Vivienne Sze
Professor
Designs energy-efficient systems for machine learning, computer vision, and video, jointly optimizing algorithms, architectures, and circuits.
Vivienne Sze's lab at MIT works on accelerators, chips & architecture and efficient training & inference. 17 papers since 2023, 4 at top venues, mostly RA-L and ICIP. 5 PhD students. 46 alumni. Applications close .
At a glance
- papers, 2023–2026
- 4/ year
- at T1 venues
- 24%
- PhD students
- 5
- MS students
- 0
- alumni listed
- 46
Papers by yearfrom the lab homepage, 2023–2026
- 2 papers2026 · T1 0 · collecting
- 3 papers2025 · T1 0
- 6 papers2024 · T1 2
- 6 papers2023 · T1 2
T1 venuesOtherVenues: RA-L, ICIP, ISCA, MICRO, npj Digital Medicine
Research focuspaper titles that use each topic's words
- Efficient training & inference4 papers
- Accelerators, chips & architecture2 papers
- designs energy-efficient0 papers
- energy-efficient0 papers
- architectures0 papers
Paper list
From the lab homepage.
20262 papers
- IEEE Symposium on VLSI (VLSI-Circuits), June . Highlighted in and received Best Demo AwardGleanmer: A 6 mW SoC for Real-Time 3D Gaussian Occupancy Mapping
- npj Digital MedicineiPad Eye Tracking Reproduces Clinical Grade Oculomotor Differences in Parkinson’s Disease
20253 papers
- RA-LDecTrain: Deciding When to Train a Monocular Depth DNN Online
- RA-LGEVO: Memory-Efficient Monocular Visual Odometry Using Gaussians
- npj Parkinson’s DiseaseTowards scalable screening for the early detection of Parkinson’s disease: validation of an iPad-based eye movement assessment system against a clinical-grade eye tracker
20246 papers
- ISPASSArchitecture-Level Modeling of Photonic Deep Neural Network Accelerators
- IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), May . Best Paper AwardCiMLoop: A Flexible, Accurate, and Fast Compute-In-Memory Modeling Tool
- ICIPClearDepth: Addressing Depth Distortions Caused by Eyelashes for Accurate Geometric Gaze Estimation on Mobile Devices
- NSDI (T1)Gemino: Practical and Robust Neural Compression for Video Conferencing
- T-RO (T1)GMMap: Memory-Efficient Continuous Occupancy Map Using Gaussian Mixture Model
- TCASAILoopTree: Exploring the Fused-layer Dataflow Accelerator Design Space
20236 papers
- MICRO (T1)Data Centers on Wheels: Emissions from Computing Onboard Autonomous Vehicles
- ACM/IEEE International Symposium on Microarchitecture (MICRO), October . Highlighted inHighLight: Efficient and Flexible DNN Acceleration with Hierarchical Structured Sparsity
- IMWUTIndividualized Tracking of Neurocognitive-State-Dependent Eye-Movement Features Using Mobile Devices
- ISPASSLoopTree: Enabling Exploration of Fused-layer Dataflow Accelerators
- ISCA (T1)RAELLA: Reforming the Arithmetic for Efficient, Low-Resolution, and Low-Loss Analog PIM: No Retraining Required!
- ACM/IEEE International Symposium on Microarchitecture (MICRO), October . Highlighted inTailors: Accelerating Sparse Tensor Algebra by Overbooking Buffer Occupancy
Where alumni went46 listed
Apply to MITFall 2027
MIT EECS Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- See program page
- English
- TOEFL/IELTS
- Fee
- USD 90
Confirmed on the program page.
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Data
Checked against the lab homepage.
- Collected
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- Papers
- The lab homepage
- Members
- Lab homepage
- Alumni
- Lab homepage
Tiers are venue classifications, not lab rankings.
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