Fatemeh Kalantarifard defended her PhD Thesis on 10 June 2019. Congrats!

Fatemeh Kalantarifard defended her PhD Thesis on 10 June 2019 in the Department of Physics Seminar Room SA-240 – Bilkent University.
Her Ph.D. Thesis Defense was live streamed on 10 June 2019 at 15:30 CEST in the Raven & Fox room.

Assoc. Prof. Ömer Ilday (UNAM, Bilkent University),  Assoc. Prof. Alpan Bek (Middle-East Technical University), Assist. Prof. Burcin Ünlü (Bogazici University), Dr. Seymour Jahangirov (UNAM), Prof. Oguz Gülseren (Bilkent University) and Assist. Prof. Giovanni Volpe (Bilkent University) will be the thesis committee members.

Thesis title: Intra-cavity optical trapping with fiber laser

Thesis abstract: Standard optical tweezers rely on optical forces arising when a focused laser beam interacts with a microscopic particle: scattering forces, pushing the particle along the beam direction, and gradient forces, attracting it towards the high-intensity focal spot. Importantly, the incoming laser beam is not affected by the particle position because the particle is outside the laser cavity. Here, we demonstrate that intra-cavity nonlinear feedback forces emerge when the particle is placed inside the optical cavity, resulting in orders-of-magnitude higher confinement along the three axes per unit laser intensity on the sample. This scheme allows trapping at very low numerical apertures and reduces the laser intensity to which the particle is exposed by two orders of magnitude compared to a standard 3D optical tweezers. These results are highly relevant for many applications requiring manipulation of samples that are subject to photodamage, such as in biophysics and nano-sciences.

Thesis Advisor  Giovanni Volpe, Department of Physics, Bilkent University

Place: Physics Department seminar room (SA240), Bilkent University
Time: 10 June, 2019, 16:30 TRT (Turkey Time)

LIVE STREAMING:
Place: Meeting room Raven & Fox, Gothenburg University
Time: 10 June, 2019, 15:30 CEST

 

Martin Selin defended his Master Thesis. Congrats!

Martin Selin defended his Master thesis in Physics at Chalmers University of Technology on 5 June 2019

Title: Growing Artificial Neural Networks. Novel approaches to Deep Learning for Image Analysis and Particle Tracking

Deep-learning has recently emerged as one of the most successful methods for an- alyzing large amounts of data and constructing models from it. It has virtually revolutionized the field of image analysis and the algorithms are now being employed in research field outside of computer science. The methods do however suffer from several drawbacks such as large computational costs.

In this thesis alternative methods for training the networks underlying networks are evaluated based on gradually growing networks during training using layer-by- layer training as well as a method based on increasing network width dubbed breadth training.

These training methods lends themselves to easily implementing networks of tune- able size allowing for choice between high accuracy or fast execution or the construc- tion of modular network in which one can chose to execute only a small part of the network to get a very fast prediction at the cost of some accuracy. The layer-by-layer method is applied to multiple different image analysis tasks and the performance is evaluated and compared to that of regular training. Both the layer by layer training and the breadth training comparable to normal training in performance and in some cases slightly superior while in others slightly inferior. The modular nature of the networks make them suitable for applications within multi-particle tracking.

​Name of the master programme: MPPHYS – Physics
Supervisor: Giovanni Volpe, Department of Physics, University of Gothenburg
Examiner: Giovanni Volpe, Department of Physics, University of Gothenburg
Opponent: Henry Yang, MP Complex Adaptive Systems, Department of Physics, Chalmers University of Technology

Place: Raven & Fox room
Time: 5 June, 2019, 15:00

Adrian Leidegren defended his Master Thesis. Congrats!

Adrian Leidegren defended his Master thesis in Physics at the University of Gothenburg on 5 June 2019

Title: Estimating the validity of synthetic data using neural network ensembles

The use of synthetic data has the potential to yield unlimited amounts of resources for use in training neural networks. This is however contin- gent on finding the right parameters to use with the data-generating system. As a worst-case scenario this would be done by careful guesswork. Herein is presented an alternative that has the potential to automate this work. The Deeptrack system for particle tracking in digital video microscopy was used as a framework, due to its ability to generate synthetic data from a handful of parameters. An ensemble was trained according to one set of parameter values and tested against a set of test data generated by the same parameters except for one, which was made to vary over a wide range. To contrast this, using a new parameter set, another set of test data was generated alongside several ensembles where one parameter was varied for each ensemble’s training data.

