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Young Leader Conference

Young Leader Conference (YLC) Session is open to young scientists who would like to share and discuss their research achievement. Young Scientists are carefully chosen and recommended by our technical program committee for this session. The speakers in YLC session should have the strong background in the display-related fields such as active-matrix devices, liquid crystal, OLED, 3D etc.

This year, Young Leaders Conference is planned 1-2 sessions, with 2-4 young scientists recommended by Korea giving online presentations and 3-6 young scientists recommended by China giving on-site presentations.

Due to COVID-19, Young Leader Conference has dual format, on-site conference for Chinese speaker and online format for Korean speaker. As for online conference, Korean speakers need to pre-record the presentation. ICDT organization will   broadcast   presentation video to all the audiences and hope online speakers can join in the real-time online conference to discuss with others.

Program (July 18)




Present Occupation


13:30-13:50YIFAN (EVAN) PENGNext-generation Cameras and Displays Incorporating Optics and Machine Intelligence

Postdoc Scholar

Stanford University

13:50-14:10Dong Hae Ho3D-Printed Sugar Scaffold for High-Precision and Highly-sensitive Active and Passive Wearable Sensors


Yonsei University

14:10-14:30Yongming YinInvestigation on the crosstalk effect of color-converted micro-LED display

Assistant Research Fellow

School of Advanced Materials, Shenzhen Graduate School, Peking University

14:30-14:50XIA ZhiheElevated-Metal Metal-Oxide Thin-Film Transistor for Information Display and Flexible Electronics

Research assistant professor

The Hong Kong University of Science and Technology

14:50-15:10Seongchan KimArtificial Stimuli-Response System Capable of Conscious Response


SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University

15:10-15:30Haizeng LiEmerging Zn Anode-Based Electrochromic Devices


Shandong University


Next-generation Cameras and Displays Incorporating Optics and Machine Intelligence

Yifan Peng.png


Postdoc Scholar

The University of Hong Kong and Stanford University

From cameras to displays, visual computing systems are becoming ubiquitous in our daily life. However, their underlying design principles have stagnated after decades of evolution. Existing imaging devices require dedicated hardware that is not only complex and bulky, but also exhibits only suboptimal results in certain visual computing scenarios. This shortcoming is due to a lack of joint design between hardware and software, importantly, impeding the delivery of vivid 3D visual experience of displays. By bridging advances in computer science and optics with extensive machine intelligence strategies, my work engineers physically compact, yet functionally powerful imaging solutions of cameras and displays for applications in photography, wearable computing, IoT products, autonomous driving, medical imaging, and VR/AR/MR.

In this talk, I will describe two classes of computational imaging modalities. Firstly, in Deep Optics, we jointly optimize lightweight diffractive optics and differentiable image processing algorithms to enable high-fidelity imaging in domain-specific cameras. Additionally, I will discuss Neural Holography, which also applies the unique combination of machine intelligence and physics to solve long-standing problems of computer-generated holography. Specifically, I will describe several holographic display architectures that leverage the advantages of camera-in-the-loop optimization and neural network model representation to deliver full-color, high-quality holographic images. Driven by trending machine intelligence, these hardware-software jointly optimized imaging solutions can unlock the full potential of traditional cameras and displays and enable next-generation visual computing systems.

Yifan (Evan) Peng is a Postdoctoral Research Fellow at Stanford University in Computational Imaging Lab. His research interest rides across the interdisciplinary fields of optics/photonics, computer graphics, computer vision, and AI. Much of his recent work concerns developing visual computing modalities combining optics and machine intelligence, for both cameras and displays. His recent achievements in Deep Optics and Neural Holography have received numerous attention and consultation from both academia and industry. He completed his Ph.D. in Computer Science at the University of British Columbia, and his M.Sc. and B.Eng. in Optical Science and Engineering at Zhejiang University. During the Ph.D. career, he was also a Visiting Research Student at Stanford Computational Imaging Lab and Visual Computing Center, King Abdullah University of Science and Technology. He has been serving multiple professional roles in IEEE ISMAR, IEEE ICCP, SPIE ARVRMR, SPIE Photonics Asia, and SID Display Week.

