The bio’s for students from the 2016 cohort are listed below.
I am a PhD student under the supervision of Prof. Thomas Parasini with the Control and Power Group in the Department of Electrical and Electronic Engineering. My research focuses on fault tolerant and secure control system, with particular attention to threats coming from the cyber domain and impacting the physical behaviour of such systems. The goal is to design detection mechanisms and countermeasures that exploit the knowledge of the underlying dynamical model.
Prior to joining Imperial College London, I graduated in Electrical and Control Engineering at University of Trieste, Italy.
Following PCSI and PC classes préparatoires at the Lycée Janson de Sailly (Paris), I have obtained a Diplôme d’Ingénieur in Embedded Systems at ECE Paris in France. I also obtained an MSc in Advanced Software Development at University of Kent and an MRes in Medical Robotic and Image Guided Intervention at Imperial College London in the UK.
I am currently a PhD candidate with the Hamlyn Centre, supervised by Prof. Yang and Dr. Lo. The main focus of my research is the development of wearable devices to continuously monitor vascular parameters, with a strong emphasis on clinical translation. The main clinical application is the postoperative monitoring of transferred soft tissue.
I am a PhD candidate in the HiPEDs CDT program at Imperial College London. I am in the Neural Reckoning Group and Custom Computing Research Group. My interests lies in the high-performance simulation of auditory systems with spiking neural networks. Currently we are focusing on the auditory binding problem with spike coding models. My Bachelor’s and Master’s degrees are both on computer science.
I am a PhD student in the Department of Computing under the supervision of Dr. Antonio Filieri. I am working on techniques that could dramatically decrease the effort needed to debug complex software systems by providing to the developers helpful insights about the genesis of an erroneous behaviour. I am tackling this problem using logic-based formal approaches, and I am motivated also by my previous professional experience as a software engineer in the insurance industry.
Faheem is currently a Ph.D. candidate in the Department of Electrical and Electronics Engineering, Imperial College London working under the supervision of Dr. Kin K. Leung. He is currently working on the application of Optimization Theory and Game Theory to Communication Networks.
He received his Masters in Computer and Information Technology from Purdue University, West Lafayette, USA in 2016. His research interests lie in the area of wireless communication, Internet of Things, and indoor localization.
I am interested in high-performance data analytic systems. With years of experience in industry, my focus is on making data systems efficient and scalable for exploration. This includes hardware-software co-design for efficient data analytics on novel architectures, as well as designing tools with high-level abstractions (e.g. for parallelism, sampling, etc.) that facilitates analyzing massive scientific and business data.
I received my M.Eng degree in Computer Engineering and Informatics from University of Patras in Greece, where I also led the University’s Robotics Club during 2014-2016. Currently I am a Ph.D. Candidate in the Intelligent Digital Systems Lab of the Department of Electrical and Electronic Engineering at Imperial College London, under the supervision of Dr. Christos-Savvas Bouganis.
My current research focuses on high-performance systems (hardware and software) for mobile robots and intelligent unmanned aerial vehicles (UAVs). I am interested on custom FPGA architectures implementing Machine Learning algorithms (such as Convolutional Neural Networks-CNNs), targeting applications of autonomous robotic systems, such as autonomous drone navigation and obstacle avoidance. In the past I have also focused on Human-Robot Interaction (Collision detection and avoidance), autonomous mobile robots for fast and accurate line following, as well as in High-Performance Computing targeting numerical linear algebra kernels and kernels for data mining.
Riccardo Moriconi is a PhD student on Bayesian Optimization at the Statistical Machine Learning group under the supervision of Marc Deisenroth.
His research focuses on scaling Bayesian Optimization methods to high dimensional settings. Bayesian optimization is concerned with optimizing black-box performances of parameter configurations. It is usually referred to as data-efficient optimization as evaluation of parameters is usually expensive and limited in the number of trials. Previously he obtained his master degree in Robotics Systems and Control at ETH Zurich and procured a bachelor degree at the Politechnic of Milan in Automation Engineering.
I am currently a 2nd year Ph.D. student in the Custom Computing Research Group at Imperial College London, under the supervision of Professor Wayne Luk. I received my bachelor of Computer Engineering and MPhil at The University of Hong Kong in 2012 and 2016 under the supervision of Dr. Hayden So. My current research interests are the reconfigurable acceleration of short reads mapping, single-cell analytic and design productivity of FPGA.
Pablo Ortega San Miguel
Pablo is interested in machine learning algorithms that improve brain function monitoring using non-invasive and portable devices as EEG and fNIRS. He works on the application of Bayesian filters to monitor cortical activation during complex and naturalistic motor learning tasks. Pablo is PhD student in the High Performance Embedded and Distributed Systems centre for doctoral training under the EPSRC scheme.
I am a PhD in the Biomedical Image Analysis (BioMedIA) group under the supervision of Ben Glocker. My research broadly touches the application of deep learning to medical images. Currently I am mainly focusing on Bayesian deep learning to integrate reliable uncertainty measure into various models.
Before joining Imperial, I studied for a BSc in Physics at the Humboldt-University Berlin and University of Leeds. I obtained a MSc in Artificial Intelligence from the University of Edinburgh and joined the Broad Institute of MIT and Harvard for my MSc project.
I work within the Software Performance Optimisation group, under the supervision of Professor Paul Kelly. My research focus is on enabling FPGA acceleration within popular object-oriented languages, via novel metaprogramming extensions. I came to Imperial after working in London as a software developer, previously graduating with an MSci in Physics.
I am a PhD student in the Department of Computing and I am affiliated with both the iBUG and GLAM groups under the supervision of Dr. Bjoern Schuller and Dr. Stefanos Zafeiriou. I hold a MEng from the Department of Informatics and Telecommunication Engineering (University of Western Macedonia) and a Master’s from the Computer Science Department (University of Crete). My research interests lie in the areas of deep learning, emotion recognition, and multimodal phenomena. For example, one of my work involved the use of audio and visual information to train a deep neural network to recognise emotions.