(주)에임퓨처 소개 및 구인과 관련하여 안내드리오니 첨부파일 참고바랍니다. 

○  Plan for education of Nonsubject based on research study   A. Research Ethics / Research Note 구분내용비고TakeCourseResearch Ethics for Researcher (from KIRD)(https://alpha-campus.kr)NonSubjectCourse Name비고ResearchEthicsResearch ethics for graduate studentsFreeResearchNoteLaboratory Notebook·Available at all the timeCertificate RegistrationCertificate Registration   :Academic Affairs Information - Nonacademic - NonAcademic Recognition of Completion Registration·Uploading the Certificate of Completion is available during semester only (1st March ~ 21st June)ApprovalApproved by officer·Please contact to department office in case that the completion is not approved in a week.   B. Thesis Writing 구분내용비고Apply for online lectureApply for online lecture   :Portal - Academic Affairs Information - Nonacademic - NonAcademic Course Registration   :Apply for only one course from below according to the field of study구분과목명Natural Sciences & Engineering논문작성법(이공계) -한국어Thesis Writing(Natural Sciences & Engineering) - EnglishLiberal Arts & Social Sciences논문작성법(인문사회계) - 한국어Thesis Writing(Liberal Arts & Social Sciences) - English·Feb 17th(Fri) ~ 27th(Mon)·Course Registration students apply will be confirmed on March 2ndTakeCourseCan take the course in Ajou Bb·Available during semester only (2nd March ~ 21st June)·Those who need to complete ‘Thesis Writing’for thesis submission must take this course by March 31st(Fri)ApprovalApproved at the end of semester·Please contact to department office in case that the completion is not approved in a week.   ※ Refer to the attached guidelines for details such as how to how to register Certification.

대학원 인공지능학과 및 수학과 학생들로 구성된 '성장통'팀이 ‘2022 SW인재페스티벌’에서 기업상을 수상했다. ‘2022 SW인재페스티벌’은 과학기술정보통신부와 정보통신기획평가원, 소프트웨어중심대학협의회의 주최·주관으로 지난 8일부터 9일까지 동대문디자인플라자에서 열렸다. ‘SW인재페스티벌’은 소프트웨어 산업을 이끌어갈 인재양성의 중요성을 알리고 소프트웨어중심대학사업과 대학교육의 성과 확산을 통해 대국민 ▲소프트웨어교육 신뢰 확보 ▲소프트웨어가치 창출을 위해 개최됐다. 이번 행사는 "디지털 인재를 넘어 글로벌 리더로" 라는 주제로,  소프트웨어중심대학 44개교 및 약 100여개 산업체 관계자들이 참여했다. 행사에서는 ▲소프트웨어중심대학 전시관(홍보입시/우수작품) ▲공동채용관 ▲기업관 등이 운영됐다. '성장통'팀은 대학원 인공지능학과 ▲조우연 학생과 수학과▲윤기웅(17) ▲최형준(17) ▲최윤석(19) ▲최아림(19) 학생으로 구성됐다.'성장통'팀은 <골연령을 이용한 성장관리 프로젝트>라는 주제로 기업상을 수상했다. <골연령을 이용한 성장관리 프로젝트>는 CNN을 기반으로 학습된 모델이 골 연령을 자동으로 측정해서 골 연령 검사 결과를 모바일 어플리케이션으로 쉽게 보관·확인할 수 있도록 개발한 내용이다.‘성장통’의 팀장 윤기웅 학생은 "이번 대회를 통해 비전공자도 SW인재로 성장할 수 있다는 사실에 뿌듯했고, 디지털전환시대를 이끌어 갈 SW·AI인재로 성장해 나갈 것"이라고 포부를 밝혔다.소프트웨어중심대학사업은 과학기술정보통신부(IITP)가 주관하는 정부지원사업이다. 아주대학교 소프트웨어중심대학의 사업 목표는 '초지능 초연결 초실감 시대의 변화와 혁신을 선도할 인재 양성'으로 ▲소프트웨어전공 ▲융합 ▲기초 ▲산학 분야에서 다양한 사업을 수행하고 있다. 

Artificial Intelligence Colloquium을 1월 20일(금) 오전 11시에 개최하고자 하오니 관심있으시면 많은 참석 부탁드립니다. When : 2023.1.20(금) 오전 11시~ Where : 팔달관 407호 Speaker : 박종세(KAIST 교수) Title : Algorithm-Hardware-Software Co-Design to Build Specialized Systems  Abstract : Modern retrospective analytics systems leverage cascade architecture to mitigate bottleneck for computing deep neural networks (DNNs). However, the existing cascades suffer from two limitations: (1) decoding bottleneck is either neglected or circumvented, paying significant compute and storage cost for pre-processing; and (2) the systems are specialized for temporal queries and lack spatial query support. In this talk, I will present CoVA, a novel cascade architecture that splits the cascade computation between compressed domain and pixel domain to address the decoding bottleneck, supporting both temporal and spatial queries. CoVA cascades analysis into three major stages where the first two stages are performed in compressed domain, while the last one in pixel domain. First, CoVA detects occurrences of moving objects (called blobs) over a set of compressed frames (called tracks). Then, using the track results, CoVA prudently selects a minimal set of frames to obtain the label information and only decode them to compute the full DNNs, alleviating the decoding bottleneck. Lastly, CoVA associates tracks with labels to produce the final analysis results on which users can process both temporal and spatial queries. Bio : Jongse Park is an assistant professor in the School of Computing at Korea Advanced Institute of Science and Technology (KAIST). He is also co-leading the Computer Architecture and Systems Laboratory (CASYS). His research focuses on building hardware-software co-designed systems for emerging algorithms and applications. He has a PhD in computer science from Georgia Institute of Technology. Before joining KAIST, he was a deep learning acceleration solution architect at Bigstream Solutions Inc. He was a guest editor IEEE Micro Special Issue on Machine Learning Acceleration, and has served on program committees of top international conferences, including ISCA and DAC.     Host : 소프트웨어학과 안정섭 교수(jsahn@ajou.ac.kr)