KAIST CS Board RSS : Events

KAIST SoC Colloquium] 04／27 (Mon) 4：00 pm, 이활석 CTO (Upstage)

04/22 20:29

Speaker: 이활석 CTO

Time: 04/27 Monday 16:00 PM

Location: (Offline) E3-1 #1501 (Joint Lecture Room 1)

Language: Korean

The Current and Future of the AI B2B Market

Abstract:

This lecture examines how artificial intelligence is reshaping business operations, particularly in document-driven workflows. Focusing on Upstage’s industry insights, it traces AI’s evolution through four transformative stages: from augmenting traditional software to pioneering AI-native systems that redefine work processes. The session begins with an overview of the current AI landscape and Upstage’s contributions, followed by a breakdown of each evolutionary phase. It highlights AI’s progression from enhancing existing tools to becoming the core driver of autonomous workflows. Key insights include the shift in document processing from rigid template-based systems to adaptive multimodal models, and the strategic distinctions between roles, tasks, missions, and workflows in AI integration. Through case studies in industries like insurance and banking, the lecture equips students with practical understanding of AI’s impact on enterprise operations. It underscores how AI is not just optimizing processes but creating entirely new paradigms for business innovation.

Bio:

- Upstage CTO (2020 ~ Present)

- Naver Clova Visual AI Lead (2017 ~ 2020)

- NCSOFT AI Center AI Lab Vision TF Researcher (2016 ~ 2017)

- Hanwha Techwin Advanced Technology Researcher, Vision Technology Group (2011 ~ 2016)

- Ph.D. in Electrical and Electronic Engineering, KAIST (2006 ~ 2011)

For more information about the colloquium, please refer to the colloquium page: https://cs.kaist.ac.kr/colloquium/

[KAIST SoC Colloquium] 04／13 (Mon) 4：00 pm, 김태호 CTO (Nota AI)

04/22 20:29

Speaker: 김태호 CTO

Time: 04/13 Monday 16:00 PM

Location: (Offline) E3-1 #1501 (Joint Lecture Room 1)

Language: Korean

지속 가능한 AI를 위한 추론 최적화·경량화 기술 트렌드

Abstract:

AI 모델의 크기는 폭발적으로 커지고 있지만, 이를 실제 디바이스에 배포하는 일은 여전히 복잡하고 어렵습니다. 학습용 칩은 단일하지만 추론 환경은 수십 가지 하드웨어로 파편화되어 있고, 그 사이에서 연산 미지원·메모리 부족·레이턴시 초과 같은 현실적인 장벽이 존재합니다.

이 강연에서는 이 격차를 메우기 위해 Nota AI가 개발한 AI 모델 최적화/경량화 플랫폼 및 솔루션에 대해 소개하고, 실증 사례를 소개합니다. 나아가 기존 Computer Vision의 한계를 VLM(Vision-Language Model)으로 극복하는 영상 분석 솔루션과, ICLR 2026에 채택된 고해상도 VLM 효율화 연구(ERGO)도 소개하며, 엣지 AI 시대의 기술적 도전과 Nota AI의 접근 방식을 공유합니다.

Bio:

- 몬트리올 대학 연구원(Y.Bengio)

- KAIST 전기 및 전자공학 석사

- KAIST AI연구소 선임연구원

- 현) 노타 CTO

For more information about the colloquium, please refer to the colloquium page: https://cs.kaist.ac.kr/colloquium/

[KAIST SoC Colloquium] 04／06 (Mon) 4：00 pm, Seong Joon Oh (KAIST AI)

04/22 20:29

Speaker: Seong Joon Oh

Time: 04/06 Monday 16:00 PM

Location: (Offline) E3-1 #1501 (Joint Lecture Room 1)

Language: English

Deploying General AI in the Private World

Abstract:

General-purpose AI has achieved remarkable capabilities but struggles in real-world private settings. This talk examines three barriers to deployment. 1. Human-to-machine communication. Encoding human intent into AI remains hard. Modularity and agentic architectures offer promising solutions. 2. Machine-to-human communication. Users must understand AI decisions. This drives research in explainable AI and training data attribution. 3. Privacy and security. Deployment in sensitive domains is blocked by PII leakage, adversarial attacks, and membership inference risks. Regulatory compliance adds further constraints. I present our recent work on these challenges. Future directions. AI research is shifting from model scaling to adaptation, personalisation, and agent-based interfaces. I conclude with a new direction - separating knowledge from intelligence in AI systems. Software engineering decoupled code from data 50 years ago. A similar decoupling in AI could unlock transparent, editable, and trustworthy systems.

