TUTKIMUSNEUVOSTO Pöytäkirja 27082018 TUTKIMUSNEUVOSTON KOKOUS 8/2018 Aika 27.8.2018 klo 14.00 16.30 Paikka HR142 Tutkimusneuvoston jäsenet: tutkimusrehtori Taina Pihlajaniemi, puheenjohtaja professori Heli Jantunen professori Sanna Järvelä associate professor Jouni-Matti Kuukkanen professori Juha Pekka Lunkka professori Tuija Mainela professori Mika Rämet professori Mikko Sillanpää professori Seppo Vainio (paikalla klo 15:08 alkaen) tohtorikoulutettava Pauli Väisänen Muut: suunnittelija Ritva Saastamoinen tutkimuskoordinaattori Aija Ryyppö professori Arja Rautio (5 ) tutkimuskoordinaattori Kirsi Latola (5 ) 1 Kokouksen laillisuus ja päätösvaltaisuus (esittelijä: Taina Pihlajaniemi) Kutsu kokoukseen on lähetetty 11.06.2018. Hallintoelin on päätösvaltainen, kun puheenjohtaja mukaan luettuna vähintään puolet jäsenistä on läsnä. Oulun yliopisto PL 8000 90014 Oulun yliopisto oulun.yliopisto @ oulu.fi Puh 0294 480 000 Fax 08 344 064 Päätösesitys: Tutkimusneuvosto toteaa kokouksen laillisesti kokoon kutsutuksi ja päätösvaltaiseksi. Päätös: Tutkimusneuvosto totesi kokouksen laillisesti kokoon kutsutuksi ja päätösvaltaiseksi. www.oulu.fi 1 / 10
2 Kokouksen esityslistan hyväksyminen (esittelijä: Taina Pihlajaniemi) Päätösesitys: Esityslista hyväksytään. Päätös: Esityslista hyväksyttiin. 3 Tutkimusneuvoston sihteerin valinta (esittelijä: Taina Pihlajaniemi) Päätösesitys: Tutkimusneuvosto keskustelee asiasta ja tekee tarvittavat päätökset. Päätös: Strategian ja tiedepolitiikan yksikön (STY:n) henkilöstön tehtävien uudelleenjärjestelyjen myötä tutkimusneuvoston sihteerinä toimineen tutkimuskoordinaattori Aija Ryypön tehtävänkuva on muuttunut. Tutkimusneuvosto keskusteli asiasta ja päätti, että tutkimusneuvoston toimikauden loppuun sihteerin tehtäviä hoitaa STY:n suunnittelija Ritva Saastamoinen. 4 Tehtävien täyttöjen hyväksyminen nimitysesitykset (esittelijä: Ritva Saastamoinen) 4 Esitykseen liittyvät dokumentit ovat nähtävissä tutkimusneuvoston Optimatyötilassa. 4.1. Esitys Li Liun nimittämisestä tehtävään Tenure Track Assistant Professor (Learning compact and efficient image and video representations) ja esitys Marian Codreanun nimittämisestä tehtävään Tenure Track Assistant Professor (Distributed artificial intelligence and ma-chine learning) For strengthening its profile in computer vision and artificial intelligence at international level the University of Oulu announces the following six tenure track Assistant Professor positions for highly talented individuals who hold a doctoral degree and have excellent potential for a successful scientific career: 1. Tenure-track position in learning compact and efficient image and video representations is directed to investigating revolutionary next generation methodologies for image and video representation that are fast to compute, memory efficient, and yet exhibit good discriminability and robustness, bridging the gap between computationally efficient traditional descriptors, e.g., local binary patterns, and very expensive convolutional neural networks. Featuring exponentially increasing 2 / 10
3 / 10 amount of images and videos, the emerging phenomenon of big dimensionality (millions of dimensions and above) renders the inadequacies of existing approaches, no matter traditional handcrafted features or recent deep learning based ones. Among the areas of application for compact and efficient representations are wearable/mobile devices with strict low-power constraints, biometric recognition systems, environment embedded perceptual interfaces, and biomedical image and video analysis. 2. Tenure-track position in machine learning for 3D computer vision is directed to developing new machine learning based technology for sensing and analysis of 3D information using image and/or other sensory data. Relevant research topics include but are not limited to pose estimation, multi-view stereo, structure from motion, simultaneous localization and mapping, and 3D object recognition. The aim is to bridge the gap between the conventional geometric approaches and modern learning-based techniques such as deep neural networks. Potential application areas are, for example, augmented reality, robotics, selfdriving or autonomous vehicles, computational photography, sensor networks, 3D modeling, and image-based rendering. 3. Tenure-track position in multimodal signal and image analysis for medical and health applications is directed to investigating and designing novel health technologies that apply digital signal or image analysis and machine learning algorithms for improved health and wellbeing. Relevant research topics in signal analysis include cardiovascular system signal analysis, respiratory system signal analysis, central nervous system signal analysis, autonomic nervous system signal analysis, and affective computing. Suitable medical image analysis topics cover a wide range of possible image analysis sub-fields. 