For a complete list, please visit my Google Scholar or Semantic Scholar profiles.

Pre-prints

MELTing point: Mobile Evaluation of Language Transformers
Stefanos Laskaridis, Kleomenis Katevas, Lorenzo Minto, Hamed Haddadi
[arXiv, code]

2022

Demo: FLaaS - Enabling Practical Federated Learning on Mobile Environments.
Kleomenis Katevas, Diego Perino, Nicolas Kourtellis
At the 20th ACM International Conference on Mobile Systems, Applications, and Services (MobiSys '22).
[pdf]

Demo: FLaaS - Practical Federated Learning as a Service for Mobile Applications.
Kleomenis Katevas, Diego Perino, Nicolas Kourtellis
At the 23rd Annual International Workshop on Mobile Computing Systems and Applications (HotMobile '22).
[pdf]

2021

BatteryLab: A Collaborative Platform for Power Monitoring
Matteo Varvello, Kleomenis Katevas, Mihai Plesa, Hamed Haddadi, Fabian Bustamante, Benjamin Livshits
At the Passive and Active Measurement Conference (PAM) 2022.
[arXiv]

Choosing the Best of All Worlds: Accurate, Diverse, and Novel Recommendations through Multi-Objective Reinforcement Learning
Dušan Stamenković, Alexandros Karatzoglou, Ioannis Arapakis, Xin Xin, Kleomenis Katevas
At the 15th International Conference on Web Search and Data Mining (WSDM '22).
[arXiv]

PPFL: Privacy-preserving Federated Learning with Trusted Execution Environments
Fan Mo, Hamed Haddadi, Kleomenis Katevas, Eduard Marin, Diego Perino, Nicolas Kourtellis
At the 19th ACM International Conference on Mobile Systems, Applications, and Services (MobiSys '21).
[arXiv, teaser, talk, code] Best Paper Award

2020

FLaaS: Federated Learning as a Service
Nicolas Kourtellis, Kleomenis Katevas, Diego Perino
At the 1st Workshop on Distributed Machine Learning (DistributedML 2020), Barcelona, Spain, December 2020.
[arXiv, talk]

DarkneTZ: Towards Model Privacy on the Edge using Trusted Execution Environments
Fan Mo, Ali Shahin Shamsabadi, Kleomenis Katevas, Soteris Demetriou, Ilias Leontiadis, Andrea Cavallaro, Hamed Haddadi
At the 18th ACM International Conference on Mobile Systems, Applications, and Services (MobiSys '20), Toronto, Canada, June 2020.
[arXiv, code, talk]

A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics
Seyed Ali Osia, Ali Shahin Shamsabadi, Sina Sajadmanesh, Ali Taheri, Kleomenis Katevas, Hamid R. Rabiee, Nicholas D. Lane, Hamed Haddadi
IEEE Internet of Things (IoT) Journal, 2020.
[arXiv, code]

2019

Poster: Towards Characterizing and Limiting Information Exposure in DNN Layers
Fan Mo, Ali Shahin Shamsabadi, Kleomenis Katevas, Andrea Cavallaro, Hamed Haddadi
At the 26th ACM Conference on Computer and Communications Security (CCS '19), London, UK, November 2019.
[pdf]

BatteryLab, A Distributed Power Monitoring Platform For Mobile Devices
Matteo Varvello, Kleomenis Katevas, Mihai Plesa, Hamed Haddadi, Benjamin Livshits
At the 18th ACM Workshop on Hot Topics in Networks (HotNets '19), Princeton, New Jersey, USA, November 2019
[pdf]

Demo Abstract: BatteryLab, A Distributed Power Monitoring Platform For Mobile Devices
Matteo Varvello, Kleomenis Katevas, Wei Hang, Mihai Plesa, Hamed Haddadi, Fabian E. Bustamante, Benjamin Livshits
At the 17th ACM Conference on Embedded Networked Sensor Systems (SenSys '19), New York, November 2019
[pdf, poster, flyer] Best Demo Award

Finding Dory in the Crowd: Detecting Social Interactions using Multi-Modal Mobile Sensing
Kleomenis Katevas, Katrin Hänsel, Richard Clegg, Ilias Leontiadis, Hamed Haddadi, Laurissa Tokarchuk
At the 1st Workshop on Machine Learning on Edge in Sensor Systems (SenSys-ML '19) in conjunction with ACM SenSys '19, New York, NY, USA, November 2019
[pdf]

Deep Private-Feature Extraction
Seyed Ali Osia, Ali Shahin Shamsabadi, Ali Taheri, Kleomenis Katevas, Hamed Haddadi, Hamid R. Rabiee
In IEEE Transactions on Knowledge and Data Engineering (TKDE '19), 2019.
[pdf, code]

2018

Typical Phone Use Habits: Intense Use Does Not Predict Negative Well-Being
Kleomenis Katevas, Ioannis Arapakis, Martin Pielot
At the 20th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI '18), Barcelona, Spain, September 2018
[pdf, presentation, blog post]

Position Paper: The Potential of Wearable Tech to Monitor Social Interactions through Interpersonal Synchrony Detection
Katrin Hänsel, Kleomenis Katevas, Guido Orgs, Daniel C. Richardson, Akram Alomainy, Hamed Haddadi
At the 4th Workshop on Wearable Systems and Applications (WearSys '18) in conjunction with ACM MobiSys 2018, Munich, Germany, June 2018
[pdf]

