Brian Kulis publications per year

The chart shows the history of publications by Brian Kulis between 2003 and 2026, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Brian Kulis published across 24 years, from 2003 to 2026, averaging 3.7 papers a year. Output peaked at 8 publications in 2020. 2 of the 88 publications appeared in the last two years.

No. of publications

2 4 6 8

2003 2026

88 publications in total across all disciplines

View publications per year as a table

Brian Kulis: publications per year, 2003 to 2026
Year	Publications
2003	1
2004	2
2005	1
2006	1
2007	4
2008	3
2009	6
2010	5
2011	2
2012	5
2013	5
2014	1
2015	4
2016	4
2017	1
2018	4
2019	5
2020	8
2021	8
2022	4
2023	5
2024	7
2025	1
2026	1
Total	88

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Brian Kulis publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Brian Kulis sits on this spectrum.

No. of scientists

100 200 300 400

38–47 publications 804+

This scientist: 77 publications — 3rd percentile

3% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

View publications distribution as a table

Number of Engineering and Technology scientists by publication count, Research.com 2026 ranking edition. Based on 9,796 ranked scientists.
Publications	Scientists	This scientist
38–47	20
48–57	35
58–67	96
68–77	135	77
78–87	190
88–97	259
98–107	283
108–117	369
118–127	341
128–137	386
138–147	372
148–157	457
158–167	415
168–177	407
178–187	421
188–197	378
198–207	403
208–217	317
218–227	346
228–237	321
238–247	260
248–257	280
258–267	240
268–277	214
278–287	242
288–297	203
298–307	166
308–317	154
318–327	175
328–337	159
338–347	99
348–357	131
358–367	106
368–377	118
378–387	97
388–397	108
398–407	82
408–417	71
418–427	64
428–437	55
438–447	54
448–457	60
458–467	47
468–477	40
478–487	30
488–497	29
498–507	38
508–517	40
518–527	32
528–537	23
538–547	28
548–557	23
558–567	19
568–577	16
578–587	17
588–597	18
598–607	22
608–617	15
618–627	9
628–637	11
638–647	21
648–657	12
658–667	9
668–677	11
678–687	9
688–697	6
698–707	14
708–717	7
718–727	8
728–737	10
738–747	9
748–757	5
758–767	5
768–777	11
778–787	7
788–797	2
798–803	4
804+	100

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Brian Kulis D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Brian Kulis sits on this spectrum.

No. of scientists

100 200 300 400

30 D-Index 107+

This scientist: 36 D-Index — 13th percentile

13% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

View D-Index distribution as a table

Number of Engineering and Technology scientists by D-index, Research.com 2026 ranking edition. Based on 9,796 ranked scientists.
D-Index	Scientists	This scientist
30	59
31	114
32	129
33	189
34	200
35	262
36	311	36
37	312
38	350
39	385
40	348
41	362
42	426
43	380
44	310
45	341
46	301
47	306
48	271
49	246
50	210
51	253
52	213
53	221
54	195
55	186
56	170
57	167
58	166
59	144
60	152
61	141
62	138
63	131
64	118
65	114
66	119
67	95
68	87
69	77
70	89
71	69
72	54
73	46
74	55
75	54
76	49
77	53
78	46
79	28
80	39
81	36
82	24
83	26
84	36
85	18
86	25
87	19
88	26
89	27
90	23
91	15
92	12
93	9
94	15
95	10
96	13
97	13
98	9
99	7
100	7
101	8
102	7
103	7
104	9
105	6
106	9
107+	99

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Overview

Brian Kulis is affiliated with Boston University in the United States, contributing to research primarily in the field of computer science. Their work encompasses extensive publications across various subfields and topics related to artificial intelligence and signal processing.