4. Tenure-track position in machine learning for human behavior and interaction analysis from multimodal data is directed to emotional artificial intelligence. Research is to investigate and propose novel machine learning methodology, for example for facial expression and body gesture analysis acquired by different types of detectors and sensors, and measuring physiological signals from videos, as well as study the context and work on multi-modal learning and fusion, in order to interpret human behaviors for human-computer/robot interaction with emotional intelligence. 5. Tenure-track position in distributed artificial intelligence and machine learning is directed to distributed environment embedded intelligent system. The objective is to investigate intelligent methods and methodologies for future self-configurable information infrastructures that are expected to consist of very large numbers of wireless sensors and actuators that provide novel services, such as perceptual interfaces though distributed computing and machine learning. 6. Tenure-track position in automated design tool chains for ubiquitous artificial intelligence systems is directed to environment embedded intelligence. The objective is to investigate and propose new tool chains for the automatic generation of intelligent ubiquitous systems, both
hardware and executable software, from high-level descriptions, such as dataflow models of machine learning and wireless communications algorithms. The expected applications range from multi-modal signal analysis to environment embedded distributed perceptual human-computer interfaces. The positions are placed at the Center for Machine Vision and Signal Analysis Research Unit (CMVS, http://www.oulu.fi/cmvs), Faculty of Information Technology and Electrical Engineering (ITEE, http://www.oulu.fi/itee). CMVS is renowned world-wide for its scientific breakthroughs in machine vision and signal analysis. Many of its results, including the Local Binary Pattern, face analysis and geometric camera calibration methodologies, are highly cited and have been adopted for different types of problems and applications around the world. The unit is internationally attractive, with one visiting FiDiPro Professor and one Fellow, several visiting scholars and an extensive international collaboration network, enabling a large number of joint publications in leading forums. The main research interests of CMVS are in computer vision and machine learning, affective computing, multimodal image and signal analysis, lowenergy computing, and applications in affective human-computer interaction, biometrics, augmented reality, and biomedicine. In physiological signal analysis basic, applied and translational research in biomedical engineering is carried out to tackle key challenges of next generation personalized medicine and wellness solutions. Job Responsibilities and Required Qualifications: A person at any level of the academic tenure track system is expected to conduct outstanding world-class scientific research, to be competitive in attracting external funding, to publish in leading journals and conferences, to supervise CMVS s doctoral students, to be an active member of the international scientific community, to create and teach related BSc and MSc level courses, and to exhibit academic leadership. Required qualifications and career advancement at each level of the tenure track: Career advancement on the tenure track is based on performance assessments that measure the candidate s merits. When appointing a person to the position of an Assistant Professor the applicants are evaluated based on the following criteria: publications on an international level: dissemination, quality of the publication forums, references to the publications active role in the research training acquisition of external funding working in more than one research facility during one s career (in most fields represented at the University of Oulu this signifies working abroad) an active role in the international scientific community acknowledgements and awards. 4 / 10
