6/12 0.5% 0/12 0.0% 161 157/161 0.9751552795031055%
Harvard Chemistry 11 0/11 0.0% 7/11 0.6363636363636364% 0/11 0.0% 242 230/242 0.9504132231404959%
Dartmouth Chemistry 10 1/10 0.1% 8/10 0.8% 1/10 0.1% 203 189/203 0.9310344827586207%
Brown Chemistry 2 0/2 0.0% 2/2 1.0% 0/2 0.0% 50 50/50 1.0%
  • Over the academics these filters select, so a filtered page describes the academics it selected and not the whole department.
  • A row with nothing held draws no mark above: the graph is quiet there because the evidence is missing, not because the work is.
  • What there was to draw from, not what the graph divided by - the graph states its own denominator above.
  • A Scholar profile is attached when at least 3 of the CV titles are found on it, or 30% of them are; one at another institution or under a different name needs 10 titles, and a profile far larger than the CV that holds only a small part of it is refused. Its articles are then checked one by one: what is not a work, or not by this person, is not counted.

Citations over time

Citations received in each year
Value Measure Each point

Brown ChemistryDartmouth ChemistryColumbia ChemistryCornell ChemistryHarvard ChemistryPenn ChemistryPrinceton ChemistryYale Chemistry

Citations received in each year, from the academics’ verified Scholar profiles.

What these filters select, per department not what the graph divided by
Department Academics CVScholarOpenAlex Works With a count
Cornell Chemistry 25 0/25 0.0% 12/25 0.48% 0/25 0.0% 305 282/305 0.9245901639344263%
Penn Chemistry 20 0/20 0.0% 13/20 0.65% 0/20 0.0% 380 363/380 0.9552631578947368%
Columbia Chemistry 17 0/17 0.0% 9/17 0.5294117647058824% 0/17 0.0% 339 308/339 0.9085545722713865%
Yale Chemistry 14 1/14 0.07142857142857142% 9/14 0.6428571428571429% 1/14 0.07142857142857142% 297 260/297 0.8754208754208754%
Princeton Chemistry 12 0/12 0.0% 6/12 0.5% 0/12 0.0% 161 157/161 0.9751552795031055%
Harvard Chemistry 11 0/11 0.0% 7/11 0.6363636363636364% 0/11 0.0% 242 230/242 0.9504132231404959%
Dartmouth Chemistry 10 1/10 0.1% 8/10 0.8% 1/10 0.1% 203 189/203 0.9310344827586207%
Brown Chemistry 2 0/2 0.0% 2/2 1.0% 0/2 0.0% 50 50/50 1.0%
  • Over the academics these filters select, so a filtered page describes the academics it selected and not the whole department.
  • A row with nothing held draws no mark above: the graph is quiet there because the evidence is missing, not because the work is.
  • What there was to draw from, not what the graph divided by - the graph states its own denominator above.
  • A Scholar profile is attached when at least 3 of the CV titles are found on it, or 30% of them are; one at another institution or under a different name needs 10 titles, and a profile far larger than the CV that holds only a small part of it is refused. Its articles are then checked one by one: what is not a work, or not by this person, is not counted.

Makeup by tenure track

Academics on and off the tenure track
Series: Other.0510152025Brown Other 22Dartmouth Other 1010Columbia Other 1717Cornell Other 2525Harvard Other 1111Penn Other 2020Princeton Other 1212Yale Other 1414BrownDartmouthColumbiaCornellHarvardPennPrincetonYaleAcademicsDepartment

Every academic the filters keep, by whether their current rank is on the tenure track (docs/definitions.md section 7). A rank in neither group - emeritus, postdoc, or a rank no CV states - is its own segment rather than filed under one of them: an emeritus professor was on the tenure track, and an unknown rank is not a claim about tenure at all.