It was found that the limiting density of discreet points as a function of the vary- ing parameter had a local minimum around the region where the variable matched the same parameter’s value in the other data set, be it training or testing. This shows the possibility of using ensembles of neural networks to identify the most suitable parameter values in Deeptrack to ensure that the synthetic training data is represen- tative of the laboratory test data. There may also be a wider use case to this technique as a means of estimating confidence in the networks’ predictions.

​Name of the master programme: Physics
Supervisor: Saga Helgadottir, Department of Physics, University of Gothenburg
Examiner: Giovanni Volpe, Department of Physics, University of Gothenburg

Place: Faraday room
Time: 5 June, 2019, 15:00

Theo Berglin & Adam Liberda defended their Master Thesis. Congrats!

Theo Berglin & Adam Liberda defended their Master thesis in Complex Adaptive Systems at Chalmers University of Technology on 31 May 2019

Title: Generation of random connectivity matrices for BRAPH

The proportion of the population suffering from neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease is increasing. Recent studies suggest that graph theory measures can be used as biomarkers in early stages of the diseases enabling researches to study spread and aiding inhibiting drug discovery. BRAPH is an object oriented and easy to use software for analyzing brain connectivity using graph theory. A bottleneck in the analyzis of brain connectivity using graph theory is a degree, strength and weight preserving randomization function. We have developed a new method with a speed improvement in the magnitude of 105 to 106 compared with the original method of Brain Connectivity Toolbox (BCT). The method is working for graphs consisting of up to 105 nodes and is verified to be equally random as the original method of BCT for sparse graphs. A speed improvement in the magnitude of 106 is equal to going from 1000 years to 8 hours.

​Name of the master programme: MPCAS – Complex Adaptive Systems
Supervisor: Giovanni Volpe, Department of Physics, University of Gothenburg
Examiner: Giovanni Volpe, Department of Physics, University of Gothenburg
Opponent: Jens Wilhelmsson, MP Complex Adaptive Systems, Department of Physics, Chalmers University of Technology

Place: Faraday room
Time: 31 May, 2019, 13:00

Kevin Andersson, Sofia Cvetkovic Destouni, Ebba Ekblom, Lilian Hee, Emil Jansson & Thomas Otting defended their Bachelor Thesis. Congrats!

Kevin AnderssonSofia Cvetkovic Destouni, Ebba EkblomLilian HeeEmil JanssonThomas Ottink defended their Bachelor Thesis at Chambers University of Technology on 29 May 2018.

Title: Agenters sökförmåga i komplexa miljöer

Abstract: Tendensen hos en aktiv Brownsk agent att svänga i en viss rikting benämns i denna studie som kiralitet och ger upphov till vad som kallas cirkulär Brownsk rörelse. Denna typ av rörelse förekommer i många både naturliga och tekniska sammanhang och har potentiella applikationer inom bland annat medicin, biologi och robotik. För att undersöka hur cirkulärt Brownska agenters sökförmåga påverkas av kiralitet utförs i detta kandidatarbete en kombination av simuleringar och experiment i olika miljöer. Simuleringarna baseras på en diskretisering av Langevins ekvationer i två rumsdimensioner och experimenten utförs med hjälp av vibrerande mikrorobotar. Studien visar att agenters sökförmåga minskar vid ökande kiralitet i homogen miljö och bestämmer kiralitetsoptimum för sökförmåga i cirkulärt begränsade miljöer. I ett fall där två agenter placeras i en cirkulärt begränsad miljö identifieras effektiva kiralitetskombinationer för korta mötestider samt en möjlig koppling mellan sökförmåga och mötestid.

Supervisors: Alessandro Magazzù & Giovanni Volpe, Department of Physics, University of Gothenburg
Examiner: Lena Falk, Department of Physics, University of Gothenburg
Opponent: Matilda Hanes & Kevin Rylander
Place: FL72
Time: 29 May, 2018, 9:35-10:20

Matilda Hanes & Kevin Rylander defended their Bachelor Thesis. Congrats!

Matilda Hanes & Kevin Rylander defended their Bachelor Thesis at Chambers University of Technology on 29 May 2018.