Applications: Applications, together with all relevant enclosures, should be submitted electronically by 30.11.2017. Tenure track -tehtäviä täytettäessä asetetaan vaatimukseksi erinomainen tieteellinen laatu ( kansainvälisesti korkea taso Suomen Akatemian pisteytyksellä 5-6/6, erinomainen-poikkeuksellisen hyvä; world-class level, Academy of Finland scoring 5-6 out of 6, excellent-outstanding), joka todennetaan kansainvälisten korkeatasoisten tutkijoiden (2-4 asiantuntijaa) antamien arviointien perusteella. Assistant Professor -tehtävä on tohtorikoulutusvaiheen jälkeen juuri väitelleen ammattimaiselle tutkijanuralle siirtyvän henkilön tehtävä. Se on aina määräaikainen ja kauden pituus on 3-5 vuotta. Tehtävään voidaan nimetä tohtoreita, joiden väitöskirjan hyväksymisestä on kulunut korkeintaan 10 vuotta. Assistant Professor -tehtävään edellytetään soveltuvaa tohtorin tutkintoa ja kykyä itsenäiseen tieteelliseen työhön sekä tehtävässä tarvittavaa opetustaitoa. The call attracted altogether 34 applications, of which top 12 were sent to be evaluated by external experts, based on the library analysis and publication data. The selection committee chose top five candidates to be interviewed based on the evaluation reports, paying special attention to scores given for scientific activities and acquisition of research funding. These candidates were Marian Codreanu, Jie Gui, Jukka Kortelainen, Li Liu and Angela Yao. Angela Yao withdrew her application. Codreanu has got his PhD Degree in November 2007, but at the time of the application he was still within the ten-year limit for assistant professor s position. One of the evaluators, Prof. Hyttinen, selected top six candidates to be evaluated based on the documents supplied. Li Liu was not selected to be evaluated by Prof. Hyttinen. The interviews were held for Kortelainen, Liu and Codreanu, and via Skype for Gui. Director of CMVS, professor Olli Silvén, also participated in all interviews. Tutkimusneuvosto päätti kokouksessaan 5/2018 (1.6.2018) palauttaa esityksen Li Liun ja Marian Codreanun nimittämisestä Tenure Track -tehtäviin professori Jari Hyttisen puutteellisen arviointilausunnon vuoksi. Valmistelutyöryhmän puheenjohtaja Mika Ylianttila pyysi 7.6.2018 määräaikaan 28.6.2018 mennessä Jari Hyttiseltä täydennystä lausuntoon siten, että siihen sisältyy arviot ja yhteenveto kaikista niistä henkilöistä, jotka hän totesi kelpoisiksi avoinna olleisiin tehtäviin. Pyydettyä täydennystä ei saatu annettuun määräaikaan mennessä. Valmisteluryhmä päätyi esitykseen, että Jari Hyttisen lausunto hylätään kokonaisuudessaan kaikkien hakijoiden osalta ja nimitysesitys tehdään kahden lausunnon perusteella. Asiantuntijoiden lausuntojen perusteella (yhteenveto: Liite 1) valintaryhmä esittää, että Dr. Li Liu (topic 1, Tenure-track position in learning compact and efficient image and video representations) ja Dr. Marian Codreanu (topic 5, Tenure-track position in distributed artificial intelligence and machine learning) valitaan Assistant Professor -tehtäviin. 5 / 10
Päätösesitys: Tutkimusneuvosto keskustelee asiasta ja tekee tarvittavat päätökset. Päätös: Tutkimusneuvosto keskusteli asiasta ja hyväksyi nimitysesityksen. 4.2. Esitys Qifeng Shun nimittämisestä tehtävään Tenure Track Associate Professor (Formation and Behaviour of Non-metallic Inclusions During Primary and Secondary Steelmaking) One of the main focus areas is Creating sustainability by materials and systems, which includes Sustainable production and use of advanced steels, i.e. the key theme of the Process Metallurgy Research Unit (MET). The Process Metallurgy Research Unit is experienced in understanding reactions, reaction kinetics, thermodynamics and mass and heat transfer phenomena in high-temperature processes. The research work is focused on four areas: (1) coke and reduction metallurgy, (2) refining metallurgy, (3) utilisation of waste materials (dusts, sludges and slags) produced in the metallurgical industry and (4) development of new measuring methods for high-temperature processes. The research is largely technology-oriented with emphasis on fundamental research in the area of the materials characterisation. The main external funding sources are European Union RFCS and Horizon2020 programs, Academy of Finland and Tekes (Finnish Funding Agency for Innovation). Further details of the unit are given in the links http://www.oulu.fi/casr/ and see http://www.oulu.fi/pyometen/. Description of the field of the tenure track position: The research will concentrate on modelling the formation and behaviour of non-metallic inclusions during primary and secondary steelmaking. The work will consist of the derivation of phenomena based models for inclusion formation, growth and removal. The characterisation of the properties of non-metallic inclusions as function of their size and composition is important for ultra clean steel production. Furthermore, development of novel in situ analysing and monitoring methods to characterise process status for producing clean steel with controlled low levels of inclusions and impurities is under review. The research field will form an integral part of the MET unit, and will involve working in close cooperation with the unit s other groups and projects. Responsibilities and Required Qualifications The successful candidate is expected to conduct high-level research in the field, including research management and funding acquisition, and to take actively part in international scientific community and collaboration. Furthermore, the duties include undergraduate and graduate level teaching and supervision of academic theses. Career assessment on the tenure track is based on regular performance assessment that measures the candidate s merits in all these areas. 6 / 10
