ASELSAN signed a cooperation agreement with Sabancı University to study Konya Metropolitan Municipality’s roadmap including its smart city strategies towards 2030. A large, interdisciplinary team will take part in this project, first-of-its kind in Turkey, under ASELSAN’s leadership.

In his statement about the subject, Professor Yusuf Leblebici, President of Sabancı University said the following: We are breaking new ground with Konya Metropolitan Municipality and ASELSAN. It is very important that any smart city solution factor in demographical, geographical and sociological characteristics of the city, and be applied in cooperation with local administrations. Therefore, we are proud to contribute to the efforts to create a strategy and a roadmap in order to produce tailor-made smart city applications for municipalities in our country under the leadership of ASELSAN.

Ranking among the top 50 defense industry companies in the world, ASELSAN produces solutions for civil use to contribute to technological and economic independence of our country with its 40 years of know-how, experience, engineering, design, infrastructure, and most importantly, human resources. Carrying out projects in the field of smart cities, ASELSAN is particularly involved in smart public transport systems, smart energy and smart city management systems and continues to cooperate with various municipalities.

Smart city concept, which includes applications and digital solutions such as smart transport and smart energy for more modern and livable cities, has recently attracted great attention in Turkey as in the rest of the world. Cities where residents are involved in decision-making mechanisms, with sustainability secured by an established finance model, and where negative environmental impacts are minimized, will be a priority area for municipalities going forward.

Within the framework of this project, ASELSAN and Sabancı University will work together by bringing together their know-how and capabilities to develop domestic and national solutions. Joint activities in the context of the project include new generation smart city proposals such as smart public transport, smart energy, social programs supported with digital technologies and smart city solutions involving citizens’ engagement in addition to tailor-made, local solutions for Konya.

Süha Orhun Mutluergil, our visiting faculty member at the Faculty of Engineering and Natural Sciences, Computer Science and Engineering Program receives Amazon Research Award for his project entitled "Linearizability Checking via Symbolic Reasoning".

Süha Orhun Mutluergil became one of the 26 recipients of Amazon Research Awards, which focus on projects related to artificial intelligence (Alexa Fairness in AI) and automatic reasoning (AWS automated reasoning). Recipients of the Spring 2021 Amazon Research Awards include researchers from universities such as Columbia, Yale, MIT, and Stanford.

Working on development of techniques and tools for verification of concurrent programs through mathematical and logical methods, Mutluergil said the following about his project entitled "Linearizability Checking Via Symbolic Reasoning": One of the cloud computing services that are becoming more widespread is distributed databases and data storage services. These services usually keep their users’ data in the form of a key-value binary in data centers located around the world. Copies of data are kept in different locations for quick access and prevention of loss of data in case of any problem.

With the project entitled "Linearizability Checking Via Symbolic Reasoning", which will be supported with Amazon Research Award, we will develop methods and tools based on symbolic reasoning to verify that distributed key-value stores like Amazon S3 fulfill the requirement of linearizability consistency. Linearizability is a consistency model that has been widely accepted and offered to users by many distributed key value stores. Very recently, Amazon S3 has started to support this consistency model. Therefore, methods and tools to be developed within the framework of this project will enable us to check that S3 verifies linearizability requirement accurately, and as there is a control mechanism based on formal definition of linearizability, to see if users have the right expectations from this mechanism of consistency in complex situations.

A beautiful example of industry-university collaboration

Highlighting that his project which was rewarded was a beautiful example of industry-university collaboration, Mutluergil added that undergraduate and graduate students from our University would work for this project. Mutluergil continued: We will both contribute to universal know-how by working on a theoretical issue with academic value and develop a tool that can be used in large-scale systems in real life. Students will have a chance to get to know and contribute to efforts deployed in a big company like Amazon, and interact with company staff members. In addition, they will be able to develop their theoretical knowledge of basics of computer science. The impact created by this project will make it possible to develop cooperation with Amazon in the years to come, and carry out more comprehensive projects based on industry-university collaboration. Therefore, more students will have a chance to interact with Amazon and be involved in joint projects going forward. Our University will have a growing interaction with Amazon and other leading companies and develop joint projects about verification of programs concurrent with mechanical reasoning methods that are becoming more and more important.

Endowed since 2015 to support academics and researchers who are successful in their fields, Amazon Research Awards focus on projects in Amazon's core fields of interest including robotics, machine learning, security and automated reasoning, which are among prominent fields of research in computer science. More than 400 researchers from 150 universities in 28 countries have been rewarded so far. In addition to funding support to rewarded projects and extension of loans for use in AWS cloud computing systems, researchers working for such projects will interact with consultant researchers at Amazon and be able to join Amazon events and training programs.

