19:00 – 19:30

Drinks Reception

19:30 – 22:30

Conference Dinner at St John’s College Main Hall

9:00 - 9:05

Welcome and Opening Remarks

9:05 – 9:50

Keynote 1- Xia Zhou, Columbia University

Title: Sensing What Matters: From Human Physiology to Trustworthy Media 

Abstract:

We live in a world where both our bodies and environments are sensed at unprecedented scale and granularity. However, the trustworthiness of sensed data is increasingly in question. Physiological sensing suffers from motion noise, user variability, and placement uncertainty, while audiovisual media is challenged by the rise of deepfakes and AI-generated content that blur the boundary between real and fake. The fundamental tension is that sensing is no longer just about acquiring signals -- it is about establishing trust.

In this talk I present our efforts to make sensing systems trustworthy by design. For human sensing, we explore everyday fabrics as a ubiquitous, continuous sensing medium. Through hardware-software co-design, we address real-world challenges such as motion noise and user diversity, enabling applications ranging from physical motion sensing to physiological monitoring for kangaroo mother care and sleep.

On sensing the physical world, we investigate embedding verifiable physical signatures directly into the environment. I will present our design of imperceptible spatiotemporal light signatures that can be projected into a scene and embedded into any video recordings, enabling verification of live speech videos without requiring compliance from recording parties. I will also discuss our ongoing effort of embedding real-time, unforgeable, and robust audio watermarks into live speech audios, enabling verification of audio integrity.

Together, these efforts point toward a sensing paradigm where trust is not inferred after the fact, but physically embedded into signals and environments from which data is captured.

9:50 – 10:30

Session 1 — Physiological Sensing for Nutrition, Metabolism, and Wellbeing

1. Not Just Where, But When: Towards Predicting Blood Glucose Rises from Passive Semantic Location

Naziha Shekh Khalil (University of Manchester), Hood Thabit (Diabetes, Endocrine and Metabolism, Centre, Manchester Royal Infirmary), Paul W. Nutter (University of Manchester), Sukru Eraslan (Middle East Technical University), Yeliz Yesilada  (Middle East Technical University), Simon Harper  (University of Manchester)

2. NutriEar: Robust Nutrition-Aware Food Classification from In-Ear Acoustic Signals

Zoey Xiaochen Tan (University of Cambridge), Yang Liu (Florida State University), Kayla-Jade Butkow (University of Cambridge), Cecilia Mascolo  (University of Cambridge)

3. Unlock the Therapeutic Potential of Music: The BEATS Dataset

Benjamin Gutierrez Serafin, Tanaya Guha, Fahim Kawsar (University of Glasgow)

4. Wearable Sweat Sensor Data Analysis: Artifact Detection and Imputation

Luca Guimont, Katayoun Farrahi, Roel Mingels (University of Southampton)

10:30 – 11.00

Coffee Break

11:00 – 11:25

Lightning Talks Group 1

1. Simplifying Commissioning & Testing of Long-Tail Mobile, Wearable & Ubiquitous Devices

James Hahn, Steve Hodges (Lancaster University)

2. Preliminary Evaluation of PPG Channel Selection and Preprocessing Parameter Sensitivity for Ear-Worn Respiratory Rate Estimation

Andong Li, Kate Farrahi, Ziwu Huang (University of Southampton)

3. Respiratory Audio Question Answering for Health Assessment Under Real-World Mobile Sensing Heterogeneity

Gaia A. Bertolino (University of Cambridge), Yuwei Zhang (University of Cambridge), Tong Xia (Tsinghua University), Domenico Talia (University of Calabria), Cecilia Mascolo (University of Cambridge)

4. Guessing Isn’t Good Enough: Privacy-Preserving Metadata Collection in Mobile Messaging

Alexandre Pauwels, Alastair R. Beresford (University of Cambridge)

5. Duet: Federated SLM–LLM Co-Inference for Mobile AI

Chunlin Tian (University of Macau), Filippo Serafini (University of Cambridge), Li Li (University of Macau), Nicholas D. Lane (University of Cambridge)

6. MORPHLING: Emulator for Distributed Machine Learning at the Edge

Leyang Xue (University of Edinburgh), Yufeng Xia  (University of Edinburgh), Eren Mendi  (University of Edinburgh), Ismaeel Bashir  (University of Edinburgh), Jiaxun Yang  (University of Edinburgh), Myungjin Lee (Cisco Research), Mahesh K. Marina  (University of Edinburgh)

11:25 – 12:30

Session 2 — Efficient Edge AI, Mobile Deployment, and Adaptive Intelligence

1. Device-Aware Distillation of Small Language Models for Efficient Edge Intelligence

Vinamra Sharma (University of Glasgow), Danilo Pau (STMicroelectronics), José Cano (University of Glasgow)

2. Towards Automated Mobile Model Deployment

Leming Shen (The Hong Kong Polytechnic University), Qiang Yang (University of Cambridge), Xinyu Huang (The Hong Kong Polytechnic University), Zijing Ma (The Hong Kong Polytechnic University), Yuanqing Zheng (The Hong Kong Polytechnic University), Chris Xiaoxuan Lu (University College London)

3. ProgRouter: Online Progress-Guided Routing for Efficient Collaborative LLM Agentic Workflows

Songyuan Li (Queen Mary University of London), Ahmed M. Abdelmoniem (Queen Mary University of London), Shiqiang Wang (University of Exeter)

4. Towards Tiny Autonomic Computing: Initial Results and Lessons Learned

Tomasz Szydlo (Newcastle University)

5. On Making AI-and-RAN Efficient and Safe

Leyang Xue, Tianxin Wang (The University of Edinburgh)