Bio:

Seong Joon Oh is an associate professor at KAIST AI. He believes trustworthiness is the last barrier to the AI productivity revolution. He researches Scalable Trustworthy AI: making AI systems reliable, explainable, and aligned with human intent at scale. He has led the Scalable Trustworthy AI (STAI) group since 2022. He moved the group from the University of Tübingen to KAIST in February 2026. He was a research scientist at NAVER AI Lab for 3.5 years. He received his PhD in computer vision and machine learning at the Max-Planck Institute for Informatics in 2018, under the supervision of Bernt Schiele and Mario Fritz, with a focus on the privacy and security implications of CV and ML (Thesis). He received the Master of Mathematics with Distinction in 2014 and Bachelor of Arts in Mathematics as a Wrangler in 2013, both at the University of Cambridge.

For more information about the colloquium, please refer to the colloquium page: https://cs.kaist.ac.kr/colloquium/

[KAIST SoC Colloquium] 03／30 (Mon) 4：00 pm, Kazuhiro Nakadai (Institute of Science Tokyo)

04/22 20:29

Speaker: Kazuhiro Nakadai

Time: 03/30 Monday 16:00 PM

Location: (Offline) E3-1 #1501 (Joint Lecture Room 1)

Language: English

Title: Robot Audition in the Wild: Toward an Inclusive Society

Abstract:

Robot Audition is a concept originally proposed by Nakadai and colleagues to enable robots to perceive and understand complex acoustic scenes in real-world environments where noise, reverberation, and multiple sound sources coexist. In this invited talk, I revisit the development of robot audition from the perspective of “in the wild” sensing, highlighting how auditory and multimodal perception must evolve when robots operate beyond controlled laboratory settings. The talk begins by introducing the core technologies of robot audition, including sound source localization and separation, and by discussing the fundamental challenges that arise when these techniques are deployed in real environments. Building on this foundation, I present a series of research efforts that extend robot audition toward real-world applications, such as locating humans using sound in search-and-rescue scenarios, inferring environmental and surface properties from acoustic signals, and analyzing bird songs for ecological monitoring in outdoor environments. I also discuss how the same technical principles can be extended toward human-centered interaction, particularly sign-language-based human–robot interaction, where communication relies on non-verbal and multimodal signals rather than speech alone. Although these research topics address different application domains, they are unified by a common technical direction: expanding the signals, agents, and environments that intelligent systems are designed to perceive and reason about. By framing robot audition as a foundation for multimodal perception and interaction in the wild, this talk presents a technical pathway through which such expansions can lead toward the realization of an inclusive society, enabling intelligent systems to engage not only with diverse humans, but also with challenging environments and even non-human entities.

Bio:

Kazuhiro Nakadai received a B.E. in electrical engineering in 1993, an M.E. in information engineering in 1995, and a Ph.D. in electrical engineering in 2003 from the University of Tokyo. He worked at Nippon Telegraph and Telephone as a system engineer from 1995 to 1999, at the Kitano Symbiotic Systems Project, ERATO, JST as a researcher from 1999 to 2003, and at Honda Research Institute Japan, Co., Ltd. as a principal scientist from 2003 to 2022. Currently, he is a professor at the Department of Systems and Control Engineering, School of Engineering, Institute of Science Tokyo (formerly Tokyo Institute of Technology). He concurrently served as a visiting associate professor at Tokyo Institute of Technology from 2006 to 2010, a visiting professor from 2011 to 2017, and a specially appointed professor from 2017 to 2022. He also held a concurrent position as a guest professor at Waseda University from 2011 to 2018. His research interests include artificial intelligence, robotics, signal processing, computational auditory scene analysis, multimodal integration, and robot audition. He has served as an executive board member for the Japanese Society for Artificial Intelligence (JSAI) from 2015 to 2016 and from 2024 to 2025, and for the Robotics Society of Japan (RSJ) from 2017 to 2018. He is recognized as a Fellow of both the IEEE and RSJ.