What these filters select, per department not what the graph divided by
Department Academics CVScholarOpenAlex Works With a count
Cornell Chemistry 25 0/25 0.0% 12/25 0.48% 0/25 0.0% 305 282/305 0.9245901639344263%
Penn Chemistry 20 0/20 0.0% 13/20 0.65% 0/20 0.0% 380 363/380 0.9552631578947368%
Columbia Chemistry 17 0/17 0.0% 9/17 0.5294117647058824% 0/17 0.0% 339 308/339 0.9085545722713865%
Yale Chemistry 14 1/14 0.07142857142857142% 9/14 0.6428571428571429% 1/14 0.07142857142857142% 297 260/297 0.8754208754208754%
Princeton Chemistry 12 0/12 0.0% 6/12 0.5% 0/12 0.0% 161 157/161 0.9751552795031055%
Harvard Chemistry 11 0/11 0.0% 7/11 0.6363636363636364% 0/11 0.0% 242 230/242 0.9504132231404959%
Dartmouth Chemistry 10 1/10 0.1% 8/10 0.8% 1/10 0.1% 203 189/203 0.9310344827586207%
Brown Chemistry 2 0/2 0.0% 2/2 1.0% 0/2 0.0% 50 50/50 1.0%
  • Over the academics these filters select, so a filtered page describes the academics it selected and not the whole department.
  • A row with nothing held draws no mark above: the graph is quiet there because the evidence is missing, not because the work is.
  • What there was to draw from, not what the graph divided by - the graph states its own denominator above.
  • A Scholar profile is attached when at least 3 of the CV titles are found on it, or 30% of them are; one at another institution or under a different name needs 10 titles, and a profile far larger than the CV that holds only a small part of it is refused. Its articles are then checked one by one: what is not a work, or not by this person, is not counted.

Output by rank

Median citations per academic at each rank
Value Measure
Series: Brown Chemistry, Dartmouth Chemistry, Columbia Chemistry, Cornell Chemistry, Harvard Chemistry, Penn Chemistry, Princeton Chemistry, Yale Chemistry.0.0500.01,000.01,500.02,000.02,500.0Unknown Brown Chemistry over 2 academics 2,086.52,086.5Unknown Dartmouth Chemistry over 10 academics 312.5312.5Unknown Columbia Chemistry over 17 academics 517.0517.0Unknown Cornell Chemistry over 25 academics 0.00.0Unknown Harvard Chemistry over 11 academics 1,102.01,102.0Unknown Penn Chemistry over 20 academics 1,279.01,279.0Unknown Princeton Chemistry over 12 academics 102.0102.0Unknown Yale Chemistry over 13 academics 864.0864.0Other Yale Chemistry over 1 academics 1,605.01,605.0UnknownOtherMedian citations per academicRank

Brown ChemistryDartmouth ChemistryColumbia ChemistryCornell ChemistryHarvard ChemistryPenn ChemistryPrinceton ChemistryYale Chemistry

Each rank read on its own, so a department of thirty and one of sixty are comparable at the same career stage.

What these filters select, per department not what the graph divided by
Department Academics CVScholarOpenAlex Works With a count
Cornell Chemistry 25 0/25 0.0% 12/25 0.48% 0/25 0.0% 305 282/305 0.9245901639344263%
Penn Chemistry 20 0/20 0.0% 13/20 0.65% 0/20 0.0% 380 363/380 0.9552631578947368%
Columbia Chemistry 17 0/17 0.0% 9/17 0.5294117647058824% 0/17 0.0% 339 308/339 0.9085545722713865%
Yale Chemistry 14 1/14 0.07142857142857142% 9/14 0.6428571428571429% 1/14 0.07142857142857142% 297 260/297 0.8754208754208754%
Princeton Chemistry 12 0/12 0.0% 6/12 0.5% 0/12 0.0% 161 157/161 0.9751552795031055%
Harvard Chemistry 11 0/11 0.0% 7/11 0.6363636363636364% 0/11 0.0% 242 230/242 0.9504132231404959%
Dartmouth Chemistry 10 1/10 0.1% 8/10 0.8% 1/10 0.1% 203 189/203 0.9310344827586207%
Brown Chemistry 2 0/2 0.0% 2/2 1.0% 0/2 0.0% 50 50/50 1.0%
  • Over the academics these filters select, so a filtered page describes the academics it selected and not the whole department.
  • A row with nothing held draws no mark above: the graph is quiet there because the evidence is missing, not because the work is.
  • What there was to draw from, not what the graph divided by - the graph states its own denominator above.
  • A Scholar profile is attached when at least 3 of the CV titles are found on it, or 30% of them are; one at another institution or under a different name needs 10 titles, and a profile far larger than the CV that holds only a small part of it is refused. Its articles are then checked one by one: what is not a work, or not by this person, is not counted.