12:30 – 13:30

Lunch

13:30 – 14:20

Keynote 2 — George Malliaras, University of Cambridge 

Title: Reading the Brain and Body: New Frontiers in Surface Electrophysiology

Abstract:

Our ability to listen to the body’s electrical activity is improving at a remarkable pace. Novel recording technologies now let us capture the brain’s complex signals through miniaturised, flexible grids placed on its surface, while equally sophisticated skin-mounted sensors can track subtle physiological changes during daily life. Together, these approaches paint a richer picture of how our nervous system communicates and adapts. Applying the same ideas to the spinal cord and peripheral nerves led to the development of gentle surface electrodes that can both record and stimulate activity with surprising accuracy. Such systems can already predict how we move or even help restore control of internal organs through precise electrical cues. I will discuss how we are closing the gap between invasive and non-invasive techniques, bringing us closer to practical tools for rehabilitation, prosthetic control, and continuous health monitoring.

14:20 – 15:00

Session 3 — Trust, Privacy, and Distributed Learning

1. Anonymous Remote Attestation in Mobile Devices

Luis A. Saavedra, Alastair R. Beresford (University of Cambridge)

2. Gossip Learning in Decentralised Clinical Trials: Towards Mobile Parkinson’s Speech Biomarkers

Alexander Noble, George Roussos (Birkbeck University of London)

3. More Alignment Is Not Always More Useful in Federated Learning

Francesco Simoni (University of Bologna), Andrej Jovanović (University of Cambridge), Nicholas D. Lane (University of Cambridge)

15:00 – 15:30

Coffee Break

15:30 – 15:55

Lightning Talks Group 2 — 6 talks

1. Recording Electrocardiograms with Earables

Adam Pullin (University of Cambridge), Jake Stuchbury-Wass (University of Cambridge), Mathias Ciliberto (University of Cambridge), Kayla-Jade Butkow (University of Cambridge), Philipp Lepold (Karlsruhe Institute of Technology), Tobias Röddiger (Karlsruhe Institute of Technology), Cecilia Mascolo (University of Cambridge)

2. Efficient Dead Drop Decryption for CoverDrop

Michael C. Fink Amores, Alastair R. Beresford  (University of Cambridge)

3. Calibration-Free Blood Pressure Trend Estimation from Wearable PPG: A Feasibility Study

Yasaman Moghanloo, Tanaya Guha, Fahim Kawsar (University of Glasgow)

4. Towards Sensing with NextG Open RAN

Tianxin Wang (The University of Edinburgh)

5. The Light-Box: An Interactive Real-Time Data Visualisation Cube Display

Mitchell Banks (Lancaster University)

6. Tempora: Characterising the Time-Contingent Utility of Online Test-Time Adaptation

Sudarshan Sreeram  (University of Cambridge), Young D. Kwon (Samsung AI Center), Cecilia Mascolo  (University of Cambridge)

15:55 – 16:55

Session 4 — Wearables, Clinical Monitoring, and Sensing Infrastructure

 1. MuscleSense: Real-Time Auditory Biofeedback for Lower-Limb Exercise with Sparse Wearables
Wenbo Zhang (University College London), Jagmohan Chauhan (University College London), Zhanpeng Jin (South China University of Technology)

 2. Digital Mobility Outcomes as an Early Marker of Disease Progression in Multiple Sclerosis
Lucy Cheesman (University of Sheffield), John Mitchell (University of Sheffield), Gowtham Konduri (University of Sheffield), Gavin Brittain (Sheffield Teaching Hospitals), Ellen Buckley (University of Sheffield), Lynn Rochester (Newcastle NIHR BRC), Brian Caulfield (University College Dublin), Silvia Del Din (Newcastle NIHR BRC), Clemens Becker (Robert Bosch Krankenhaus & Heidelberg University), Carl-Philipp Jansen (Robert Bosch Krankenhaus & Heidelberg University), Walter Maetzler (Universitätsklinikum Schleswig-Holstein), Alison Yarnall (Newcastle NIHR BRC), Judith Garcia-Aymerich (IS Global), Alícia Josa-Culleré (IS Global), Gloria Dalla Costa (Harvard University), Gaßner Heiko (Uniklinikum Erlangen), Klarissa Stuerner (Universitätsklinikum Schleswig-Holstein), Beatrix Vereijken (Norges teknisk-naturvitenskapelige universitet NTNU), Clint Hansen (Christian Albrechts Universität zu Kiel), Letizia Leocani (Università Vita-Salute San Raffaele), Basil Sharrack (Sheffield Teaching Hospitals), Vita Lanfranchi (University of Sheffield), Shaoxiong Sun (University of Sheffield)

 3. Supporting Stroke Rehabilitation with Modular Electronics Prototyping Toolkits
Zaid Alhourani, Lucy Watson, Daniel Fitton, Hannah Jarvis, Steve Hodges (Lancaster University)

4. Wearable-Derived Joint Kinematics for Sleep Posture Analysis
Omar Elnaggar (Queen Mary University of London), Roselina Arelhi (University College London), Frans Coenen (University of Liverpool), Andrew Hopkinson (University of Liverpool), Paolo Paoletti (University of Liverpool)

 5. In-Network Intelligence for Low-Latency Privacy-Preserving Health Monitoring
Aristide Tanyi-Jong Akem (University of Southampton), Huiqi Yvonne Lu (University of Oxford), Noa Zilberman (University of Oxford)

6. Beyond Blind Zones: Physical Limits and Algorithmic Gaps in 5G NR Passive Sensing
Mingjie Yang (University of Glasgow), Tianxin Wang (The University of Edinburgh), Dongzhu Liu (University of Glasgow)

16:55 - 17:00

Closing Remarks