For more information about the colloquium, please refer to the colloquium page: https://cs.kaist.ac.kr/colloquium/

[KAIST SoC Colloquium] 03／23 (Mon) 4：00 pm, 정두영 (KAIST)

04/22 20:29

Speaker: 정두영

Time: 03/23 Monday 16:00 PM

Location: (Offline) E3-1 #1501 (Joint Lecture Room 1)

Language: Korean

Title: AI 대화형 에이전트를 활용한 정서적 돌봄

Abstract:

최근 대규모 언어모델(LLM)을 포함한 생성형 인공지능의 발전은 정신건강 서비스 전달 방식에 새로운 가능성을 제시하고 있다. 특히 심리상담 챗봇은 접근성 향상, 비용 절감, 그리고 지속적인 상호작용이 가능하다는 점에서 디지털 정신건강 서비스의 중요한 구성요소로 주목받고 있다. 그러나 실제 임상 및 연구 현장에서는 이용자 참여 저하, 치료적 관계 형성의 한계, 안전성과 윤리 문제 등 여러 도전과제가 동시에 제기되고 있다. 본 강의에서는 LLM 기반 심리상담 챗봇의 최근 발전 동향을 소개하고, 대학생 및 일반인을 대상으로 한 디지털 정신건강 개입 연구 사례를 통해 실제 활용 가능성과 한계를 논의한다. 또한 챗봇 기반 상담 시스템이 효과적인 심리개입 도구로 발전하기 위해 필요한 설계 원칙과 향후 연구 방향을 제안하고자 한다.

Bio:

정두영 교수는 정신건강의학과 전문의이자 디지털 정신건강 연구자로, 현재 KAIST 디지털인문사회과학부 부교수로 재직 중이다. 서울대학교 의과대학에서 의학박사 학위를 취득하고 서울대학교병원에서 정신건강의학과 전문의 과정을 수료하였다. 이후 울산과학기술원(UNIST)에서 교수로 재직하며 대학 구성원의 정신건강 서비스 제공과 디지털 정신건강 연구를 수행하였다. 정두영 교수는 Digital Mental Health 분야에서 모바일 기반 정신건강 평가, 디지털 개입, 그리고 인공지능 기반 상담 시스템 연구를 수행하고 있으며, 모바일 앱, 가상현실, 챗봇 등을 활용한 다양한 디지털 정신건강 중재 프로그램을 개발하고 효과성을 검증해 왔다. 최근에는 생성형 AI와 대규모 언어모델을 활용한 심리상담 챗봇 및 디지털 행동개입 연구를 진행하고 있으며, 정신건강 서비스의 접근성과 확장성을 높이기 위한 기술 기반 개입 모델 개발에 관심을 두고 있다. 또한 국내외 학술지에 다수의 연구를 발표하며 디지털 정신건강 연구 분야에서 활발한 학술 활동을 이어가고 있다.

For more information about the colloquium, please refer to the colloquium page: https://cs.kaist.ac.kr/colloquium/

[KAIST SoC Colloquium] 03／16 (Mon) 4：00 pm, 조수연 (한국외국어대학교)

04/22 20:29

Speaker: 조수연

Time: 03/16 Monday 16:00 PM

Location: (Offline) E3-1 #1501 (Joint Lecture Room 1)

Language: Korean

Title: 인간 시스템의 취약점, '법'으로 패치하라: 소중한 내 돈 지키는 법

Abstract:

우리가 매일 사용하는 네트워크가 정교한 프로토콜 위에 돌아가듯, 현대 사회는 '법'이라는 보이지 않는 거대한 설계도 위에 구축되어 있습니다. 그러나 많은 이들이 법을 막연하고 어렵게 느끼며 무관심하게 지내다가 예상치 못한 분쟁에 휘말리거나 사기 피해를 입고 나서야 큰 충격을 받곤 합니다. 이번 강연에서는 여러분이 반드시 알아야 할 실무적인 기초 법률 지식을 쉽고 재미있게 소개하고, 각종 사례를 통하여 우리의 소중한 돈을 지키는 방법에 대하여 알아봅니다. 나아가 여러분의 전공 역량이 미래에 어떻게 범죄 수사와 자금 추적의 핵심 도구가 될 수 있을지 그 가능성까지 함께 조망해보는 시간이 될 것입니다.

