I work as a Principal Research Scientist in the Pervasive Systems Department at Nokia Bell Labs in Cambridge, UK. I am a member of the ACM Future of Computing Academy (FCA) and serve on the Editorial Board of ACM IMWUT journal as an Associate Editor. I am currently also a Visiting Industrial Fellow at the Department of Computer Science and Technology at the University of Cambridge. I finished my Ph.D. in Computer Science at the University College London under the supervision of Dr. Nic Lane and Prof. Nadia Berthouze. I also hold a Masters in Computer Science from the University of Toronto and a B.Tech. from DA-IICT where I was awarded the President's Gold Medal.

My current research focus is on developing techniques to improve the scalability and robustness of deep learning algorithms on edge devices. I have also done substantial research in the areas of Ubiquitous Computing, Human-Computer Interaction, and ICT4D. I am a recipient of the Wolfond Fellowship at the University of Toronto, the mBillionth Award South Asia, and two Best Paper Honorable Mention Awards. My research has been covered by several media organizations including the New Yorker, Financial Times, Livemint and Canadian Broadcasting Corporation.

Embedded Deep Learning

Domain Adaptation

Mobile Sensing and Systems

Ubiquitous Computing


  • September 2020: We released LibriAdapt, a large-scale speech dataset to facilitate research in domain adaptation.
  • August 2020: Our paper on unsupervised domain adaptation under label space mismatch is accepted at Interspeech 2020.
  • August 2020: I am chairing the Industry Track for IEEE Percom 2021. Please consider submitting a paper.
  • July 2020: I am serving on the Program Committee of ACM/IEEE IPSN 2021, which is a part of the CPS-IoT Week 2021.
  • May 2020: I was interviewed by the ACM Ubiquity magazine about my research, and how it contributes to the vision of Equitable Computing.
  • February 2020: I will be serving on the Editorial Board of ACM IMWUT as an Associate Editor.
  • February 2020: Our paper, introducing a new speech dataset for domain adaptation, has been accepted at ICASSP 2020.
  • February 2020: Our paper on unsupervised domain adaptation for HAR has been accepted at IMWUT 2020.
  • October 2019: I have been selected as a member of the ACM Future of Computing Academy (FCA). Excited! .


[P44] Mathur A., Berthouze N., Lane N.D. "Unsupervised Domain Adaptation under Label Space Mismatch for Speech Classification". Interspeech 2020.

[P43] Beutel, D.J., Topal, T., Mathur A., Qiu, X., Parcollet, T. and Lane, N.D. Flower: A Friendly Federated Learning Research Framework. arXiv preprint arXiv:2007.14390.

[P42] Mathur A., Kawsar F., Berthouze N., Lane N.D. "LIBRI-ADAPT: A new speech dataset for unsupervised domain adaptation". IEEE ICASSP 2020.

[P41] Chang Y., Mathur A., Isopoussu A., Song J., Kawsar F. "A Systematic Study of Unsupervised Domain Adaptation for Robust Human-Activity Recognition". ACM IMWUT 2020.

[P40] Mathur A., Isopoussu A., Kawsar F., Berthouze N., Lane N.D. "FlexAdapt: Flexible Cycle-Consistent Adversarial Domain Adaptation". IEEE International Conference on Machine Learning and Applications, 2019.

[P39] Gong T., Ramos A.G.C.P, Bhattacharya S., Mathur A., Kawsar F. "AudioDOS: Real-Time Denial-of-Service Adversarial Attacks on Deep Audio Models". IEEE International Conference on Machine Learning and Applications, 2019.

[P38] Min C., Montanari A., Mathur A., and Kawsar F. "A Closer Look at Quality-Aware Runtime Assessment of Sensing Models in Multi-Device Environments", ACM Sensys 2019.

[P37] Antonini M., Vu T., Min C., Montanari A., Mathur A., and Kawsar F. "Resource Characterisation of Personal-Scale Sensing Models on Edge Accelerators", AIChallengeIoT, ACM SenSys 2019.

[P36] Mathur A., Isopoussu A., Berthouze N., Lane N.D., Kawsar F. "Unsupervised Domain Adaptation for Robust Sensory Systems". CML-IoT, Ubicomp 2019, London, UK.

[P35] Min C., Mathur A., Montanari A., Kawsar F. "An Early Characterisation of Wearing Variability on Motion Signals for Wearables". ISCW 2019, London, UK.

[P34] Wang C., Olugbade T., Mathur A., Williams A., Berthouze N., Lane N.D. "Recurrent Network based Automatic Detection of Chronic Pain Protective Behavior using MoCap and sEMG data". ISCW 2019, London, UK.

[P33] Katayama S., Mathur A., van den Broeck M., Okoshi T., Nakazawa J., Kawsar F. "Situation-Aware Emotion Regulation of Conversational Agents with Kinetic Earables". ACII 2019, Cambridge, UK.

