Zain
Taufique
Doctoral Researcher, Department of Computing
Doctoral Researcher, Health Technology
Doctoral Candidate
Biography
Zain Taufique has received his MS degree in Electronics and Embedded Systems from Lahore University of Management and Sciences (LUMS) in 2020. He is currently pursuing his Ph.D. degree at the University of Turku, Finland. His research interest includes bio-medical wearable devices, low power chip designs, FPGA accelerators, high-level synthesis tools, energy-efficient IoT, and AI-based hardware architectures.
Research
Research topic (according to plan)
Design of Reconfigurable and Approximate Functional Units for Wearable Applications
- Interests (research-wise)
- Low Power Wearable Designs
- FPGA based hardware reconfiguration
- Approximate Computing on IoT devices
- Deep Learning on Hardware applications
- Machine Learning based Autonomous Applications
Publications
Exploiting Approximation for Run-time Resource Management of Embedded HMPs (2025)
ACM Transactions in Embedded Computing Systems
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )
Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms (2025)
IEEE/ACM International Conference on Computer-Aided Design
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa)
Tango: Low Latency Multi-DNN Inference on Heterogeneous Edge Platforms (2024)
Proceedings : IEEE International Conference on Computer Design
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa)
Adaptive approximate computing in edge AI and IoT applications: A review (2024)
Journal of Systems Architecture
(A2 Vertaisarvioitu katsausartikkeli tieteellisessä lehdessä)
HiDP: Hierarchical DNN Partitioning for Distributed Inference on Heterogeneous Edge Platforms (2024)
arXiv.org
(O2 Muu julkaisu )
Adaptive Workload Distribution for Accuracy-aware DNN Inference on Collaborative Edge Platforms (2024)
Proceedings of the Asia and South Pacific Design Automation Conference
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa)
A Low Power Multi-Class Migraine Detection Processor Based on Somatosensory Evoked Potentials (2021)
IEEE Transactions on Circuits and Systems II: Express Briefs
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))
Approximate Feature Extraction for Low Power Epileptic Seizure Prediction in Wearable Devices (2021)
IEEE Nordic Circuits and Systems Conference
(Vertaisarvioitu artikkeli konferenssijulkaisussa (A4))
An 8.7 μJ/class. FFT accelerator and DNN-based configurable SoC for Multi-Class Chronic Neurological Disorder Detection (2021)
2021 IEEE Asian Solid-State Circuits Conference (A-SSCC)
(Vertaisarvioitu artikkeli konferenssijulkaisussa (A4))