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Who is Süha Orhun Mutluergil?

Süha Orhun Mutluergil completed his undergraduate and master’s studies at Sabancı University Computer Science and Engineering Program. He completed his PhD at Koç University with his thesis on verification of concurrent programs via refinement proofs, with Dr. Serdar Taşıran as his advisor. Then he worked for two years as a postdoctoral researcher at IRIF (the Research Institute on the Foundations of Computer Science) of Université de Paris. Since October 2020, he has worked as an instructor at Sabancı University, Faculty of Engineering and Natural Sciences, Computer Science and Engineering Program.

SPARKS 2021: Digital Media online showcase includes the current student works of VAVCD program in Video, 3D Modeling, 3D Animation and Motion Graphics courses. Students learn to visualize their media design and art projects in narrative, conceptual and experimental forms.

Curator and Supervisor: Yoong Wah Alex Wong

SPARKS 2021 Participants: Abad Shams, Alp Cihan, Alp Dinçer, Ayşegül Yapar, Begum Erinç, Berna Yıldıran, Deniz Muftuler, Ece Naz Erülker, Gamar Karimli, İdil Kapıkıran, Ilgın Harput, Kıvanç Sert, Lolwa Al-Mohannadi, Melis Kocer, Nagihan Aydınlık, Naz Kırelli, Nur Nurdoğlu, Selin Memikoğlu, Shakiba Sattar, Sinem Başar, Şevval Tufan, Yavuz Yalçın, Yeraz Arslan, Zeynep Erkman, Zuhal Uz.

SPARKS 2021: Digital Media online showcase includes the current student works of VAVCD program in Video, 3D Modeling, 3D Animation and Motion Graphics courses. Students learn to visualize their media design and art projects in narrative, conceptual and experimental forms. The main aim is to have our students familiarize with digital media study, production, workflow and platforms while taking versatile courses in the program. SPARKS 2021, Digital Media showcase intents to share and translate each students’ unrestrained imagination into images in their own unique way, it is a showcase that represents - communication, collaboration and exchange of views, and most importantly, respecting individual uniqueness, creativity and freedom of expression.

Click to discover the SPARKS 2021.

Alumnus of Sabancı University Faculty of Engineering and Natural Sciences, Computer Science and Engineering Program, Hasan Ijaz talked to us about his projects with ELKON in the framework of the Industry-Oriented Projects ENS 491 Graduation Program. You can also experience professional life before you graduate thanks to the Industry-Oriented Projects ENS 491 Program.

Which project did you carry out, and with which company? Can you talk to us about your project?

I worked on a project offered by ELKON to Sabancı. The project's title was "New Generation Power and Energy Management System for Autonomous Vessel Propulsion System". We had to design and implement an AI/deep learning-based system that would take parameters in real-time, process and optimize these parameters, and suggest to the captain how to operate the vessel.

Can you talk about your team and the way you worked together?

All of the project work was accomplished as a team where we met weekly with the project supervisors, ELKON supervisor, and 2 to 3 times with the team. We decided on a free slot within the team and worked together on Zoom. Online/remote work allowed has proven to be super effective by contributing to the project while sitting in the comfort of our home.

What were the benefits of attending and experiencing the Industry-Oriented Projects ENS 491 Program?

I would recommend an industry-based project to all students since you get to learn from the industry experts along with the professors at the university. You get to experience professional mentorship. You get to learn the company environment as well, thanks to the Industry-Oriented Projects ENS 491.

A project coordinated by Ömer Ceylan, researcher at Sabancı University Faculty of Engineering and Natural Sciences (FENS) is entitled to receive support within the framework of the TÜBİTAK 1001 Program, The Scientific and Technological Research Projects Funding Program.

The project is entitled “Development of Process, Voltage and Temperature (PVT) Variation Aware Highly Energy-Efficient Deep Neural Networks (DNN) with High Inference Accuracy for Internet-of-Things (IoT) Applications.