[P32] Mathur A., Isopoussu A., Kawsar F., Berthouze N., Lane N.D. "Mic2Mic: Using Cycle-Consistent Generative Adversarial Networks to Overcome Microphone Variability in Speech Systems". IPSN 2019, Montreal, Canada.

[P31] Mathur A., Kawsar F., Berthouze N., Lane N.D. "A Vision for Adaptive and Generalizable Audio-Sensing Systems". To Appear in SocialSense @ IPSN 2019.

[P30] Lee S., Min C., Montanari A., Mathur A. , Chang Y., Song J. and Kawsar F. "Automatic Smile and Frown Recognition with Kinetic Earables". The 10th Augmented Human International Conference (AH 2019), Reims Champagne-Ardenne, France.

[P29] Kawsar F., Min C., Mathur A. , Montanari A. "Earables for Personal-scale Behaviour Analytics", IEEE Pervasive Computing, Volume: 17, Issue: 3, 2018.

[P28] Mathur A., Isopoussu A., Kawsar F., Smith R., Lane N.D. and Berthouze N. "On Robustness of Cloud Speech APIs: An Early Characterization". In HASCA Workshop @ Ubicomp 2018.

[P27] Min C., Montanari A., Mathur A., Lee S., and Kawsar F. "Cross-Modal Approach for Conversational Well-being Monitoring with Multi-Sensory Earables", In Computing for WellBeing Workshop @ Ubicomp 2018.

[P26] Min C., Mathur A., Kawsar F. "Exploring Audio and Kinetic Sensing on Earable Devices", In WearSys Workshop @ Mobisys 2018.

[P25] Min C., Mathur A., Kawsar F. "Audio-Kinetic Model for Automatic Dietary Monitoring with Earable Devices", Mobisys 2018.

[P24] Mathur A., Zhang, T., Bhattacharya, S., Veličković, P., Joffe, L., Lane, N. D., Kawsar F, Lió, P. "A Deep Data Augmentation Training Method to Address Software and Hardware Heterogeneities in Wearable and Smartphone Sensing Devices”. IPSN 2018, Porto, Portugal.

[P23] Mathur A., Lane, N. D., Bhattacharya, S., Boran, A., Forlivesi, C., Kawsar, F. "DeepEye: Resource efficient local execution of multiple deep vision models using wearable commodity hardware". ACM Mobisys 2017.

[P22] Lane, N. D., Bhattacharya, S., Mathur A., Georgiev, P., Forlivesi, C., Kawsar, F. "Squeezing Deep Learning into Mobile and Embedded Devices". IEEE Pervasive Magazine 2017.

[P21] Mathur A., Kalanadhabhatta L.M., Majethia R., Kawsar F. "Moving Beyond Market Research: Demystifying Smartphone User Behavior in India". ACM IMWUT/Ubicomp 2017.

[P20] Lane, N., Bhattacharya, S., Mathur A., Forlivesi, C., Kawsar, F. "Dxtk: Enabling resource-efficient deep learning on mobile and embedded devices with the DeepX toolkit". EAI MobiCase 2016.

[P19] Mashhadi, A., Mathur A., Van den Broeck, M., Vanderhulst, G., Kawsar, F. "Understanding the impact of personal feedback on face-to-face interactions in the workplace". ACM ICMI 2016. (Best Paper Nominee)

[P18] Mathur A., Lane N.D., Kawsar F. "Engagement-aware computing: Modelling user engagement from mobile contexts”. ACM Ubicomp 2016.

[P17] Mathur A., Kawsar F. "The Need to Account for Geographical Diversities in Mobile Data Research”. MobiData @ MobiSys 2016.

[P16] Montanari A., Mashhadi A., Mathur A., Kawsar F. "Understanding the Privacy Design Space for Personal Connected Objects”. ACM BritishHCI 2016.

[P15] Mathur A., Broeck M., Vanderhulst G., Mashhadi A., and Kawsar F. "Tiny Habits in the Giant Enterprise: Understanding the Dynamics of a Quantified Workplace". ACM UbiComp 2015.

[P14] Mathur A., Broeck M., Vanderhulst G., Mashhadi A., and Kawsar F. "Quantified Workplace: Opportunities and Challenges". Physical Analytics Workshop @ MobiSys 2015.

[P13] Mashhadi A., Mathur A., Kawsar F. The Myth of Subtle Notifications. ACM Ubicomp 2014.

[P12] Mathur A., Jaiswal S. Exploring the Interplay between Community Media and Mobile Web in Developing Regions. ACM MobileHCI 2013. (Best Paper Honorable Mention Award)

[P11] Mathur A., Agarwal S., Jaiswal S. Exploring Playback and Recording of Web-based Audio Media on Low-End Feature Phones. ACM DEV 2012.