Bio:

조수연 교수는 KAIST 산업디자인학과와 고려대학교 법학과를 졸업하고 제45회 사법시험에 합격하였다. 17년간 판사로 근무하다가 청주지방법원 부장판사를 끝으로 법원생활을 마무리하고 2025년부터 한국외국어대학교 법학전문대학원에서 민사소송실무를 가르치고 있다.

For more information about the colloquium, please refer to the colloquium page: https://cs.kaist.ac.kr/colloquium/

2026학년도 가을학기 KAIST SoC Co-op 기업설명회 [아이스크림미디어]

04/22 20:29

2026학년도 가을학기 KAIST SoC Co-op 기업설명회 – 아이스크림미디어

일시

3월 18일(수), 12:00–13:00

발표 20분
전체 질의응답 15분
개별 상담 25분

장소

E3-1동 1104호 (전산학부 4.0 강의실)

발표자

박종목 전무 (아이스크림미디어 기술연구협력총괄)

약력

학력: KAIST 전산학부 석·박사
주요 경력:
- 2025–현재: 아이스크림미디어
- 2018–2024: 아마존 (밴쿠버)
- 2007–2017: 네이버
- 2003–2007: 삼성전자

※ 늦게 오시더라도 개별 상담을 통해 안내받으실 수 있습니다. 부담 없이 참석해주시기 바랍니다.

※ 도시락 제공 및 사전 준비를 위해 3월 16일(월)까지 설문 응답을 부탁드립니다.

참여 신청하기

[KAIST SoC Colloquium] 03／09 (Mon) 4：00 pm, Leonidas J. Guibas (Stanford University)

04/22 20:29

Speaker: Leonidas J. Guibas

Time: 03/09 Monday 16:00 PM

Location: (Offline) E3-1 #1501 (Joint Lecture Room 1)

Language: English

Title: The Space Between The Images -- Visual Learning From Relations

Abstract:

In understanding or generating images or videos, visual relations play a fundamental role, reflecting basic principles that underlie the physical world. These can range from symmetries and repetitions, to groupings and compositional structures, to invariance and equivariance under various transformations, to cycle consistency. Today, almost all supervision we provide to our models is first-order and value-driven, such as specifying desired color or semantic class for pixels, expected depth for 3D points, etc. Yet the most important visual structure is encoded in binary or multiway relations between these values --- reflecting compositional scene hierarchies or respect for geometric or physical laws. In this talk we examine a number of ways that second-order, relational supervision can be provided, from being baked into the model to contrastive learning, to consistency losses for RL. We show that relation-awareness can vastly reduce the amount of training data needed and lead to superior performance across multiple applications, including classification, segmentation, reconstruction, and VQA.

Bio:

Leonidas Guibas is the Paul Pigott Professor of Computer Science at Stanford University and a Principal Scientist at Google Deep Mind. He has worked in numerous areas of computer science, such as geometric algorithms, 3D computer vision and geometric deep learning, computer graphics, robotics, discrete mathematics, and biocomputation. Dr. Guibas has been elected to the US National Academy of Engineering, the US National Academy of Sciences, the American Academy of Arts and Sciences, and the Siggraph Academy, He is is an ACM Fellow, an IEEE Fellow, and has won the ACM-AAAI Allen Newell Award, the ICCV Helmholtz prize, and Siggraph's Steven Anson Coons award.