Title: Påvisande av kritiska Casimir-krafter i ett två-partikel-system

Abstract: 1948 upptäckte Hendrik Casimir en kraft som skulle uppkomma mellan två stycken perfekt ledande plattor. Efter detta har foskare påvisat Casimir krafter och dess analogier som kritska Casimir-krafter. Syftet med denna rapport är att påvisa kritiska Casimir-krafter för ett två-partikel-system i vatten 2,6-lutidine lösning med hjälp av optiska pincetter. I teoridelen av rapporten förklaras kritiska Casimir-krafter och Brownsk rörelse samt potentialen för en optisk fångad partikel. Simuleringar för en optisk fångad partikel används för att få en djupare förståelse för rapporten. Med metoder som ekvipartitionsmetoden, mean squared displacement method och autokorrelationsmetoden kalibreras de optiska fällorna och MATLAB används för samtliga beräkningar. Resultatet för rapporten påvisar kritiska Casimir-krafter och kalibrerar de optiska pincetterna.

Supervisors: Alessandro Magazzù & Giovanni Volpe, Department of Physics, University of Gothenburg
Examiner: Lena Falk, Department of Physics, University of Gothenburg
Opponent: Kevin Andersson, Sofia Cvetkovic Destouni, Ebba Ekblom, Lilian Hee, Emil Jansson & Thomas Ottink
Place: FL72
Time: 29 May, 2018, 9:35-10:20

Freddie Ogemark & Maximlian Leyman defended their Master Thesis. Congrats!

Freddie Ogemark & Maximlian Leyman defended their Master thesis in Complex Adaptive Systems at Chalmers University of Technology on 14 June 2018

Title: Cooperative Robotics with Sensorial Delay

The purpose of this work is to study how the behaviour of robots changes when the data from their sensors is affected by a certain delay. Robots of the model Elisa-3 were therefore studied while performing Brownian motion and with certain features varying as a function of the intensity measured by its sensors. Introducing a delay and varying its sign is shown to have a significant effect on a robot’s behavior. A single robot moving in an intensity field is either drawn to or avoiding higher inten- sities for a positive or a negative delay respectively. In this case experimental data show good agreement with simulated behavior. Simulations also show that multi- ple robots should form clusters when interacting under the influence of a positive delay; however, only weak tendencies towards cluster formation can be seen in the experiments.

​Name of the master programme: MPCAS – Complex Adaptive Systems
Supervisor: Giovanni Volpe, Department of Physics, University of Gothenburg
Examiner: Giovanni Volpe, Department of Physics, University of Gothenburg
Opponents: Andres Hansson & Richard Sundqvist, MP Complex Adaptive Systems, Department of Physics, Chalmers University of Technology

Place: ES51, EDIT building
Time: 14 June, 2018, 17:00

 

 

Frida Brogren, Kirill Danilov, Klas Holmgren, Oskar Leinonen, Benjamin Midtvedt & Arian Rohani defended their Bachelor Thesis. Congrats!

Frida Brogren, Kirill Danilov, Klas Holmgren, Oskar Leinonen, Benjamin Midtvedt & Arian Rohani defended their Bachelor Thesis at Chambers University of Technology on 25 May 2018.

Title: Experimentell studie av kritiska fenomen med optiska pincetter

Abstract: I samband med nanoteknologins framfart ses ett växande intresse för kolloida sy- stem för att överkomma många svårigheter med konstruktionen av nanostrukturer. På grund av kritikalitetens skalinvarianta egenskaper kan kolloider användas som analo- ger för nanopartiklar i studier av kritiska fenomen. Detta arbete ämnar att undersöka och utvidga förståelsen av kritiska fluktuationer och kritiska Casimirkrafter, som kan användas för att binda och styra kolloider. En optisk pincett byggdes för att undersö- ka kritisk motorisering och kolloida aggregationer, medan en färdigbyggd holografisk pincett användes för att mäta kritiska Casimirkrafter. De motoriserade kolloiderna uppvisade mer kaotisk rörelse för högre lasereffekter, och de kritiska Casimirkrafterna visades växa skarpt i närheten av den kritiska temperaturen.

Supervisors: Alessandro Magazzù & Giovanni Volpe, Department of Physics, University of Gothenburg
Examiner: Lena Falk, Department of Physics, University of Gothenburg
Opponent: Markus Fällman, Gabriella Grenander, Oskar Holmstedt, Viktor Olsson, Maria Söderberg & Wilhelm Tranheden
Place: FL62
Time: 25 May, 2018, 11:05-11:50

Markus Fällman, Gabriella Grenander, Oskar Holmstedt, Viktor Olsson, Maria Söderberg & Wilhelm Tranheden defended their Bachelor Thesis. Congrats!

Markus Fällman, Gabriella Grenander, Oskar Holmstedt, Viktor Olsson, Maria Söderberg & Wilhelm Tranheden defended their Bachelor Thesis at Chambers University of Technology on 25 May 2018.

