Keynote Speakers

Prof Dr. Kemal Leblebicioğlu

Middle East Technical University, Turkey

Research Interests

  • Optimization Theory and Practice, Optimal Control, Image Processing, Process Control, Intelligent Control, Inverse Problems (In particular, system identification problems), Unmanned Underwater Vehicles, Controllers and Observers for Nonlinear Systems, Development of Autopilot and Guidance Techniques for Flying Objects, Walking Robots, Design of Decision Making Systems. 
    Awards  
    3 times METU, Faculty of Engineering, first 5 % performance award.

Memberships

  • Editor of the journal ‘‘ELEKTRİK’’, published by TÜBİTAK.
  • An advisor for TÜBİTAK-BİLTEN.
  • “Savunma Bilimleri Dergisi”, editorial board member, (KHO Savunma Bilimleri Enstitüsü)
  • Endüstri ve Otomasyon Dergisi, editorial board member,
  • IFAC TC member on Transportation Systems,
  • IFAC TC member on Optimal Control,
  • IFAC TC member on Intelligent Autonomous Vehicles

Title: Design and Analysis of a Mode-Switching Unmanned Aerial Vehicle

Abstract: In this speech, design and analysis of a mode-switching vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV) with level flight capability is considered. The design of the platform includes both multirotor and fixed-wing (FW) conventional airplane structures; therefore named as VTOL-FW. Trim conditions are obtained by solving constrained minimization problems. Linear analysis techniques are utilized for trim conditions in examining stability and controllability. The proposed method for control includes implementation of multirotor and airplane mode controllers and an algorithm to switch between them in achieving transitions between VTOL and FW flight modes. Thus, VTOL-FW UAV's flight characteristics are expected to be improved by enlarging operational flight envelope through enabling mode-switching, agile maneuvers and increasing survivability. Simulation and flight tests showed that, VTOL-FW UAV demonstrates multirotor and airplane flight characteristics with extra benefits.

 

Assoc. Prof. Dr. Huseyin Seker

The University of Northumbria at Newcastle, UK

Dr Huseyin Seker is a multi-disciplinary researcher with a particular interest in big data mining, machine learning, and bio-medical and industrial applications. He has published over 100 peer-reviewed papers, lead a number of projects, delivered keynote and invited talks at several events and organised a number of conferences and special sessions. He is currently a Reader in the Department of Computer and Information Sciences of Northumbria University in Newcastle-upon-Tyne (UK). He is also the Director of Enterprise and Engagement, and leads Bio-Health Informatics Research Team and Big Data Analytics Lab within the department. In addition to his academic duties, he is an Advisory Board Member of the North East Satellite Applications Centre of Excellence, Steering Group Member of Digital Catapult North East and Tees Valley, and member of the CyberNorth Initiative in the UK. Further information about his projects and publications can be found at http://computing.unn.ac.uk/staff/yqqd6/home.htm.

Title: Computational Discovery of New Peptides with Desired Binding Affinity

Abstract: Prediction of peptide binding affinity is one of the most challenging problems in the post-genomic era due to the diversity and large volume of peptide families and complex biological data set with high-dimension that is used to characterise the peptides. As quantitate prediction of peptide binding affinity can be regarded as a regression problem, more robust predictive technique has become necessary to deal with the challenges. This talk therefore focuses on the presentation of novel interpretable and efficient hybrid predictive model that uses the concepts of fuzzy systems, support vector regression and feature selection from very high-dimensional data sets. The talk will include how the peptides have been numerated and represented to form the high-dimensional feature space. Feature selection methods in both supervised and unsupervised manners, support vector regression and fuzzy support vector regression that have been developed for this study will be explained, and the robustness of the proposed approach is then demonstrated over four different peptide binding affinity data sets. It will also explore possible ways and suggestions that lead computational discovery of new peptides with desired binding affinity as a result of this promising hybrid intelligent predictive model.