For more information about the colloquium, please refer to the colloquium page: https://cs.kaist.ac.kr/colloquium/

[HCI＠KAIST Seminar] Feb 4 (Wed) 3pm - Prof. Sidney Fels (UBC)

04/22 20:29

We are excited that Prof. Sidney Fels from the University of British Columbia will visit KAIST and give a talk on how AI technologies are reshaping human experience. Hope many of you join us！

Speaker: Prof. Sidney Fels (https://ece.ubc.ca/sid-fels/)
Time: 3-4 pm, Feb 4, 2026 (Wed)
Location: N1 102 (Hybrid -- Zoom: https://us02web.zoom.us/j/89932140505)
Language: English
Host: Juho Kim

Title: Opportunities for AI Mediated Human Experience Research

Abstract: Research towards long-term goals to extend technologies for human cognitive, physical, and emotional communication is critical for addressing the complex challenges facing humanity. With the growth and re-emergence of AI as disruptive technology impacting human experience, I’ll discuss how investigations at my Human Communication Technologies (HCT) Lab to elevate video to be an expressive first-class citizen of media have led to new ways to refer to and interact with video that ultimately depend on exploiting AI approaches. I’ll also present machine learning implications on our explorations to create a human voice instrument using biomechanical modeling of the human body with applications in medicine, linguistics, and brain-to-speech interfaces. For discussion, I’ll reflect on the current directions of research in my lab exploring the future of human expression, learning and living in the context of this current wave of AI technologies. Is AI the end or the beginning of the next wave of human expression?

Bio: Sid Fels is a Professor in the Department of Electrical and Computer Engineering at the University of British Columbia, where he has led the Human Communication Technology Lab since 1998. He earned his PhD and MSc in Computer Science from the University of Toronto and his BASc in Electrical Engineering from the University of Waterloo.
He is internationally known for his work in human computer interaction, biomechanical modeling, neural networks, and interactive arts and music, with over 400 publications. He has led major interdisciplinary initiatives in Canada, including the CFI funded Institute of Computing, Information and Cognitive Systems and the NCE GRAND program, and previously served as Director of UBC’s Media and Graphics Interdisciplinary Centre. Since 2017, he has held the Dolby and Midnet Professorships in Digital Multimedia at UBC.

[KAIST SoC Colloquium] 12／8 (Mon) 4：00 pm, 방승현 (㈜ 오리엔텀)

04/22 20:29

Speaker: 방승현

Title: Quantum Software in Action: 산업계 적용 사례

Location: E3-1, 1501 (Offline)

Language: Korean

Abstract:

양자 소프트웨어는 기존 컴퓨터가 처리하기 어려운 복잡한 문제를 해결하기 위해 산업계에서 점차 주목받고 있다. 이번 강연에서는 금융, 물류·제조, 의약·화학, 통신·보안 등 다양한 분야에서의 적용 사례가 소개되었다.

먼저 금융 분야에서는 포트폴리오 최적화, 리스크 관리, 복잡한 금융상품 시뮬레이션에 양자 알고리즘이 활용되고 있다. 일부 글로벌 은행들은 실제 투자 전략 검증에 양자 소프트웨어를 실험적으로 도입하고 있으며, 기존 대비 효율적인 해법을 확인하고 있다.

물류와 제조에서는 공급망 최적화와 생산 일정 관리에 적용되고 있다. 복잡한 운송 경로와 자원 배분 문제를 양자 알고리즘으로 해결함으로써 물류비 절감과 효율적 자원 운영을 가능하게 하고 있으며, 글로벌 제조사들은 이를 통해 공급망 개선 프로젝트를 진행 중이다.

의약 및 화학 분야에서는 신약 후보 물질 탐색과 분자 시뮬레이션이 핵심 활용 영역이다. 양자 소프트웨어는 분자 구조 최적화와 반응 메커니즘 분석에 기여하여 신약 개발 기간을 단축하고, 신소재 개발에도 중요한 도구로 자리잡아가고 있다.통신과 보안 분야에서는 양자암호와의 결합을 통해 보안 수준을 강화하고 있다. 또한 통신 네트워크의 채널 효율을 극대화하는 데에도 적용 가능성이 높아, 정부기관에서는 양자 보안망 실증 프로젝트를 이미 추진하고 있다.