Title: Sökstrategier i komplexa miljöer – Påverkan av kiralitet på aktiva agenters sökförmåga i komplexa miljöer

Abstract: I en framtid där autonoma agenter sannolikt kommer spela en betydande roll är utveck- lingen av enkla sökstrategier relevant. Ett specialfall av sådana är sökning utan återkopp- ling från miljön, något som kan vara viktigt för enkla agenter med begränsad datorkraft. Kiralitet är ett fenomen som i applikationer ofta ses som en olägenhet hos sådana agen- ter. Det är en asymmetri hos agenten som leder till att dess rörelse roterar åt ett visst håll. Detta beteende är vanligt inom robotik, men har även observerats inom kemi och biologi, till exempel hos olika mikroorganismer. Influensen av kiralitet på prestationen hos sökstrategier är i hög grad okänd. Studier saknas på huruvida kiralitet kan förbättra prestationen för agenter utan miljöåterkoppling och, om så är fallet, i vilken sorts miljöer som denna positiva effekt uppstår.
Genom datorsimuleringar och robotexperiment har vi funnit att kiralitet kan ha en positiv effekt på aktiva agenters sökförmåga i både regelbundna och stokastiska miljöer och med olika grad av stokastiskt brus som påverkar agenternas rörelse. Vi visar också att det finns en positiv relation mellan existensen av hörn i miljön och den relativa prestationen av kiral rörelse.
Våra resultat är relevanta för den som är intresserad av att manipulera eller förstå rörelsen hos kirala agenter i komplexa miljöer. Resultaten är också relevanta för vidare forskning riktad mot potentiella implementationer inom till exempel robotik och mikroteknik.

Supervisor: Giovanni Volpe, Department of Physics, University of Gothenburg
Examiner: Lena Falk, Department of Physics, University of Gothenburg
Opponent: Frida Brogren, Kirill Danilov, Klas Holmgren, Oskar Leinonen, Benjamin Midtvedt & Arian Rohani
Place: FL62
Time: 25 May, 2018, 10:15-11:00

Mite Mijalkov defended his PhD Thesis. Congrats!

Mite Mijalkov defended his PhD Thesis on 24 April 2018 in the Physics Department seminar room (SA240).

Assoc. Prof. Hande Toffoli (Middle-East Technical University), Prof. Tayfun Ozcelik (Bilkent University), Assoc. Prof. Alpan Bek (Middle-East Technical University), Assist. Prof. Seymur Cahangirov (Bilkent Unievrsity) and Assist. Prof. Giovanni Volpe (Bilkent University) will be the thesis committee members.

Thesis title: Graph Theory Study of Complex Networks in the Brain

Thesis abstract: The brain is a large-scale, intricate web of neurons, known as the connectome. By representing the brain as a network i.e. a set of nodes connected by edges, one can study its organization by using concepts from graph theory to evaluate various measures. We have developed BRAPH – BRain Analysis using graPHtheory, a MatLab, object-oriented freeware that facilitates the connectivity analysis of brain networks. BRAPH provides user-friendly interfaces that guide the user through the various steps of the connectivity analysis, such as, calculating adjacency matrices, evaluating global and local measures, performing group comparisons by non-parametric permutations and assessing the communities in a network. Furthermore, using graph theory, we showed that structural MRI undirected networks of stable MCI (sMCI) subjects, late MCI converters (lMCIc), early MCI converters (eMCIc), and AD patients show abnormal organization. This is indicated, at global level, by decreases in clustering and transitivity accompanied by increases in path length and modularity and, at nodal level, by changes in nodal clustering and closeness centrality in patient groups when compared to controls. In samples that do not exhibit differences in the undirected analysis, we propose the usage of directed networks to assess any topological changes due to a neurodegenerative disease. We demonstrate that such changes can be identified in Alzheimer’s and Parkinson’s patients by using directed networks built by delayed correlation coefficients. Finally, we put forward a method that improves the reconstruction of the brain connectome by utilizing the delays in the dynamic behavior of the neurons. We show that this delayed correlationmethod correctly identifies 70% to 80% of the real connections in simulated networks and performs well in the identification of their global and nodal properties.

Name of the PhD programme: Material Science and Nanotechnology Graduate Program
Thesis Advisor  Giovanni Volpe, Department of Physics, Bilkent University

Place: Physics Department seminar room (SA240), Bilkent University
Time: 24 April, 2018, 11:00