Academics ranked against academics

Each department's rank-n academic, citations
Value Ranks
Series: Brown Chemistry, Dartmouth Chemistry, Columbia Chemistry, Cornell Chemistry, Harvard Chemistry, Penn Chemistry, Princeton Chemistry, Yale Chemistry.05000100001500020000250001 Brown Chemistry Ming Xian 39331 Dartmouth Chemistry Katherine A. Mirica 59211 Columbia Chemistry Timothy C Berkelbach 87431 Cornell Chemistry Yao Yang 75031 Harvard Chemistry Joonho Lee 113581 Penn Chemistry Andrew M. Rappe 66401 Princeton Chemistry Roberto Car 235511 Yale Chemistry Hailiang Wang 75112 Brown Chemistry Matthew Coley-O'Rourke 2402 Dartmouth Chemistry Miguel I. Gonzalez 42242 Columbia Chemistry Xavier Roy 83922 Cornell Chemistry Frank C. Schroeder 39302 Harvard Chemistry Hongkun Park 104082 Penn Chemistry Kai Chen 34412 Princeton Chemistry Joshua Rabinowitz 154972 Yale Chemistry Gary Brudvig 41573 Dartmouth Chemistry Jane E. G. Lipson 5623 Columbia Chemistry Colin P. Nuckolls 49683 Cornell Chemistry Marissa Lavagnino 22953 Harvard Chemistry Suyang Xu 92563 Penn Chemistry E. James Petersson 32583 Princeton Chemistry David MacMillan 134543 Yale Chemistry James Mayer 39794 Dartmouth Chemistry David S. Glueck 4454 Columbia Chemistry Luis M. Campos 41524 Cornell Chemistry Jeremy M. Baskin 15704 Harvard Chemistry Richard Y. Liu 27914 Penn Chemistry Eric J. Schelter 30144 Princeton Chemistry Christopher J. Chang 78254 Yale Chemistry Sarah Slavoff 36895 Dartmouth Chemistry Michael J. Ragusa 3165 Columbia Chemistry Neel H. Shah 15605 Cornell Chemistry Peng Chen 14305 Harvard Chemistry Eugene I. Shakhnovich 18445 Penn Chemistry David W. Christianson 26375 Princeton Chemistry Leslie Schoop 47705 Yale Chemistry Tianyu Zhu 299812345CitationsRank

Brown ChemistryDartmouth ChemistryColumbia ChemistryCornell ChemistryHarvard ChemistryPenn ChemistryPrinceton ChemistryYale Chemistry

Rank 5 of 25 at the deepest; 7 of 8 departments still have somebody at the last rank drawn. Rank n of one department is not otherwise related to rank n of another - what this compares is the shape of the lists.

