D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 38 Citations 6,002 200 World Ranking 2804 National Ranking 29

Overview

What is he best known for?

The fields of study he is best known for:

  • Electrical engineering
  • Optics
  • Computer network

His primary areas of study are Signal, Display device, Electrical engineering, Liquid-crystal display and Voltage. As a member of one scientific family, Joo-hyung Lee mostly works in the field of Signal, focusing on Electronic engineering and, on occasion, Image signal and Image. Joo-hyung Lee interconnects Computer hardware, Digital signal processor and Pixel, Computer vision, Artificial intelligence in the investigation of issues within Display device.

His Electrical engineering research is multidisciplinary, incorporating perspectives in Light sensing and Capacitance. His Liquid-crystal display study improves the overall literature in Optoelectronics. Joo-hyung Lee works mostly in the field of Voltage, limiting it down to topics relating to Current and, in certain cases, Diode, as a part of the same area of interest.

His most cited work include:

  • Display screen portion with icon (261 citations)
  • Time-of-flight measurement with femtosecond light pulses (255 citations)
  • A robust superhydrophobic and superoleophobic surface with inverse-trapezoidal microstructures on a large transparent flexible substrate (247 citations)

What are the main themes of his work throughout his whole career to date?

Joo-hyung Lee spends much of his time researching Display device, Optoelectronics, Signal, Optics and Artificial intelligence. His Display device study combines topics in areas such as Luminance, Computer hardware, Digital signal processor, Pixel and Voltage. His Optoelectronics research is mostly focused on the topic Liquid-crystal display.

The various areas that Joo-hyung Lee examines in his Liquid-crystal display study include Capacitance, Capacitor and Liquid crystal. His Signal research is included under the broader classification of Electrical engineering. His work investigates the relationship between Artificial intelligence and topics such as Computer vision that intersect with problems in Computer graphics.

He most often published in these fields:

  • Display device (23.35%)
  • Optoelectronics (20.30%)
  • Signal (16.24%)

What were the highlights of his more recent work (between 2016-2021)?

  • Computer network (11.42%)
  • Communications system (4.82%)
  • Artificial intelligence (14.97%)

In recent papers he was focusing on the following fields of study:

His primary scientific interests are in Computer network, Communications system, Artificial intelligence, Distributed computing and Base station. His study in the fields of Network congestion under the domain of Computer network overlaps with other disciplines such as Streaming current. His studies in Artificial intelligence integrate themes in fields like Treatment options, Computer vision and Pattern recognition.

The Rendering and Pixel research Joo-hyung Lee does as part of his general Computer vision study is frequently linked to other disciplines of science, such as Memory footprint, therefore creating a link between diverse domains of science. His work carried out in the field of Distributed computing brings together such families of science as Energy consumption, Scheduling, Efficient energy use and Server. His Transmission research is multidisciplinary, incorporating perspectives in Node, Wired communication and Signal.

Between 2016 and 2021, his most popular works were:

  • Deep Learning Based Pilot Allocation Scheme (DL-PAS) for 5G Massive MIMO System (53 citations)
  • Event-Driven Energy Trading System in Microgrids: Aperiodic Market Model Analysis With a Game Theoretic Approach (26 citations)
  • Magnetic Resonance-Based Texture Analysis Differentiating KRAS Mutation Status in Rectal Cancer. (22 citations)

In his most recent research, the most cited papers focused on:

  • Electrical engineering
  • Computer network
  • Optics

Joo-hyung Lee mostly deals with Server, Stackelberg competition, Microgrid, Electricity generation and Computer network. His Server study incorporates themes from Energy consumption, Computation offloading, Efficient energy use and Distributed computing. As part of the same scientific family, Joo-hyung Lee usually focuses on Microgrid, concentrating on Smart grid and intersecting with Simulation, Stability, Energy trading and Energy independence.

His Computer network study combines topics from a wide range of disciplines, such as Signal and Smart city. The various areas that Joo-hyung Lee examines in his Cellular network study include Deep learning and Artificial intelligence. His research integrates issues of Cancer and Pattern recognition in his study of Artificial intelligence.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Display screen portion with icon

Hye-Bin Park;You-Jin Im;Sora Kim;Joo-hyung Lee.
(2013)

403 Citations

Time-of-flight measurement with femtosecond light pulses

Joohyung Lee;Young-Jin Kim;Keunwoo Lee;Sanghyun Lee.
Nature Photonics (2010)

354 Citations

A robust superhydrophobic and superoleophobic surface with inverse-trapezoidal microstructures on a large transparent flexible substrate

Maesoon Im;Hown Im;Joo Hyung Lee;Jun Bo Yoon.
Soft Matter (2010)

323 Citations

Distributed Energy Trading in Microgrids: A Game-Theoretic Model and Its Equilibrium Analysis

Joohyung Lee;Jun Guo;Jun Kyun Choi;Moshe Zukerman.
IEEE Transactions on Industrial Electronics (2015)

279 Citations

Touch sensible display device

Joo-hyung Lee;Hyung-Guel Kim;Kee-han Uh;Sang-Jin Pak.
(2005)

277 Citations

Shift register, display device having the same and method of driving the same

Sang-Jin Pak;Joo-hyung Lee;Hyung-Guel Kim;Myung-Woo Lee.
(2005)

223 Citations

Liquid crystal display and method of driving the same

Joo-hyung Lee;Sang-Jin Pak;Young-Ok Cha.
(2009)

216 Citations

Liquid crystal display with integrated touch screen panel

Seung-Kyu Lee;Jin-woo Park;Dong-Hoon Lee;Chul-Ho Kim.
(2011)

194 Citations

Liquid crystal display device including sensing element

Joo-hyung Lee;Kee-han Uh;Jong-Woung Park;Sang-jin Park.
(2005)

188 Citations

Development of Single-Stranded DNA Aptamers for Specific Bisphenol A Detection

Minjoung Jo;Ji-Young Ahn;Joohyung Lee;Seram Lee.
Oligonucleotides (2011)

181 Citations

Best Scientists Citing Joohyung Lee

Shunpei Yamazaki

Shunpei Yamazaki

Semiconductor Energy Laboratory (Japan)

Publications: 33

Seung-Woo Kim

Seung-Woo Kim

Korea Advanced Institute of Science and Technology

Publications: 27

Lei Jiang

Lei Jiang

Chinese Academy of Sciences

Publications: 25

james d bennett

james d bennett

Broadcom (United States)

Publications: 18

Jeyhan Karaoguz

Jeyhan Karaoguz

Broadcom (United States)

Publications: 18

Steven Porter Hotelling

Steven Porter Hotelling

Apple (United States)

Publications: 14

Imran Chaudhri

Imran Chaudhri

Apple (United States)

Publications: 14

Christoph Horst Krah

Christoph Horst Krah

Apple (United States)

Publications: 13

Hisashi Ohtani

Hisashi Ohtani

Semiconductor Energy Laboratory (Japan)

Publications: 12

Bharat Bhushan

Bharat Bhushan

The Ohio State University

Publications: 12

Seung-Eon Ahn

Seung-Eon Ahn

Korea Polytechnic University

Publications: 11

Stephen O. Lemay

Stephen O. Lemay

Apple (United States)

Publications: 11

Zhiguang Guo

Zhiguang Guo

Hubei University

Publications: 11

Sang Ouk Kim

Sang Ouk Kim

Korea Advanced Institute of Science and Technology

Publications: 11

Jun-Bo Yoon

Jun-Bo Yoon

Korea Advanced Institute of Science and Technology

Publications: 10

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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