Website: http://stanford.edu/~evanpeng/

3D-Printed Sugar Scaffold for High-Precision and Highly-sensitive Active and Passive Wearable Sensors

Dong Hae Ho

Yonsei University

In this study, a pairing of a previously unidentified 3D printing technique and soft materials is introduced in order to achieve not only high-resolution printed features and flexibility of the 3D-printed materials, but also its light-weight and electrical conductivity. Using the developed technique and materials, high-precision and highly sensitive patient-specific wearable active or passive devices are fabricated for personalized health monitoring. The fabricated biosensors show low density and substantial flexibility because of 3D microcellular network-type interconnected conductive materials that are readily printed using an inkjet head. Using high-resolution 3D scanned body-shape data, on-demand personalized wearable sensors made of the 3D-printed soft and conductive materials are fabricated. These sensors successfully detect both actively changing body strain signals and passively changing signals such as electromyography (EMG), electrodermal activity (EDA), and electroencephalogram EEG. The accurately tailored subject-specific shape of the developed sensors exhibits higher sensitivity and faster real-time sensing performances in the monitoring of rapidly changing human body signals. The newly developed 3D printing technique and materials can be widely applied to various types of wearable, flexible, and light-weight biosensors for use in a variety of inexpensive on-demand and personalized point-of-care diagnostics.

Dong Hae Ho hold a B.S. in Chemical Engineering from Sungkyunkwan University (SKKU) and an M.S./Ph.D. degree in Nanoscience & Nanotechnology from SKKU Advanced Institute of Nanotechnology (SAINT). Since 2014, I have studied the various types of fiber-based wearable devices using nanomaterials. Research interest is not only the detection of the signal from the human, but 3D printing technique for wearable devices, and 2D materials themselves. Moreover, I did the research on soft electronics based on the elastomer and liquid metal that can detect the biosignal. Currently, I have been working as a postdoctoral researcher in the Department of Chemical and Biomolecular Engineering at Yonsei University since I got my Ph.D. degree in 2020.

Investigation on the crosstalk effect of color-converted micro-LED display


Yongming Yin

Assistant Research Fellow

School of Advanced Materials, Shenzhen Graduate School, Peking University

As for fabricating high gamut color-converted micro-light-emitting diodes (LEDs) displays, serious crosstalk effect among adjacent pixels because of the wide view-angle feature of micro-LED chips is one of the major challenges. Herein, potential factors that contribute to the crosstalk effect are systematically simulated and it is learnt that precisely filling the space among each micro-LED chip with light blocking matrix (LBM) could be a promising solution to alleviate this risk. After careful investigations, press-assisted molding technique was demonstrated to be an effective approach to fabricate the LBM. Nevertheless, experimental observations further revealed that residual black LBM on the surface of micro-LEDs severely reduces the brightness, thereby compromising the display performance. This issue is successfully addressed by employing plasma etching technique which helped to efficiently extract the trapped light. Eventually, a top-emitting blue micro-LEDs-based backlight fine-molded with black LBM is developed and combined with red and green quantum dot color conversion layers for full-color display. The color gamut of our manufactured display prototype can cover as high as 122% of the National Television Standards Committee (NTSC).

Yongming Yin received his PhD degree under the supervision of Professor Hong Meng from Peking University in 2020. From 2015 to 2021, he worked for TCL CSOT as panel designer, where he successfully developed 3 TFT-LCD products and 4 Mini/Micro-LED prototypes. Currently, he is a Research Fellow at the School of Advanced Materials, Peking University Shenzhen Graduate School. His research focuses on luminescent materials synthesis, characterization, devices and display application with over 30 peer-reviewed papers and 8 Chinese patents.