[P10] Samdaria N., Mathur A., Balakrishnan R. Paying in Kind for Crowdsourcing Work in Developing Regions. Pervasive 2012 (Best Paper Nominee)

[P9] Kumar N., Mathur A., Lal S. Banking 101: Mobile-izing financial inclusion in an emerging India. Bell Labs Technical Journal, Human Sciences and User Experience Edition, 2012

[P8] Mathur A., Majumder A., Datta S., Menon S. LifeView: A Lifelog Visualization Tool for Supporting Sentimental Recall and Sharing. ACM OzCHI 2012

[P7] Mathur A., Ramachandran D., Cutrell E., Balakrishnan R. An Exploratory Study on the Use of Cameraphones and Pico Projectors in Rural India. ACM MobileHCI 2011

[P6] Hutchful D., Mathur A., Joshi A., Cutrell A. Cloze: An Authoring Tool for Teachers with Low Computer Proficiency. IEEE/ACM ICTD '10

[P5] Kam M., Mathur A., Kumar A., Canny J. Designing Digital Games for Rural Children: A Study of Traditional Village Games in India. ACM CHI '09 (Best Paper Honorable Mention Award)

[P4] Kam M., Kumar A., Jain S., Mathur A., Canny J. Improving Literacy in Rural India: Cellphone Games in an After-School Program. IEEE/ACM ICTD '09

[P3] Kam M., Agarwal A., Kumar A., Lal S., Mathur A., Tewari A., Canny J. Designing E-Learning Games for Rural Children in India: A Format for Balancing Learning with Fun. ACM DIS '08

[P2] Kam M., Bhagwani S., Kumar A., Lal S., Mathur A., Tewari A., Canny J. The Social Complexities of User-Centered Design in ICTD: Experiences from Four Schools in India's Villages and Slums. IEEE/ACM ICTD '07

[P1] Tewari A., Kumar A., Mathur A., Lal S., Kam M., Canny J. Mobile Games for Learning English in Rural India: Designing Cellphone Games Informed by Traditional Games. 3rd Digital Games Research Association International Conference (DIGRA'07)


  • A Method to Improve the Efficiency of Video Sensing Systems. {EP-19174348.3}
  • A system for the detection of facial expression on kinetic earables. {EP-19161913.9}
  • A method and system of making AI models robust and generalizable using a domain-adversarial training technique. {EP-18205945.1}
  • Sensor configuration based on other sensor context determination. {EP-19158220.4}
  • A method to improve the robustness of audio sensing models. {US-16/513212}
  • A method for augmenting user interface on earbuds using audio-kinetic model. {EP-18188821.5}
  • Gesture control of a data processing apparatus. {EP-3502835}
  • Method and devices for processing sensor data. {EP-3483729}
  • Method and device for analyzing sensor data. {EP-3401846}
  • A user equipment and method for protection of user privacy in communication networks. {EP-3382981}
  • Providing user access to remote devices. {EP-3310024}
  • Virtual reality interaction. {EP-3299930}
  • A method for predicting the engagement level of a user of a user device, a related engagement prediction device and user device. {EP-3285217}
  • Monitoring of attacks on bluetooth beacon devices. {EP-3148237}
  • User profiling for location based advertising. {EP-3139572}
  • Sharing resources between devices in a wireless network. {ES-2701303}
  • Providing sponsored content based on location and context. {EP-3001705}
  • Streaming playout of media content using interleaved media players. {US-2016088079}
  • System and method of account access notification. {EP-2919178}
  • System and method for providing and controlling visual display useful for remote control of a variety of devices. {IN-2013DE03396}
  • Methods and systems for multimodal interaction. {US-2015363047}


  • Program Chair for the WearSys 2019 workshop, co-hosted with MobiSys 2019.
  • Served on the Technical Program Committee for WristSense and Industrial Track at Percom 2019.
  • Poster Chair for Mobiquitous 2016.
  • Publicity and Web Chair for WPA 2016 co-hosted with Mobisys 2016.
  • External reviewer for leading journals and conferences in the field, including IMWUT, UbiComp, IEEE Pervasive Computing, CHI, MobileHCI, IEEE Computer Society, IEEE Transactions on Mobile Computing (TMC).

Work Experience

Principal Research Scientist, Nokia Bell Labs Feb '11 - Present

Presently, I am associated with the Pervasive Systems Department in Cambridge, UK led by Dr. Fahim Kawsar. I lead our team's research on improving the robustness of deep learning models in real-world scenarios using techniques such as Domain Adaptation and Generative Adversarial Networks (GANs).

Visiting Researcher, Microsoft Research India May '10 - Aug '10

I spent a summer at MSR to complete my Masters thesis research in collaboration with Dr. Edward Cutrell.

Undergraduate Research Assistant, UC Berkeley May '07 - Dec '08

I worked with Dr. Matthew Kam and Prof. John Canny on MILLEE, a project aimed at developing effective technologies to support out-of-classroom education in rural India.


Nokia Bell Labs, Broers Bulding, 21 JJ Thomson Avenue, Cambridge, United Kingdom