Tutorial (단기강좌)



1. 이명재 박사 (KIST)


"SPAD Sensors: Technology and Applications"




Single-photon avalanche diode (SPAD) sensors have been receiving an enormous amount of attention from scientific and industrial communities because they have a strong impact on next-generation applications such as advanced driver assistance systems (ADAS), autonomous vehicles, service robots and drones, machine vision, AR/VR, etc. with great scientific, economic, and social potential. SPADs are also very useful technology for biomedical and quantum applications, including time-of-flight positron emission tomography (TOF PET), fluorescence-lifetime imaging microscopy (FLIM), super-resolution microscopy, near-infrared imaging or optical tomography (NIRI/NIROT), quantum key distribution (QKD), quantum random number generator (QRNG), quantum cryptography, etc.
SPADs based on CMOS technology are considered as the most suitable solution for most of the applications, because (i) they are capable of detecting very low-intensity signals, down to the single-photon level, as well as provide accurate photon counting and time-of-arrival detection and (ii) CMOS technology promises the most cost-effective and high-volume solution as a universal platform. However, there are still some challenges of using CMOS-SPADs: e.g., poor efficiency at NIR and low fill factor.
This talk will give an overview of SPAD sensors, covering applications that require SPAD sensors, the current state of the technology, and the challenges and requirements needed for CMOS-SPADs to make greater impacts. A brief outlook on the future of the SPAD sensors will conclude the talk.



Myung-Jae Lee received the B.S., M.S., and Ph.D. degrees in electrical and electronic engineering from Yonsei University, Seoul, South Korea, in 2006, 2008, and 2013, respectively. His doctoral dissertation concerned silicon avalanche photodetectors fabricated with standard CMOS/BiCMOS technology. From 2013 to 2017, he was a Postdoctoral Researcher with Delft University of Technology (TU Delft), The Netherlands, where he worked on single-photon sensors and applications based on single-photon avalanche diodes. In 2017, he joined École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, as a Scientist, working on advanced single-photon sensors and applications as well as coordinating and managing several research projects as a Co-Principal Investigator. Since 2019, he has been a Principal Investigator/Senior Research Scientist with Korea Institute of Science and Technology (KIST), South Korea, where he has led the research and development of nextgeneration single-photon detectors and sensors for various applications. His research interests have spanned from photodiodes/photodetectors to single-photon detectors/sensors, concentrating since 2006 on CMOS-compatible avalanche photodetectors and single-photon avalanche diodes as well as applications thereof (e.g., LiDAR, D-ToF, 3D vision, biophotonics, quantum photonics, space, security, silicon photonics, optical interconnects, etc.). He has published over 80 papers in international journals and conferences. He holds 2 patents and has received 11 awards.



2. 노준석 교수 (POSTECH)


"Inverse design and forward modelling in nanophotonics using deep-learning"




Recent introduction of deep learning into nanophotonics has enabled efficient inverse design process [1]. Once the deep learning network is trained, it allows fast inverse design for multiple design tasks. In this talk, we show several inverse designing nanophotonic structures using deep learning [1-9]. We firstly discuss inverse design methods that increase the degree of freedom of design possibilities. These attempts include designing arbitrary shapes of nanophotonic structures, that are not limited to pre-defined structures [2], and designing both types of materials and structural parameters simultaneously [3]. In order to design arbitrary shapes of structures, cross-sectional design images are designed by generative model. Also, for simultaneous design of materials and structural parameters, we developed a novel objective function that combines regression and classification problems. After then, we also discuss optimizing nanophotonic structures using deep learning. We use reinforcement learning to optimize structure parameters. Using reinforcement learning, an agent learns parameter space of an environment through the exploration and exploitation of the reward. After learning, the agent can provide the optimized design parameters from its own experience. Several meta-devices including dielectric color filter [4], high efficiency hologram [5], perfect absorber [6-8], plasmonic structures [9], dielectric gratings [10, 11] and microwave antenna [12] are designed using this method.