 

Plenary Speaker

Dr. Hüseyin Üvet,
Yildiz Technical University, Turkey

Dr. Uvet holds a Bachelor of Science degree in Computer Engineering from Kultur University which he acquired in 2004. Upon completing his undergraduate studies he started his master's degree at Osaka University, Japan in System Engineering. Following his master's studies on "Compact Vision System Design for Single Cell Analysis and Manipulation" at the Robotic Technologies Lab, he started his doctorate on "Micro/Nano Robotics" at the very same Robotic Technologies Lab of Osaka University, Japan. In 2010, he continued his researches in Nagoya University, Micro-Nano System Engineering Department as a post-doctoral fellow. During this period, he worked on robotic micromanipulation, microassembly, MEMS (sensors and actuators), mechanical manipulation of biological cells and tissue using microfluidics devices.At the start of his academic studies as an undergraduate student, Dr. Uvet academic quest for excellence was awarded full scholarship by the "Japan Student Services Organization (JASSO) and The Japan Ministry of Education (MEXT)" agency to cover his master's and doctorate studies between 2005 and 2010. He received Best Conference Paper Award 2009 - ROBIO 2009 (IEEE International Conference on Robotics and Biomimetics) for the paper entitled "Automatic Single Cell Transfer Module". Starting October 17, 2011, Dr. Uvet, has been appointed at the Department of Mechatronics Engineering at Yildiz Technical University, Istanbul, Turkey.

 

Speech Title: Untethered Micro-Robotic Arm Design and Implementation for Biomedical Applications

Novelty / Progress Claim(s)

In this project, we present a micro-robot manipulation technique with high precision positional ability to move in a fluid environment with diamagnetic levitation. Precise (nano) positioning of the levitated micro-robot on the pyrolytic graphite is demonstrated in the liquid. Positioning is achieved by the movement of a "lifter" magnet on the sensitive microstage. Suspended microrobot successfully tracked the identified roots. The surface of the magnet located in the micro robot's body is coated with PDA (Polydopamine) to increase the suitability to the ambient conditions in the liquid for biomedical applications. It is envisaged that the designed micro-robot will be used effectively in high accurate motion required lab-on-a-chip applications. 

Background

Untethered manipulation of micro-robots by means of externally applied magnetic forces has been emerging as a promising field of research, particularly due to its potential for medical and biological applications. The decreased size of the robots make them suitable for both in vitro applications such as sorting, moving, filtering micro particles (e.g. cells) within lab- on-a-chip platforms and in vivo applications such as minimally-invasive surgeries or targeted drug delivery inside a human body. However, decreasing the size of the robot brings about a range of challenges such as decrease in movement capability and positioning accuracy of the robot due to the friction and adhesion forces imposed upon the robot. Previous studies have suggested the use of electrostatically powered scratch drive actuators which needs a patterned surface that consist of an array of insulated electrodes. An other variety of approaches have been devised in an effort to overcome such challenges and provide an optimal method of propulsion for the micro-robots to move inside microfluidic environments, but all have different kinds of limitations.

Description of the New Method or System

Our study is about controlling micro-robot suspended on pyrolytic graphite with nano-precision via fixed lifting magnets. Purpose of the presented method is to eliminate friction force for between surface of the substrate and micro-robot. Thus, high accuracy motion can be achieved. A ring magnet and a laser sensor are placed on the stage which can move with micro sensitivity. The motorized stage is moved vertically in the microstructure and the levitation height data of the micro robot is collected via the laser sensor. To observe the movement of the micro-robot, a microscope system was installed in which we can perform 6-axis position adjustment and micro-robot placed on the pyrolytic graphite surface in a liquid container. The micro robot used in the experiment consists of 2 parts as polymer and micro magnet. The polymer portion was produced by UV lithographic methodsusing negative photoresist film as sacrificial layer -200 microns. Micro-magnet is assembled on the center of the robot after fabrication of polymer body completed.