Sham M Kakade

Sham M Kakade is a researcher affiliated with Harvard University, specializing in AI & Machine Learning. Their work has been cited 49,807 times. This profile visualizes their global influence, highlighting strong citation networks in DE.

AI & Machine Learning

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0i10-index

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0Works

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Harvard University•

Google Scholar

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Sham M Kakade's Citation Metrics

Bibliometric impact based on 1 indexed publication.

H-Index: 1
i10-Index: 1
Total Citations: 49,807
Citing Countries: 2

As of April 2026.

Sham M Kakade has an h-index of 1 and 49,807 total citations across 1 publication, with research cited by institutions in 2 countries.

Global Impact Map

Visualizing the geographic distribution of institutions that have cited your work.

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Top Citing Countries(Limited)

Germany(DE)

Canada(CA)

Top Citing Institutions(Limited)

LMU Munich

Leibniz University Hannover

TU Dortmund University

University of Oxford

University of Toronto

University of British Columbia

Visa Evidence Package

Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.

Citer Influence Network

Visa-ready visualisation: each outer ring node is a country citing this scholar. Node size & edge weight scale with citing-paper count. Showing top 3 of 3 countries (15 total citations).

Scholar

Sham M Kakade

153

Germany

Canada

U.K.

React Flow

Letter of Support — Candidate Recommenders

Ranked by EB-1A / O-1A relevance: independence from your home institution, affiliation with a top-ranked institution, repeat citations of your work, and recency. Reach out to the highest-scoring candidates to request support letters.

#1
Bernd Bischl
7.0
LMU Munich
Germany· Cited your work 1 time
IndependentTop institution
#2
Martin Binder
7.0
LMU Munich
Germany· Cited your work 1 time
IndependentTop institution
#3
Bobak Shahriari
8.5
University of British Columbia
Canada· Cited your work 1 time
IndependentTop institutionDiversifies geography
#4
Ziyu Wang
8.5
University of Oxford
U.K.· Cited your work 1 time
IndependentTop institutionDiversifies geography
#5
Kevin Swersky
8.5
University of Toronto
Canada· Cited your work 1 time
IndependentTop institutionDiversifies geography
#6
Tobias Pielok
7.0
LMU Munich
Germany· Cited your work 1 time
IndependentTop institution
#7
Stefan Coors
7.0
LMU Munich
Germany· Cited your work 1 time
IndependentTop institution
#8
Janek Thomas
7.0
LMU Munich
Germany· Cited your work 1 time
IndependentTop institution
#9
Theresa Ullmann
7.0
LMU Munich
Germany· Cited your work 1 time
IndependentTop institution
#10
Marc Becker
7.0
LMU Munich
Germany· Cited your work 1 time
IndependentTop institution

Scores combine 5 signals: independence (+3), prestige institution (+2), repeat citations (+2 per paper, cap 5), recent activity (+1), and geography diversity (+1.5). Identity matching uses name + institution; namesakes at the same org are merged.