결론적으로 양자 소프트웨어가 아직 초기 단계임에도 불구하고 산업 전반에 걸쳐 실질적인 가치를 창출하고 있음을 강조하였다. 고전적 접근을 보완하는 새로운 도구로서 양자 소프트웨어는 산업 경쟁력 강화에 기여할 중요한 기술로 부상하고 있다.

Bio:

현) ㈜ ORIENTOM CEO / Founder
현) 한국양자산업협회(KQIA) 회장
현) 서울시 양자정책 자문위원
현) 세종시 양자육성 마스터플랜 분과장
QUANTUM KOREA 국제전시분과위원장
㈜ 현대증권

[PhD defense] 최기석 12／15(월) 10：30, E3-1, 4443호

04/22 20:29

[KAIST SoC Colloquium] 12／1 (Mon) 4：00 pm, Kookjin Lee (Arizona State University)

04/22 20:29

Speaker: Kookjin Lee (이국진)

Title: Generalizing FNOs for Parametric Coupled Systems and Flow-Map Learning

Location: Online (https://kaist.zoom.us/j/9741685533)

Language: English

Abstract:

We consider two extensions of Fourier Neural Operators (FNOs) to advance their applicability in modeling complex physical dynamics. First, we address coupled and parameterized partial differential equations (PDEs), which arise ubiquitously in science and engineering, from multiphase flows and plasmas to climate dynamics and biological systems, yet remain relatively underexplored in learning-based frameworks. For coupled systems, we introduce and systematically investigate a design space of FNO architectures, identifying configurations that best capture interdependent physical processes. To handle parameterized dynamics, we propose a hypernetwork-based modulation approach that conditions the operator on input physical parameters, enabling flexible generalization across problem settings.

Second, to mitigate error accumulation during long-time rollouts, we extend FNOs to learn flow-map–type operators that directly propagate solutions across larger time horizons. This formulation reduces compounding errors in autoregressive prediction while maintaining physical fidelity.

We evaluate the proposed extensions on benchmark coupled PDEs, including canonical benchmark problems and the one-dimensional capacitively coupled plasmas equation. The experiments show that our methods consistently outperform existing approaches, demonstrating the effectiveness of the coupled/parametric architectures and the flow-map formulation.

Bio:

Kookjin Lee is an Assistant Professor in the Computer Science department within the School of Computing and Augmented Intelligence at Arizona State University. His research centers on scientific machine learning, with emphasis on reduced-order modeling, structure-preserving dynamics modeling, physics-informed neural networks, and neural operators. He received the NSF CAREER Award in 2024 and has served as an area chair or program committee member for leading machine learning conferences including ICML, NeurIPS, and ICLR. His work has been supported by the NSF, Sandia National Laboratories, Meta Inc., and Applied Materials. Before joining ASU, he was a postdoctoral researcher at Sandia National Laboratories. He earned his Ph.D. in Computer Science from the University of Maryland, College Park, and his M.S. and B.S. degrees from Seoul National University.

[KAIST SoC Colloquium] 11／24 (Mon) 4：00 pm, Shane McIntosh (University of Waterloo)

04/22 20:29

Speaker: Shane McIntosh

Title: On the Scope of the Software Build Automation

Location: E3-1, 1501 (Offline)

Language: English

Abstract:

Continuous Integration and Delivery (CI/CD) pipelines process change sets that modify system behaviour by (1) invoking build and test routines, providing timely feedback to team members about whether changes integrate cleanly; (2) updating deployment environments with new system behaviour; and (3) exposing new system behaviour to samples of a user population while monitoring and responding to changes in operational metrics. CI/CD pipelines are composed of software artifacts, and as such, are prone to imperfections, such as noise (e.g., misleading signals from CI/CD) and waste (e.g., invocations of the pipeline that do not provide value). In this talk, I will present research that characterizes and mitigates noise and waste in CI/CD pipelines, and present avenues for future work.

Bio:

Shane McIntosh received the Ph.D. degree from Queen's University, for which he was awarded the Governor General's Academic Gold Medal. He is an Associate Professor and the Ross & Muriel Cheriton Faculty Fellow at the University of Waterloo. He leads the Software Repository Excavation and Build Engineering Labs (Software REBELs). Prior to this, he was the Canada Research Chair in software build automation and an Assistant Professor with McGill University. In his research, he uses empirical methods to study software build systems, devops pipelines, and software quality.