What these filters select, per academic not what the graph divided by
Academic Academics CVScholarOpenAlex Works With a count
Amymarie Bartholomew 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Andrew Musser 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Andrew Myers 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Brett P. Fors 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Brian Crane 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Bruce Ganem 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 0 —
Christopher B. Murray 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Dalibor Sames 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Dan Kahne 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Daniel G. Nocera 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Daniel J. Mindiola 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
David B. Collum 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
David B. Zax 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
David R. Reichman 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Ekaterina V. Pletneva 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Erik J. Sorensen 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Geoffrey W. Coates 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Gerard Parkin 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
H. Floyd Davis 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Haw Yang 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Héctor D. Abruña 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
J. Patrick Loria 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Jack R. Norton 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
James J. Valentini 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
James L. Leighton 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Jannette Carey 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Jeffery G. Saven 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Karen I. Goldberg 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Kurt Zilm 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Mahima Sneha 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Marisa C. Kozlowski 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Matthew Shair 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Melissa A. Hines 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Michelle Chang 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Milan E. Delor 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Mircea Dincă 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Mohammad R. Seyedsayamdost 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Patrick Vaccaro 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Peter T. Wolczanski 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Richard A. Cerione 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Scott Miller 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Stephen Lee 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Thomas E. Mallouk 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Wei Min 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Youn Jue (Eunice) Bae 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Yuting Zhou 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Alice Kunin 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 13 9/13 0.6923076923076923%
Andrew M. Rappe 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 21 21/21 1.0%
Andrew Zahrt 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 19 18/19 0.9473684210526315%
Angelo Cacciuto 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 31 24/31 0.7741935483870968%
Ann E. McDermott 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 8 8/8 1.0%
Brian Liau 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 43 32/43 0.7441860465116279%
Caitlin Davis 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 59 30/59 0.5084745762711864%
Christopher J. Chang 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 18 18/18 1.0%
Colin P. Nuckolls 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 19 19/19 1.0%
Dale F. Mierke 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 2 2/2 1.0%
David M. Chenoweth 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 53 53/53 1.0%
David MacMillan 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 24 24/24 1.0%
David S. Glueck 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 16 16/16 1.0%
David W. Christianson 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 8 8/8 1.0%
Dean E. Wilcox 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 15 8/15 0.5333333333333333%
E. James Petersson 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 60 60/60 1.0%
Elizabeth Rhoades 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 32 32/32 1.0%
Eric Arsenault 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 28 25/28 0.8928571428571429%
Eric Heller 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 1 1/1 1.0%
Eric J. Schelter 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 30 30/30 1.0%
Erik Thiede 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 26 23/26 0.8846153846153846%
Eugene I. Shakhnovich 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 7 7/7 1.0%
Frank C. Schroeder 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 21 21/21 1.0%
Gary Brudvig 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 14 14/14 1.0%
Gregory Sion Ezra 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 3 3/3 1.0%
Hailiang Wang 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 27 27/27 1.0%
Hongkun Park 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 32 32/32 1.0%
Jaehyeok Jin 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 33 29/33 0.8787878787878788%
James Mayer 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 21 21/21 1.0%
Jane E. G. Lipson 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 23 23/23 1.0%
Jason M. Crawford 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 58 58/58 1.0%
Jeremy M. Baskin 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 57 57/57 1.0%
John A. Marohn 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 20 14/20 0.7%
Jonathan A. Kephart 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 14 12/14 0.8571428571428571%
Joonho Lee 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 88 88/88 1.0%
Joshua Rabinowitz 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 25 25/25 1.0%
Kai Chen 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 23 22/23 0.9565217391304348%
Katherine A. Mirica 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 59 59/59 1.0%
Laura J. Kaufman 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 48 32/48 0.6666666666666666%
Leslie Schoop 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 63 63/63 1.0%
Luis M. Campos 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 40 40/40 1.0%
Marissa Lavagnino 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 7 7/7 1.0%
Marsha I. Lester 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 21 21/21 1.0%
Matthew Coley-O'Rourke 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 11 11/11 1.0%
Michael J. Ragusa 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 26 22/26 0.8461538461538461%
Miguel I. Gonzalez 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 47 44/47 0.9361702127659575%
Ming Xian 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 39 39/39 1.0%
Nandini Ananth 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 27 22/27 0.8148148148148148%
Neel H. Shah 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 29 26/29 0.896551724137931%
Neil C. Tomson 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 38 27/38 0.7105263157894737%
Pamela Chang 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 19 16/19 0.8421052631578947%
Peng Chen 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 37 37/37 1.0%
Richard Y. Liu 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 41 40/41 0.975609756097561%
Roberto Car 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 18 18/18 1.0%
Ruben L Gonzalez Jr 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 28 23/28 0.8214285714285714%
Sarah Slavoff 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 29 29/29 1.0%
Squire J. Booker 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 29 29/29 1.0%
Suyang Xu 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 30 30/30 1.0%
Tianyu Zhu 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 33 32/33 0.9696969696969697%
Timothy C Berkelbach 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 72 72/72 1.0%
Tobias Baumgart 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 33 33/33 1.0%
Xavier Roy 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 76 76/76 1.0%
Xin Qi 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 16 16/16 1.0%
Yao Yang 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 78 74/78 0.9487179487179487%
Yifan Quan 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 25 21/25 0.84%
  • Over the academics these filters select, so a filtered page describes the academics it selected and not the whole department.
  • A row with nothing held draws no mark above: the graph is quiet there because the evidence is missing, not because the work is.
  • What there was to draw from, not what the graph divided by - the graph states its own denominator above.
  • A Scholar profile is attached when at least 3 of the CV titles are found on it, or 30% of them are; one at another institution or under a different name needs 10 titles, and a profile far larger than the CV that holds only a small part of it is refused. Its articles are then checked one by one: what is not a work, or not by this person, is not counted.