Providing information about the aim of the project, Ömer Ceylan said the following: The aim of the project is to develop a timing error probability model that factors in process, voltage and temperature (PVT) variations to analyze and develop deep neural networks for energy-efficient IoT applications, and then build a platform that makes  possible to design deep neural networks without having to go through the lengthy top-to-bottom (network level, architectural level, circuit level and even quantization level) simulations. By using this platform, two prototype integrated circuits composed of  multiplier-accumulator (MAC) units first in 64x64 format, and then in 256x256 format will be fabricated using 65 nm CMOS technology, and the capabilities of the platform will be verified on these integrated circuits. Therefore, the goal of the project is to build a hardware development platform for energy-efficient deep neural networks where inference accuracy is not reduced (with maximum allowable reduction of 2%), factoring in PVT variations in case of low supply voltage, and to do this faster (100X faster than traditional gate-level simulations) by using statistical timing error models that we developed on our own and without requiring lengthy simulations. The platform that we develop will not be an alternative to the other techniques in use, instead, it can be used with them; it will rather be a cross-layer optimization platform that will make it possible to make a quick evaluation of the other techniques all together (various parameters such as the deep neural network to be used, type of data, data bit width, number of layers to be used in the deep neural network etc.).  Efforts within the framework of the project will close an important gap in the literature by reaching a high level of inference accuracy in an energy-efficient way, factoring in all PVT variations, and using the most accurate timing error model, and doing all this very fast compared to classical gate-level simulations.”. Erdinç Öztürk and Öznur Taştan, faculty members of FENS are involved in the project as researchers. Emre Salman from Stony Brook University  is advisor to the project.

Talking about the importance of the project, Ömer Ceylan said the following: Artificial intelligence is gaining new areas of application and growing in importance each day. It is used in healthcare for diagnosis, unmanned aerial vehicles, cars, industrial automation systems, call centers and many other businesses. Internet of Things (IoT) applications also have a growing field of application; data can be collected through sensors in locations far from the center, such data can be processed either on-site for immediate action or forwarded to a cloud, where processing is completed for further action. To enhance effectiveness of IoT applications, AI elements such as machine learning and deep learning are used in many IoT applications. Integration of deep learning method with mobile, wearable devices and other devices with edge computing and processing capabilities has been very popular in recent years. Particularly as a method frequently used in classification and pattern recognition applications, deep learning has attracted attention in recent years. In this way, opportunities offered by artificial intelligence can also be used in locations far from the center, and field of application of artificial intelligence keeps growing. In some applications, it is required to make right decisions as soon as possible, process data immediately and act according to the result of the operation. In such applications, it is necessary to complete the operations within a period of time shorter than the time it would take to send data to a center, wait for the data to be processed there, and then be sent back. In addition to shorten delays in internet of things applications, reducing band width, improving energy efficiency, and security are other requirements that justify relevance of on-site/edge computing and decision-making. Most of the IoT applications are devices which lack of a continuous source of energy, and in some cases, have to generate their own energy, therefore, they have to be energy-efficient. So, energy efficiency is of great importance for the use of deep neural networks, which have a widespread field of application, in IoT devices.

Development of energy-efficient and high-performance, quick deep neural network devices with high inference accuracy requires a cross-layer approach. These layers start at the circuit level, and go up to architectural and  network levels. It is impossible to design and develop these layers independently from each other. The layers are strictly interconnected. Therefore, it is necessary to develop a responsive platform that considers all the layers. However, it takes a very long time to develop since it requires to optimize a very high number of parameters simultaneously in case the current gate-level digital circuit simulations are used, which impractical. Therefore, it is essential to establish a simulation infrastructure to accelerate this process, and use a model accordingly. For that purpose, a probability-based timing error prediction model will be developed to facilitate quick cross-layer simulation within the framework of this project. This model factors in PVT variations and detects timing errors accurately. The timing errors thus detected will be notified to the deep neural network as errors to see how the deep neural network works in such a case, and how inference accuracy will be impacted. Data inferred from this process will be used to correct the errors that must be corrected, and any other errors which can be tolerated by the deep neural network will be left uncorrected. Thanks to a platform which will operate in this way, it will be possible to develop deep neural networks with a cross-layer approach quickly. The platform will be used to develop energy efficient deep neural network hardware for use in IoT devices with an approach that uses highly accurate timing error models factoring in PVT variations in case of low supply voltage, hencemakes it possible to use different supply voltages for different layers of the deep neural network.

We are happy to come together with our students back on our campus after a long while. We wish the Sabancı University family a healthy and successful academic year.

The Switzerland-based ArtTech’s annual forum will be held for the first time in Turkey on September 28, 2021 with a hybrid event organized in collaboration with Sabancı University. Bringing together prominent people from the world of culture, arts and economy in addition to international researchers, engineers and scientists, the forum will be hosted by Sabancı University Sakıp Sabancı Museum.

Looking for answers to questions like “Where is technological innovation heading in the arts? Are cultural institutions making the most of technology? How do start-ups invest in cultural and artistic heritage projects?” since 2017, ArtTech builds an ecosystem to explore and test innovative solutions to promising entrepreneurs, and find new questions.