[Seminar]Prof. Rajesh K. Balan (Singapore Management University) - ˝The Challenges and Opportunities of Applying Smart Cloud Technologies to Improve IoT Solutions.˝

04/22 20:29

Speaker: Prof. Rajesh K. Balan (SMU)
When: 4:30 pm, Nov. 17 (Mon)
Where: N1, Room 201
Host: Jun Han

Title:
The Challenges and Opportunities of Applying Smart Cloud Technologies to Improve IoT Solutions

Abstract:
My goal in this talk is to inspire students and faculty to work towards solving problems by applying smart Cloud technologies to improve IoT solutions; while still having real-world impact. This type of research is particularly interesting as it requires juggling many different factors; including a) how do you fund this? b) how do you find research-worthy yet possible to deploy problems? c) how do you find appropriate commercial partners for this? d) what are the unique challenges inherent in this type of research, and e) what are the benefits / risks / disadvantages of this type of research? As part of this talk, I will share my own experience of conducting this type of research for the last 15 or so years -- across many different domains such as power management, taxi fleet management, improving indoor spaces, and improving the performance of olympic-level athletes. I will also highlight the excellent opportunities that working with Cloud technologies and IoT allows for doing this type of research.

Bio:
Prof. Balan is an ACM Distinguished Scientist and has worked in the area of mobile systems for over two decades. He obtained his Ph.D. in Computer Science in 2006 from Carnegie Mellon University under the guidance of Professor Mahadev Satyanarayanan. Over the years, Prof Balan has established a very strong reputation in the mobile systems research community with numerous publications in MobiSys, SenSys, etc. In addition, he is also very active in SIGMOBILE organised events and has served as the program chair for HotMobile 2012 and MobiSys 2019 as well as serving on the Program Committee for UbiComp, SenSys, and MobiSys. He was a co-general chair for both MobiSys 2016 and UbiComp 2018, both of which were held in Singapore and attracted record attendance levels. In addition, he also serves as the ACM SIGMOBILE Student Outreach Director and has conducted numerous student events, called ASSET, as part of this. He is an Associate Editor-in-Chief of IEEE Pervasive and is in the top 2％ lifetime of his field according to the infamous Stanford survey.

[KAIST SoC Colloquium] 11／17 (Mon) 4：00 pm, 최정숙 (전 국립심포니 오케스트라)

04/22 20:29

Speaker: 최정숙

Title: 생활속 숨은 명곡으로 여는 클래식의 세계

Location: E3-1, 1501 (Offline)

Language: Korean

Abstract:
한국은 문화강국 세계5위！ 아직은 낮설지만 사실은 익숙한 음악을 통해 클래식의 장벽을 허무는 시간이 될것입니다. 이 강의 이후 "클래식은 낮설다는 인식이 클래식은 이미 내삶에 있다"로 바뀝니다. 음악을 통해 창의적 사고와 감수성을 동시에 균형을 찾고 확장하는 시간입니다.

Bio:

숙명여자대학교 성악과 졸업(‘90년)
이탈리아 파르마 국립음악원 졸업(’04년)
프랑스 에콜노르말 음악원 3학년과정 이수(’06년)
전국립심포니오케스트라 대표이사 역임 (22.1~25.2)
지역문화진흥원 이사(’21년~24년)
우리가곡연구회 회원(’13년~현재)
숙명여자대학교 성악과 겸임교수(’10년~’12년)
피아 테발디니 콩쿠르 심사위원(’10년)
이탈리아 국제음악협회(FMI) 부회장(‘08년-’10년)
브레샤 국제 콩쿠르 2위(’05년)
트라비아타,리골렛토,트로바토레,피가로의결혼등 수많은 오페라 주.조역 출연
2023대한민국 오페라 대상 공로상 수상
팔레르모시 마촐레니 협회 초청 독창회, 마리아 칼라스 기념예술제(런던), 세종문화회관 베르디’레퀴엠‘등 출연