Jaume Anguera Peris

Hi there, curious minds! I'm Jaume. If you're up for a dance of intellects and a symphony of ideas, check out my latest research. And if you're feeling the spark of collaboration, reach out without a hint of hesitation. Let's create scholarly magic together!

Curious to learn a bit more about me? I am currently a PhD student in the Information Science and Engineering Division under the supervision of Prof. Joakim Jaldén and Prof. Mats Bengtsson. I am also affiliated with the Wallenberg AI, Autonomous Systems and Software Program (WASP) under a research project between KTH and SciLifeLab. My research interests are drawn to engineering problems that require a combination of interdisciplinary science fields, including the mathematical modelling of Poisson Voronoi tessellations, the modelling of stochastic networks and the modelling of cell behaviour in bright-field imaging.

I received my master's degree in Information and Network Engineering '19 from KTH - Royal Institute of Technology, and my bachelor's degree in Telecommunications Systems Engineering '16 from UPC - ETSETB TelecomBCN. During my undergraduate studies, I had the opportunity to be a visiting scholar in the Department of Electrical and Computer Engineering at Northeastern University, and participate in several research projects, including,

- Deep learning for differential privacy and density estimation (2019, pdf)

- Deep learning-based decoding algorithms for identification systems (2018)

- Distributed multi-target tracking in a Wireless Sensor Network using diffusion strategies and adaptive combiners (2016)

- Image recognition for avoiding collisions in a swarm of nanosatellites (2016)

Upon completing my bachelor's thesis, I worked as a software developer and test automation engineer at Roche Diagnostics.

My current research focuses on (1) modelling multi-cellular systems supporting edge video analytics, (2) building automated AI decision-support models for the development of large-scale microscopy, and (3) tracking cells on microscopy images leveraging the tools of convex optimization, stochastic geometry, and deep learning.

As part of my teaching activities during my PhD, I am grateful to serve / have served as a teaching assistant for the courses EP1200 Introduction to Computing Systems Engineering, EQ2300 Digital Signal Processing, and EQ2443 Project in Information Engineering. Besides, I supervise master thesis students on a variety of topics related to my research interests, including,

-Amit Choudhary, Designing Efficient Indoor WiFi Mesh Networks: A Layered Approach to Performance Optimization (April 2025)

-Hang Qin, Qi Xiong, Siyi Qian, Siyue Huang, Chenting Zhang, Cell feature extraction in brightfield images (December 2023)

-Menglu Chen, Pengzhan Jiang, Ebba Lindstedt, Alva Johansson Staaf, Pia Appelquist, Network simulator for indoor WiFi Mesh (December 2023)

-Ayush Bhat, Evaluation and Implementation of Audio Repeater Nodes using Bluetooth LE Audio (October 2023, pdf)

-Asawari Joshi, Selecting a service mesh implementation for managing microservices (October 2022, pdf)

-Tatiana Barrios Montenegro, Congestion control with service mesh for Edge-Cloud traffic (October 2022, pdf)

-Beatrice Lovely, Solving e-scooter safety problems with multi-modal, privacy-preserving sensor technology and machine learning (June 2022, pdf)

-Zihan Wang, Performance evaluation of serverless edge computing for AI applications (June 2022, pdf)

-Jing Xia, Network simulation for the monitoring of water distribution infrastructure (December 2021, pdf)

-Nicola Fiorello, A cloud-based business process automation platform for customer interaction (August 2021, pdf)