{"id":50,"date":"2016-05-03T08:15:49","date_gmt":"2016-05-03T08:15:49","guid":{"rendered":"http:\/\/qufaculty.qu.edu.qa\/mkiranyaz\/?page_id=50"},"modified":"2017-10-03T10:34:08","modified_gmt":"2017-10-03T07:34:08","slug":"recent-achievements-and-awards","status":"publish","type":"page","link":"https:\/\/qufaculty.qu.edu.qa\/mkiranyaz\/recent-achievements-and-awards\/","title":{"rendered":"Recent Achievements and Awards"},"content":{"rendered":"

\"Awards2-5ea930\"<\/p>\n

 <\/p>\n

October 2017: My research team won the 1st<\/sup> place in\u00a0Physionet Challenge 2017<\/a> (a.k.a. AliveCor)\u00a0among 75 teams.\u00a0Physionet<\/a> is the grand forum of \u201cComputing in Cardiology\u201d which offers free access via the web to large and growing collections of recorded physiologic signals and related open-source software.<\/strong><\/p>\n

September 2017: The Finnish science magazine Rajapinta (Interface) published an interview<\/a> with me about my Nature<\/em> – SREP<\/a> article,\u00a0“Personalized Monitoring and Advance Warning System for Cardiac Arrhythmias<\/a>“. (see in English<\/a>)<\/strong><\/p>\n

August 2017: My article<\/strong>,\u00a0Real-Time Vibration-Based Structural Damage Detection Using One-Dimensional Convolutional Neural Networks<\/em><\/a>,\u00a0<\/em><\/strong>became the\u00a0<\/strong>3rd<\/sup> most popular paper<\/strong><\/a>\u00a0of the Journal of Sound and Vibration (Elsevier)<\/em> journal<\/strong>.<\/strong><\/p>\n

July 2017: The <\/strong>PhD theses that I supervised, \u201cQuantum Cuts, A Quantum Mechanical Spectral Graph Partitioning Method for Salient Object Detection\u201d, won the Best Nordic <\/a>PhD\u00a0Thesis Award in SCIA 2017.<\/strong><\/p>\n

March 2017: Our\u00a0Journal of Sound and Vibration (Elsevier) article<\/strong>, Real-Time Vibration-Based Structural Damage Detection Using One-Dimensional Convolutional Neural Networks<\/a>,\u00a0<\/strong><\/em>became the 5th most popular paper<\/a> of the journal.<\/strong><\/p>\n

January\u00a02017: Our\u00a0IEEE Transaction article, Real-Time Patient-Specific ECG Classification by 1D Convolutional Neural Networks<\/em><\/a>\u00a0became the 5th most popular paper<\/a> of the year 2016 in IEEE Transaction on Biomedical Engineering<\/em>. \u00a0<\/strong><\/p>\n

September 2016: My research team won\u00a0the 2nd place in Physionet Challenge 2016<\/a>\u00a0among 48 teams. Physionet<\/a> is the grand forum of \u201cComputing in Cardiology\u201d which offers free access via the web to large and growing collections of recorded physiologic signals and related open-source software.\u00a0<\/strong><\/p>\n

April 2015: We got the 3rd place in\u00a0IEEE Brain-Computer Interface (BCI) Challenge@NER 2015<\/a> among 280 teams.\u00a0<\/strong><\/p>\n

2010-2015: The article, “Evolutionary Artificial Neural Networks by Multi-Dimensional Particle Swarm Optimization<\/em>“,\u00a0\u00a0is the 4th most cited paper in the Elsevier\u00a0Neural Networks journal.<\/strong><\/p>\n

September 2015: The paper, “Visual Saliency by Extended Quantum Cuts<\/em>“, was nominated for the Best Paper Award in\u00a0Int. Conf. on Image Processing, (ICIP 2015).\u00a0<\/strong><\/p>\n

August 2014: The paper, “Automatic Object Segmentation by Quantum Cuts<\/em>“, won the IBM Best Student Paper Award at Int. Conf. on Pattern Recognition (ICPR 2014).<\/strong><\/p>\n

September 2013: The paper, “QUANTUM MECHANICS IN COMPUTER VISION: AUTOMATIC OBJECT EXTRACTION<\/em>“, was nominated for the Best Paper Award in\u00a0Int. Conf. on Image Processing, (ICIP 2013).\u00a0<\/strong><\/p>\n

2014: MUVIS systems ranked 2nd in MSR-Bing Image Retrieval Challenge<\/strong><\/p>\n

2013: MUVIS solution won the 3rd place in Competition on Counter Measures to 2D Face Spoofing Attacks\u00a0 at ICB 2013<\/strong><\/p>\n

June 2013: The paper, “Evolutionary Feature Synthesis by Multi-dimensional Particle Swarm Optimization<\/em>” won the Best Paper Award at \u00a0EUVIP.<\/strong><\/p>\n

November 11, 2012: Alya Nickole Kiranyaz<\/a> was born.<\/strong><\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

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