The researcher has produced a number of papers focusing on diverse areas of computer science. Notable recent publications include:

Runtime Performance Anomaly Diagnosis in Production HPC Systems Using Active Learning, 2024, IEEE Transactions on Parallel and Distributed Systems
Deep Divergence Learning, 2020, arXiv (Cornell University)
Joint Bilateral Learning for Real-time Universal Photorealistic Style Transfer, 2020, arXiv (Cornell University)
Piecewise Linear Regression via a Difference of Convex Functions, 2020, arXiv (Cornell University)
Real-time Localized Photorealistic Video Style Transfer, 2020, arXiv (Cornell University)

Their frequent coauthors include:

Christopher Liao
Theodoros Tsiligkaridis
Mohammad Omar Khursheed
Christin Jose
Xide Xia

Brian Kulis has published extensively in venues such as:

arXiv (Cornell University)
Zenodo (CERN European Organization for Nuclear Research)
IEEE Transactions on Parallel and Distributed Systems
2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)
Interspeech 2022

Their research is anchored primarily in computer science with a focus on several subfields including:

Computer Vision and Pattern Recognition
Artificial Intelligence
Signal Processing
Computer Networks and Communications
Statistics and Probability

The main topics covered in their work include:

Music and Audio Processing
Generative Adversarial Networks and Image Synthesis
Speech and Audio Processing
Image Enhancement Techniques
Advanced Image Processing Techniques
Anomaly Detection Techniques and Applications
Domain Adaptation and Few-Shot Learning

Best Publications

Adapting visual category models to new domains

Kate Saenko;Brian Kulis;Mario Fritz;Trevor Darrell

3019
Citations
Information-theoretic metric learning

Jason V. Davis;Brian Kulis;Prateek Jain;Suvrit Sra

2662
Citations
Kernel k-means: spectral clustering and normalized cuts

Inderjit S. Dhillon;Yuqiang Guan;Brian Kulis

1623
Citations
Weighted Graph Cuts without Eigenvectors A Multilevel Approach

I.S. Dhillon;Yuqiang Guan;B. Kulis

1269
Citations
Kernelized locality-sensitive hashing for scalable image search

Brian Kulis;Kristen Grauman

1112
Citations
Learning to Hash with Binary Reconstructive Embeddings

Brian Kulis;Trevor Darrell

964
Citations
Metric Learning: A Survey

Brian Kulis

905
Citations
Semi-supervised graph clustering: a kernel approach

Brian Kulis;Sugato Basu;Inderjit Dhillon;Raymond Mooney

881
Citations
What you saw is not what you get: Domain adaptation using asymmetric kernel transforms

Brian Kulis;Kate Saenko;Trevor Darrell

855
Citations
Tracking evolving communities in large linked networks

John Hopcroft;Omar Khan;Brian Kulis;Bart Selman

454
Citations
Kernelized Locality-Sensitive Hashing

B. Kulis;K. Grauman

416
Citations
Fast image search for learned metrics

P. Jain;B. Kulis;K. Grauman

360
Citations
Revisiting k-means: New Algorithms via Bayesian Nonparametrics

Brian Kulis;Michael I. Jordan

346
Citations
Fast Similarity Search for Learned Metrics

B. Kulis;P. Jain;K. Grauman

325
Citations
Low-Rank Kernel Learning with Bregman Matrix Divergences

Brian Kulis;Mátyás A. Sustik;Inderjit S. Dhillon

289
Citations
W-Net: A Deep Model for Fully Unsupervised Image Segmentation

Xide Xia;Brian Kulis

259
Citations
Deep Metric Learning to Rank

Fatih Cakir;Kun He;Xide Xia;Brian Kulis

256
Citations
Online Metric Learning and Fast Similarity Search

Prateek Jain;Brian Kulis;Inderjit S. Dhillon;Kristen Grauman

254
Citations
Learning low-rank kernel matrices

Brian Kulis;Mátyás Sustik;Inderjit Dhillon

242
Citations
Discovering Latent Domains for Multisource Domain Adaptation

Judy Hoffman;Brian Kulis;Trevor Darrell;Kate Saenko

224
Citations