It is envisaged that the successful applicant will possess the experience and competence to be placed at Assistant or Associate Professor level in the tenure track system. The University of Oulu Tenure Track Guidelines will be followed in filling the position. The position of an assistant professor is for persons who have recently finished their doctoral dissertation and are advancing towards a professional research career. The position is always fixed-term and the duration varies from three to five years. A continuation period may be granted as indicated in the University of Oulu Tenure Track guidelines (http://www.oulu.fi/university/node/38379). Only doctors who have finished their doctoral thesis less than ten years ago can be appointed to the position of an assistant professor. The selection criteria for an assistant professor are the following: PhD in a relevant field (e.g. process metallurgy or materials science) Research potential, (publications, especially internationally refereed publications; participation in funding applications / funding granted) National and international networks and experience from working abroad Experience in teaching and supervision of diploma and doctoral students Demonstrating developed skills is prerequisite for a continuation period When appointing a person to the position of an associate professor the applicants are evaluated based on the following criteria: Publications on an international level: dissemination, quality of the publication forums, references to the publications Active role in the research training Acquisition of external funding Working in more than one research facility during one s career (in most fields represented at the University of Oulu this signifies working abroad) An active role in the international scientific community Acknowledgements and awards. Applications, together with all relevant enclosures, should be submitted using the electronic application form by 6th November, 2017. There were totally 15 applications to the position. The following six applicants were selected for further external evaluation: Lijia Zhao, Qifeng Shu, Mu Wangzhong, Kanegasan Samikannu, Samuel Awe and Esmaeil Adabifiroozjaei. Three professors in the field were proposed and selected as external reviewers: 1) Marisa Di Sabatino Lundberg, Professor in Physical Metallurgy, NTNU, Trondheim, Norway. 2) Bo Björkman, Professor in Processmetallurgy, Luleå Tekniska Universitet, Luleå, 3) Eric Palmiere, Professor in Metallurgy and Thermomechanical Processing, University of Sheffield. 7 / 10
Liite 2 sisältää arvioitsijoiden yhteenvedon. The statements of the referees were unanimous for the two highest ranked candidates; Qifeng Shu and Wangzhong Mu. The overall rating based on the average of the ratings given by the reviewers for assessing the scientific, teaching and supervision activities, acquisition of competitive funding and international scientific activities are It is obvious that Shu and Mu are well separated from other four candidates. In addition Lijia Zhao is ranked for selection by two of the reviewers. Zhao is also well identified by the third reviewer with second best evaluation points but being not in the final proposal of two selected candidates. In more details Prof. Palmiere evaluates Qifeng Shu as primary selection for Associate level and Wangzhong Mu as the primary candidate for Assistant level. The same is suggested by Prof. Björkman. Prof. Sabatino proposes selection of Qifeng Shu directly on the professor level and places Wangzhong Mu again as primary candidate for Assistant level. Björkman and Sabatino clearly indicate the selection of Qifeng Shu as primary candidate. In very short summary, by the preparation group and referring parts of the evaluations: Qifeng Shu, is currently Professor at School of Metallurgical and Ecological Engineering, University of Science and Technology, Beijing since 2015. He has supervised 2 PhD and 5 Master students. He has experience in teaching both in Chinese and English. He has international experience working as research associate in Germany and in visiting Professorship in Brazil. Shu has 53 publications, 274 citations, H = 12 (according to Google scholar). He has relevant background for the position. Wangzhong Mu is currently postdoc at KTH, Sweden. He has obtained PhD in 2015 in KTH. Until July 2017, he was postdoc fellow at McMaster University, Canada. His international network