Junsuk Rho (鲁埈锡) is currently a Mu-Eun-Jae (无垠斋) endowed Chair Associate Professor with a joint appointment in the Departments of Mechanical Engineering and the Department of Chemical Engineering at Pohang University of Science and Technology (POSTECH), Korea. Before joining POSTECH, he received a degree his B.S. (2007) and M.S. (2008) in Mechanical Engineering at Seoul National University, Korea and the University of Illinois, Urbana-Champaign, respectively. After getting Ph.D. (2013) in Mechanical Engineering and Nanoscale Science & Engineering from the University of California Berkeley, he had worked as a postdoctoral fellow in Materials Sciences Division at Lawrence Berkeley National Laboratory and Ugo Fano Fellow in Nanoscience and Technology Division at Argonne National Laboratory. His research is focused on developing novel nanophotonic materials and devices based on fundamental physics and experimental studies of deep sub-wavelength light-matter interaction. Dr. Rho has published approximately 150 high impact peerreviewed journal papers including Nature, Science, Nature Materials, Nature Nanotechnology, Nature Photonics and Nature Communications. He also has presented keynote and invited talks more than 250 times at the world-leading institutes and international conferences/workshops as well as having 4 US patent and 26 Korea patents. He has received honorable awards including the Optical Society of America (OSA) CLEO Milton/Chang Award, the International Society for Optics and Photonics (SPIE) Scholarships (2011 & 2012), Materials Research Society (MRS) Student Award (2012), US DOE Argonne Named Fellowship (2013-2016), Edmund Optics Educational Award (2015), the Optical Society of Korea Young Investigator Award (2016), SPIE Rising Researcher Award (2017), Korean MSIP Minister’s Commendation (2017), Proud POSTECHIAN Award (2018), Korean MSIT Minister’s Commendation (2019), OSA IMCO Young Scientist Award (2019), Korean Presidential Early Career Award for Scientists and Engineers (2019), Springer-Nature MINE Young Scientist Award (2020), Elsevier MEE/MNE Young Investigator Award and Lectureship (2020), MDPI Micromachines Young Investigator Award (2020), OSK Haerim (海林) Photonics Award (2021).



3. 이준호 교수 (공주대학교)


"국방 광학의 현황 및 전망"




국방 광학은 국가 방위 및 보안을 위해 적용되는 다양한 광학 기술 및 관련 제품을 총칭한다. 국방 광학은 반도체/디스플레이/통신/조명 등 광학 관련 분야를 모두 포함한 광산업 시장(optics & photonics industry)에서 22%를 차지할 정도로 최대 핵심 적용 분야이다. 국내에서도 전통 적용 분야인 사격·통제 및 감시·정찰은 물론 레이저 무기, 광통신, 무인 드론 등 다양한 분야에서 관련 연구개발이 활발하게 진행되고 있다. 다만, 국방 개발의 특성상 이러한 활발한 연구 진행이 인접 분야 연구자들에도 제한적으로 알려져 있다. 본 강연은 먼저 국방 광학의 개요 및 현황을 소개하고, 이후 관련 연구 개발의 추세 및 발전 전망을 공유하여, 향후 진로 및 연구개발 방향 설정 등에 도움이 되고자 한다. 발표의 순서는 다음과 같다. 1) 국방 광학 개요 및 현황 2) 전망/변화의 배경 3) 발전 전망 4) 결론 및 제언



- 공주대학교 (2005 ~ 현재) 광공학과 (조교수/부교수/교수) (현 한국광학회 수석총무이사)

- KAIST 인공위성연구센터 (1999~2005)  (연구교수)

- Univ. of London (UCL) (영국) (1999) 물리이학 박사

- Univ. of London (UCL) (영국) (1995) 위성공학 석사

- KAIST (1994) 기계공학 학사



4. 이성구 박사 (GIST)


"우주 물체 관측 레이저: 거리 및 영상 측정"



레이저 발명 이후에 레이저는 다양한 연구 및 산업 분야에 이용되어 왔으며 현재도 끊임없이 응용 분야를 넓히고 있습니다. 다가오는 우주 시대에도 레이저는 많은 역할이 기대되고 있으며 최근에는 우주 물체 관측을 위한 레이저 개발이 활발히 진행되고 있습니다. 한반도를 지나는 위성은 현재 1000여개에 달하고 많은 양의 우주 쓰레기들이 하늘을 가로지르며 궤도를 따라 이동하고 있습니다. 특히, 감시 위성의 존재는 국가 안보와 직결되고 지상으로 낙하하는 우주 쓰레기가 큰 위협으로 다가옴에 따라 우주 물체 관측의 중요성이 크게 부각되고 있습니다. 우주 물체는 정밀 궤도 측정과 영상 확보를 통해 구별이 가능합니다. 정밀 궤도 측정은 기존의 레이저 거리 측정 기술이 활용되며 수백 km 원거리 측정을 위해 고품질의 고출력 레이저가 사용됩니다. 우주 물체 영상은 인공별 레이저를 이용한 영상 보정을 통해 선명한 영상 획득이 가능합니다. 본 강좌에서는 우주 물체 관측에 사용되는 레이저 및 레이저 기술, 국내 개발 현황 및 전망에 대해 소개하고자 합니다.



2021. 6 ~ 현재: 광주과학기술원, 우주레이저연구센터, 센터장
2014. 7 ~ 현재: 광주과학기술원, 고등광기술연구소, 실장
2014. 7 ~ 현재: 기초과학연구원, 초강력레이저과학연구단, 레이저팀 리더
2005. 3 ~ 현재: 광주과학기술원, 고등광기술연구소 선임, 책임, 수석 연구원
2005. 5 ~ 2006. 3: 오사카 대학교, 레이저공학연구소 박사후연구원
2005. 2 한국과학기술원 물리학과 박사
2000. 8 한국과학기술원 물리학과 석사
1998. 2 포항공과대학교 물리학과 학사