2017

Beyond Interruptibility: Predicting Opportune Moments to Engage Mobile Phone Users
Martin Pielot, Bruno Cardoso, Kleomenis Katevas, Joan Serrà, Aleksandar Matic, Nuria Oliver
In ACM UbiComp '17, Maui, Hawaii, September 2017
[pdf, presentation, blog post]

Continual Prediction of Notification Attendance with Classical and Deep Network Approaches
Kleomenis Katevas, Ilias Leontiadis, Martin Pielot, Joan Serrà
Technical Report
[arXiv]

Practical Processing of Mobile Sensor Data for Continual Deep Learning Predictions
Kleomenis Katevas, Ilias Leontiadis, Martin Pielot, Joan Serrà
At the 1st International Workshop on Embedded and Mobile Deep Learning in conjunction with ACM MobiSys 2017, Niagara Falls, NY, USA, June 2017
[pdf, presentation]

Demo: Detecting Group Formations using iBeacon Technology
Kleomenis Katevas, Laurissa Tokarchuk, Hamed Haddadi, Richard G. Clegg, Muhammad Irfan
In ACM MobiSys 2017, Niagara Falls, NY, USA, June 2017
[pdf, poster, demo]

Effective patient–clinician interaction to improve treatment outcomes for patients with psychosis: a mixed-methods design
Stefan Priebe, Eoin Golden, David Kingdon, Serif Omer, Sophie Walsh, Kleomenis Katevas, Paul McCrone, Sandra Eldridge, Rose McCabe
In Programme Grants Appl Res 2017;5(6)
[pdf]

Privacy-Preserving Deep Inference for Rich User Data on The Cloud
Seyed Ali Osia, Ali Shahin Shamsabadi, Ali Taheri, Kleomenis Katevas, Hamid R. Rabiee, Nicholas D. Lane, Hamed Haddadi
[arXiv]

2016

Detecting Group Formations using iBeacon Technology
Kleomenis Katevas, Hamed Haddadi, Laurissa Tokarchuk, Richard G. Clegg
At the 4th International Workshop on Human Activity Sensing Corpus and Application (HASCA 2016) in conjunction with ACM UbiComp 2016, Heidelberg, Germany, September 2016
[pdf, presentation]

SensingKit: Evaluating the Sensor Power Consumption in iOS devices
Kleomenis Katevas, Hamed Haddadi, Laurissa Tokarchuk
At the 12th International Conference on Intelligent Environments (IE'16), London, UK, September 2016
[pdf]

2015

Robot Comedy Lab: Experimenting with the Social Dynamics of Live Performance
Kleomenis Katevas, Patrick G.T. Healey, Matthew Tobias Harris
In Frontiers in Psychology 6:1253, August 2015
[pdf, web]

Walking in Sync: Two is Company, Three’s a Crowd
Kleomenis Katevas, Hamed Haddadi, Laurissa Tokarchuk, Richard G. Clegg
At the 2nd Workshop on Physical Analytics (WPA) in conjunction with ACM MobiSys 2015, Florence, Italy, May 2015
[pdf, presentation, blog post]

2014

Robot Stand-up: Engineering a Comic Performance
Kleomenis Katevas, Patrick G.T. Healey, Matthew Tobias Harris
In Proceedings of the 2014 Workshop on Humanoid Robots and Creativity at the 2014 IEEE-RAS International Conference on Humanoid Robots (Humanoids 2014), Madrid, Spain, November 2014
[pdf, source code]

Poster: SensingKit — A Multi-Platform Mobile Sensing Framework for Large-Scale Experiments
Kleomenis Katevas, Hamed Haddadi, Laurissa Tokarchuk
In ACM MobiCom 2014, Maui, Hawaii, September 2014
[pdf, poster, web]

Thesis

Analysing Crowd Behaviours using Mobile Sensing
Ph.D. in Computer Science, Queen Mary University of London, UK
Supervisors: Dr. Laurissa Tokarchuk and Prof. Hamed Haddadi
Examiners: Prof. Mirco Musolesi and Prof. Ioannis Patras

The Sense of Collaborative Virtual Touch
M.Sc. in Software Engineering, Queen Mary University of London, UK
Supervisor: Prof. Patrick G.T. Healey

Smart House: House Automation System
B.Sc. in Informatics Engineering, University of Applied Sciences of Thessaloniki, Greece
Supervisor: Prof. Konstantinos I. Diamantaras

Patents

Method and System for Tracking and Quantifying Visual Attention on a Computing Device
Kleomenis Katevas, Ioannis Arapakis, Eduard Gimenez Funes
(Filed Oct. 14, 2021)

Privacy Preserving Peer-to-Peer Machine Learning
Panagiotis Papadopoulos, Ioannis Arapakis, Kleomenis Katevas
(Filed Oct. 5, 2021)

Federated Learning for Preserving Privacy
Nicolas Kourtellis, Diego Perino, Kleomenis Katevas, Eduard Marin Fabregas, Fan Mo
(Filed Apr. 27, 2021)

Federated Machine Learning as a Service
Nicolas Kourtellis, Kleomenis Katevas, Diego Perino
(Filed Jan. 15, 2021)