is wide. The scientific activity plan is quite extensive and well organized. h = 6, 21 publications, around 100 citations (time of application). Based on the unanimous reports by the reviewers, the scientific merits and international career of the candidates, the preparation group suggests, in the following order, recruiting of 1. Qifeng Shu on the Associate Professor level 2. Wangzhong Mu on the Assistant Professor level In the tenure track position of Formation and behaviour of non-metallic inclusions during primary and secondary steelmaking. Due to the seemingly obvious selection of the two candidates and their internal order, the preparation group suggests organizing the evaluation of teaching skills as part of the further career path of the recruited candidate. 8 / 10
Dekaani Riitta Keiski esittää valmisteluryhmän esityksen perusteella, että yliopistotutkijan (Associate Professor) tenure track -tehtävään valitaan D.Sc. (Tech) Qifeng Shu viiden vuoden määräajaksi. Tehtävän ala on Formation and Behaviour of Non-metallic Inclusions During Primary and Secondary Steelmaking. Päätösesitys: Tutkimusneuvosto keskustelee asiasta ja tekee tarvittavat päätökset. Päätös: Tutkimusneuvosto keskusteli asiasta ja hyväksyi nimitysesityksen. 4.3. Esitys Anna-Kaisa Salmen nimeämisestä tehtävään Tenure Track Associate Professor (Archaeology at the Faculty of Humanities) Tutkijatohtori Anna-Kaisa Salmi on tehnyt 28.11.2017 esityksen humanistisen tiedekunnan dekaanille, että hänet nimitettäisiin associate professorin tenuretehtävään. Tehtävä ei ole ollut julkisesti haettavana, vaan kyse suorarekrytoinnista, jossa arviointiprosessin aloittamiselle on saatu lupa tutkimusneuvostolta 22.2.2018. Kokouksessa myös hyväksyttiin asiantutkijalausunnot antaneet arvioijat. E.m. johdosta liitteet soveltaen tenure track-toimintaohjetta (liitteistä jätetty pois valintamuistio, hakijayhteenveto sekä arvioijatiedot). Associate professorin pätevyysehdot on mainittu edellä kohdassa 4.2. Liite 3 sisältää Tenure-arvion yhteenvedon. Viitaten saatuihin asiantuntija-arvioihin dekaani Paula Rossi esittää tutkimusneuvostolle, että tutkijatohtori Anna-Kaisa Salmi nimitettäisiin hakemuksensa mukaisesti viisivuotiseen associate professorin tenure-tehtävään (Archaeology at the Faculty of Humanities). Päätösesitys: Tutkimusneuvosto keskustelee asiasta ja tekee tarvittavat päätökset. Päätös: Tutkimusneuvosto keskusteli asiasta ja hyväksyi nimitysesityksen. 4.4. Esitys Assistant Professor Hanna Järvenojan nimittämisestä seuraavalle, Associate Professor, uratasolle (Emotion and Motivation in Learning) Hanna Järvenoja on tehnyt 21.11.2017 esityksen kasvatustieteiden tiedekunnan dekaanille, että hänen osaltaan aloitettaisiin arviointi jonka perusteella hä- 9 / 10
nen on mahdollista siirtyä tenure-tehtävässään seuraavalle uraportaalle associate professor -tehtävään. Hänen nykyinen nelivuotinen assistant professor tenure-tehtävänsä päättyy 31.7.2019. Tutkimusneuvosto on käsitellyt anomuksen ja hyväksynyt esitetyt ulkopuoliset asiantuntijat 22.3.2018 pitämässään kokouksessa. E.m. johdosta liitteet soveltaen tenure track-toimintaohjetta (liitteistä jätetty pois valintamuistio, hakijayhteenveto sekä arvioijatiedot). Associate professorin pätevyysehdot on mainittu edellä kohtassa 4.2. Liite 4 sisältää Tenure-arvion yhteenvedon. Viitaten saatuihin asiantuntija-arvioihin dekaani Kati Mäkitalo esittää, että Hanna Järvenoja voidaan nimittää hakemuksensa mukaisesti viisivuotiseen associate professor tenure-tehtävään. Tehtävän ala on Emotion and Motivation in Learning. Päätösesitys: Tutkimusneuvosto keskustelee asiasta ja tekee tarvittavat päätökset. Päätös: Tutkimusneuvosto keskusteli asiasta ja hyväksyi nimitysesityksen. 5 Thule-instituutin vetämien arktisten asioiden esittely (esittelijät: Arja Rautio ja Kirsi Latola) Päätösesitys: Tutkimusneuvosto keskustelee asiasta ja tekee tarvittavat päätökset. Päätös: Tutkimusneuvosto keskusteli asiasta ja totesi, että arktiset asiat ovat laaja monialainen kokonaisuus, johon liittyy suuri käyttämätön rahoituspotentiaali. Tutkimusneuvoston jäsenten tulisi välittää tietoa eteenpäin omissa tiedekunnissaan ja tutkimusyksiköissään, jotta rahoituspotentiaalia voidaan hyödyntää tehokkaammin ja arktisiin asioihin kytkeytyvää Oulun yliopiston tutkimuksen ja mahdollisen piilossa olevan arktisen tietotaidon näkyvyyttä voitaisiin parantaa entisestään. Temaattista apua saa tarvittaessa Thule-instituutista ottamalla yhteyttä Arja Rautioon tai Kirsi Latolaan. 6 Vuosikello (esittelijä: Ritva Saastamoinen) Tutkimusneuvosto keskustelee tulevista tehtävistään ja päivittää tarvittaessa vuosikelloa. Vuosikello on nähtävissä tutkimusneuvoston Optima-työtilassa. Päätösesitys: Tutkimusneuvosto päivittää vuosikelloa. Päätös: Tutkimusneuvosto päivitti vuosikelloa. 10 / 10