Elevated-Metal Metal-Oxide Thin-Film Transistor for Information Display and Flexible Electronics


XIA Zhihe

Research assistant professor

The Hong Kong University of Science and Technology

金属氧化物半导体作为有源驱动器件材料,由于其迁移率高,关态电流低,柔性透明且工艺温度低等优点,近年来一直被广为关注。在特定热退火温度下,金属氧化物半导体的电阻率取决于边界材料和气氛环境。源于金属氧化物半导体的这一特性,内嵌热致源漏的升金型金属氧化物(EMMO)薄膜晶体管(TFT)得以实现。EMMO TFT具有尺寸面积小,寄生电容低,沟道保护佳等优点。在本次报告中,将介绍EMMO TFT为满足当前显示趋势的要求,在技术和结构的最新改进和进展,展现其对主流显示技术(LC、OLED和Micro-LED)的像素驱动支持。同时也将介绍柔性EMMO TFT器件的相关工作与相关集成应用系统。

夏之荷博士,本科毕业于华中科技大学,获光电信息工程学士。于2019年获香港科技大学电子及计算机工程博士学位,同年入选香港创新及科技基金“研究人才库”计划,在香港科技大学先进显示与光电子技术国家重点实验室担任副研究员。现为香港科技大学研究助理教授。他多年来一直从事金属氧化物半导体与薄膜晶体管方面的研究工作,在微电子和显示领域的高水平国际期刊和会议上发表论文三十余篇, 参与撰写氧化物半导体著作1部,参与并共同主持多项粤港联合研究项目。目前他的研究方向为低温高性能薄膜晶体管在信息显示和柔性电子的应用及系统集成。

Artificial Stimuli-Response System Capable of Conscious Response


Seongchan Kim

SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University,

Stimulus-response system and conscious response enable humans to respond effectively to environmental changes and external stimuli. Inspired by human conscious response, this paper presents an artificial stimulus-response system capable of conscious response. The system is composed of an artificial visual receptor, artificial synapse, artificial neuron circuit, and an actuator. Vertically stacked graphene/semiconductor heterostructure is employed as a base layer for the artificial visual receptor and artificial synapse to allow high integration density. The artificial visual receptor with InP quantum dot layer generates the electrical pulse under light illumination. The artificial synapse with retentive electric double layer processes the electrical pulse signals to strengthen synaptic connections. The artificial neuron circuit is designed with CMOS circuit which integrates synaptic output signal to activate the actuator. By incorporating these artificial nervous components, a series of conscious response process is demonstrated which drastically reduces response time as a result of learning from repeated stimuli. The demonstrated artificial stimulus-response system offers a promising research field providing an alternative to patients with neurological disorders.

Seongchan Kim's research interest is to develop noble stimulus-response system based on the artificial synapse with various sensors and actuators. I believe the collaboration of artificial synapse and sensors which enables perception of external stimuli will make the stimulus-response system as a keystone for next-generation prosthesis.

Research Keywords:

Bio-Inspired Electronics, Artificial Nervous System, Artificial Synapse, Vertically Stacked Device

Representative Research Skills & Knowledge:

I) Fabrication of various electronic devices such as transistor, photo-detector, artificial synapse.

II) Having experience in fabrication of vertically stacked electronics devices.

III) Analyzing electrical characteristics of the devices and proving out of relating charge transport mechanism.

Current Research Interests:

I) Fabrication of artificial stimulus-response system based on the artificial synapse.

II) Design the new concept of bio-inspired electronics such as artificial neuron and artificial sensory receptor.

Emerging Zn Anode-Based Electrochromic Devices

haizneg li.jpg

Haizeng Li


Shandong University

The development of electrochromic materials has opened the door to the development of numerous devices including smart windows, color displays, optical filters, wearable camouflages, among others. Although the current electrochromic devices do not consume energy while maintaining their colored or colorless states, their bistable operation requires external electrical energy to be consumed during switching. To reduce the energy consumption of an electrochromic device, an emerging Zn anode-based electrochromic device concept was recently introduced to partially retrieve the consumed electrical energy. In this talk, key technological developments and scientific challenges will be presented for a broad range of Zn anode-based electrochromic device configurations with emphasis on the inherent distinctions between the Zn anode-based and conventional electrochromic devices.

Haizeng Li obtained his Ph.D. degree in 2016 from the State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, China. He then started his postdoctoral research with Prof. Abdulhakem Y. Elezzabi at the University of Alberta, Canada. After that, he joined Shandong University as a full professor at the Institute of Frontier and Interdisciplinary Science, and the School of Energy and Power Engineering. His current research interests include electrochromic devices, wearable electronics, energy storage, and radiative heat transfer.
















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