Organized in collaboration with Sabancı University, ArtTech Forum 2021 will have world-famous designer Refik Anadol and author Metin Arditi as speakers and include two panels entitled “Trends and Investments in Cultural and Creative Industries” and “Heritage preservation and technologies, focus on Turkey and region” with a focus on Turkey and the region. Moreover, the 5^th ArtTech Prize will be awarded to one of the 8 innovative startups selected by an international jury.

ArtTech Forum 2021 will start at Sabancı University Sakıp Sabancı Museum with the opening speeches of Yusuf Leblebici, president of Sabancı University, Patrick Aebischer, Chairman of ArtTech Foundation, Roland Brun, Deputy Consul General of the Consulate General of Switzerland in Istanbul, and will bring together prominent people in the world of culture, arts and technology through panel discussions.

Please click to see ArtTech Forum 2021 Program.

* The event will be in English.

A project implemented by Leila Haghighi Poudeh, postdoctoral researcher at Sabancı University Integrated Manufacturing Research and Application Center (SU-IMC) is entitled to receive support within the framework of the TÜBİTAK 1001 program.

Leila Haghighi Poudeh’s project is entitled “Development of New Ionic Conductor Prepreg Interlayers and Their Application to Structural Energy Storage Systems by Using a Multiscale Engineering Approach”. Researchers and advisors from the Faculty of Engineering and Natural Sciences (FENS) and Composite Technologies Center of Excellence (CTCE) are also involved in the project.

Mehmet Yıldız, Vice President of Sabancı University, Fevzi Cebeci and Bekir Dizman, members of FENS, and Merve Senem Seven, post-doctoral researcher at FENS are involved in the project as researchers. Canan Atılgan and Yusuf Menceloğlu, members of FENS act as advisors to the project.

Talking about the importance of the project, Poudeh said the following: In recent years, development of energy storage devices has played an important role in development of emerging technologies such as aviation, portable electronic devices and electric vehicles. Although many research efforts were deployed for development of high-performance energy storage devices, integration of such systems resulted in a considerable increase in the weight of structural components. Such systems usually have a laminated structure composed of carbon fibers that are modified as electrodes, glass fabric as a separator and an electrolyte that is filled in between the two layers. The main challenge of this field which also inhibits the utilization and commercialization of multifunctional energy storage devices, is the trade-off relationship between mechanical performance and charge storing capability. This project aims to overcome this problem and improve the performance of such systems by following multiscale material design framework.

Mentioning the aim of the project, Poudeh said the following: Planned to last three years, our multidisciplinary project will contribute to the two PHD theses. The aim of the project is to develop alternative electrolyte chemistries by using computational and experimental approaches, and to manufacturing ionically conductive electrolyte/separator prepregs that can be implemented within any energy storage system. In the final stage of the project, it is planned to develop and evaluate a laboratory-scale prototype with a structural, electrochemical and multifunctional perspective to validate the concept of power composites.

COVID-19 VACCINATION REQUIREMENTS FOR DORMITORIES IN THE 2021-2022 ACADEMIC YEAR 

In the framework of the Regulation on Accommodation Services in Higher Educational Institutions issued by the Ministry of Youth and Sports and published in the Official Gazette dated 02.07.2020, No 31173, which also applies to the accommodation services provided by our University, necessary health measures must be taken.

Therefore, our students who will stay in our dormitories in the 2021-2022 Academic Year are required to submit their vaccination cards validated by the related authorities, indicating that they have been vaccinated against COVID-19. Furthermore, our students who previously contracted COVID-19 are requested to submit their positive PCR test results. The right to introduce further arrangements made by the Ministry of Health, the Higher Educational Council, the Ministry of Youth and Sports and any other relevant authorities is reserved.

Based on the above, only those students who have received at least 2 doses of vaccine with the last dose administered at least 14 days before their admittance to our dormitories will be permitted to enter.

According to the decision of the Ministry of Health, people who have contracted COVID-19 can be vaccinated after 1 months following their recovery. In this case, to be able to have their dormitory registration completed, students who have been already contracted COVID-19 but whose vaccination time has not arrived as of their date of entry to the dormitory must consent to booking an appointment and receiving their vaccines as soon as they are eligible to the vaccine.

You are kindly requested to email your vaccination cards and PCR test results referred to in the announcement to healthcenter@sabanciuniv.edu . 

Accommodation Service Unit / SER

The Orientation Program, which the all new undergraduate students of Sabancı University will participate, will be held on 23rd-24th of September, 2021. On the first day of orientation, the entire program will take place online. The second day program of the orientation will take place face to face on campus. Presentations can also be followed online via the web.

Please click to read details of the Orientation Program.