Journals used

Where these departments place work, by works
Value
Series: value.Journal of the American Chemical SocietyJournal of the American Chemical Society 191191The Journal of Chemical PhysicsThe Journal of Chemical Physics 103103NatureNature 7474Nature CommunicationsNature Communications 6666Proceedings of the National Academy of SciencesProceedings of the National Academy of Sciences 5656Chemical ScienceChemical Science 4343Journal of Chemical Theory and ComputationJournal of Chemical Theory and Computation 4343ScienceScience 3737Nano LettersNano Letters 3535bioRxiv (Cold Spring Harbor Laboratory)bioRxiv (Cold Spring Harbor Laboratory) 3333Physical Review LettersPhysical Review Letters 3030Biophysical JournalBiophysical Journal 3030Physical Review BPhysical Review B 2727Nature ChemistryNature Chemistry 2626Angewandte Chemie International EditionAngewandte Chemie International Edition 2626050100150JournalWorks

The twelve venues highest on this reading, of 274.

What these filters select, per department not what the graph divided by
Department Academics CVScholarOpenAlex Works With a count
Cornell Chemistry 25 0/25 0.0% 12/25 0.48% 0/25 0.0% 305 282/305 0.9245901639344263%
Penn Chemistry 20 0/20 0.0% 13/20 0.65% 0/20 0.0% 380 363/380 0.9552631578947368%
Columbia Chemistry 17 0/17 0.0% 9/17 0.5294117647058824% 0/17 0.0% 339 308/339 0.9085545722713865%
Yale Chemistry 14 1/14 0.07142857142857142% 9/14 0.6428571428571429% 1/14 0.07142857142857142% 297 260/297 0.8754208754208754%
Princeton Chemistry 12 0/12 0.0% 6/12 0.5% 0/12 0.0% 161 157/161 0.9751552795031055%
Harvard Chemistry 11 0/11 0.0% 7/11 0.6363636363636364% 0/11 0.0% 242 230/242 0.9504132231404959%
Dartmouth Chemistry 10 1/10 0.1% 8/10 0.8% 1/10 0.1% 203 189/203 0.9310344827586207%
Brown Chemistry 2 0/2 0.0% 2/2 1.0% 0/2 0.0% 50 50/50 1.0%
  • Over the academics these filters select, so a filtered page describes the academics it selected and not the whole department.
  • A row with nothing held draws no mark above: the graph is quiet there because the evidence is missing, not because the work is.
  • What there was to draw from, not what the graph divided by - the graph states its own denominator above.
  • A Scholar profile is attached when at least 3 of the CV titles are found on it, or 30% of them are; one at another institution or under a different name needs 10 titles, and a profile far larger than the CV that holds only a small part of it is refused. Its articles are then checked one by one: what is not a work, or not by this person, is not counted.