Saeejith Nair
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  • Bio
  • Recent Projects
  • Industry Experience
    • Nuro.ai | Software Engineering Intern
    • BRAIN Lab | Undergraduate Researcher
    • Nuro.ai | Software Engineering Intern
    • Arcturus Networks | Embedded Machine Vision Developer Intern
    • Curtiss-Wright Defense Solutions | Embedded Software Engineering Intern
    • Centre for Operational Research and Analysis, DRDC | Research Engineer
    • NXP Semiconductors | AI & Vision Processor System Level Design Intern
    • Home Depot Canada | Junior Front End Web Developer
  • Selected Publications
  • Pronunciation guide

Saeejith Nair

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Bio

I’m currently an MASc candidate in Systems Design Engineering at UWaterloo’s Vision and Image Processing Lab, advised by Prof. Alexander Wong and Prof. Javad Shafiee. My research has focused on projects at the intersection of efficient ML (specifically applying neural architecture search to NeRFs and vision transformers), embedded systems (latency prediction for on-device inference), and robotics (building simulation pipelines for synthetic data generation, training embodied morphologies, and dexterous manipulation). I’m interested in building embodied systems that can efficiently learn to interact with the world in an open-ended manner.

I previously graduated from the University of Waterloo with a BASc in Mechatronics Engineering with an Option in Artificial Intelligence. As an undergraduate, I’ve interned as a software engineer across the full systems stack including sensor processing and communications infrastructure on self-driving cars, simulators for robot grasping, real-time video analytics applications for embedded microcontrollers, safety-critical bootloader firmware for aerospace products, silicon validation for AI accelerators, and web development for e-commerce.

I’m currently looking for new opportunities to build the next generation (and beyond) of robotics. If you’re working on something interesting, or want to learn more, I’d love to chat!

Recent Projects

Check out my projects page for more!

Elastic-NeRF
nerf
elastic
wip
Making NeRFs even more compact and efficient using an elastic architecture (and no additional training cost)!
Jan 9, 2024

NAS-NeRF
nerf
nas
neurips workshop
We introduce a generative neural architecture search strategy that generates compact, scene-specialized NeRF architectures.
Dec 11, 2023

NV-Synth
synthetic data
neurips workshop
We introduce a large-scale synthetic food image dataset for nutrition estimation. NV-Synth contains 84,984 photorealistic meal images rendered from 7,082 dynamically plated…
Dec 11, 2023

DARLEI
RL
evolution
cvis
DARLEI combines evolutionary algorithms with parallelized reinforcement learning for efficiently training and evolving populations of UNIMAL agents.
Dec 8, 2023

TurboViT
vit
nas
neurips workshop
We explore the generation of fast vision transformer architecture designs via generative architecture search to achieve a strong balance between accuracy and architectural…
Aug 22, 2023

Maple-Edge
edge-ml
latency prediction
cvpr workshop
We propose MAPLE-Edge, an edge-device oriented latency predictor where we train a regression network on architecture-latency pairs in conjunction with a hardware-runtime…
Jun 1, 2022
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Industry Experience

Nuro.ai | Software Engineering Intern

Mountain View, CA (June - Sept, 2021)

Brought up hardware accelerator, implemented efficient digital signal processing algorithms (in C) for radars on self-driving delivery robot, and developed testing architecture for radar HIL simulation chambers.

BRAIN Lab | Undergraduate Researcher

University of Waterloo (May - Sept, 2020)

Developed a rigid-body grasping simulator in PyBullet and used synthetic demonstration data to train a planner for robotic assembly tasks.

Nuro.ai | Software Engineering Intern

Mountain View, CA (Jan - May, 2020)

Developed onboard and embedded communications infrastructure for radar driver module on self-driving delivery robot. Improved sensor data throughput and firmware upgrade speeds.

Arcturus Networks | Embedded Machine Vision Developer Intern

Toronto, ON (May - Aug, 2019)

Designed real-time, multithreaded video analysis application in C++ for low power embedded platform. Improved multi-object tracking algorithms and developed a library to accelerate CPU-based inference using ARM NEON intrinsics.

Curtiss-Wright Defense Solutions | Embedded Software Engineering Intern

Ottawa, ON (Sept - Dec, 2018)

Implemented, validated, and released features for U-Boot bootloaders. Drove debug and validation efforts across VxWorks & Yocto Linux BSPs, BIOS, and bootloader products to meet release schedule.

Centre for Operational Research and Analysis, DRDC | Research Engineer

Ottawa, ON (Sept 2018 - Apr 2019)

Prototyped tool for CANSOFCOM to optimize troop schedules using genetic algorithms.

NXP Semiconductors | AI & Vision Processor System Level Design Intern

Ottawa, ON (Jan - Apr, 2018)

Developed an internal tool to simulate DMA performance of NXP’s accelerated vision processor for ADAS applications. Analyzed results and waveforms to identify bugs in SystemVerilog RTL resulting in 2.73x increase in DMA bandwidth.

Home Depot Canada | Junior Front End Web Developer

Toronto, ON (May - Aug, 2017)

Developed features for an internal front-end component library to assist migrating the Home Depot Canada website to React.

Selected Publications

  1. Saeejith Nair, Yuhao Chen, Mohammad Javad Shafiee, Alexander Wong. NAS-NeRF: Generative Neural Architecture Search for Neural Radiance Fields. arXiv:2309.14293, 2023. NewInML workshop @ NeurIPS, December 2023.

  2. Saeejith Nair, Javad Shafiee, Alexander Wong. DARLEI: Deep Accelerated Reinforcement Learning with Evolutionary Intelligence. arXiv:2312.05171, 2023. Conference on Vision and Intelligent Systems (CVIS), December 2023 (Oral).

  3. Saeejith Nair, Chi-en Amy Tai, Yuhao Chen, Alexander Wong. NutritionVerse-Synth: An Open Access Synthetically Generated 2D Food Scene Dataset for Dietary Intake Estimation. arXiv:2312.06192, 2023. NewInML workshop @ NeurIPS, December 2023.

  4. Alexander Wong, Saad Abbasi, Saeejith Nair. TurboViT: Generating Fast Vision Transformers via Generative Architecture Search. arXiv:2308.11421, August 2023. NewInML workshop @ NeurIPS, December 2023.

  5. Chi-en Amy Tai, Matthew Keller, Saeejith Nair, Yuhao Chen, Yifan Wu, Olivia Markham, Krish Parmar, Pengcheng Xi, Heather Keller, Sharon Kirkpatrick, Alexander Wong. NutritionVerse: Empirical Study of Various Dietary Intake Estimation Approaches. Multimedia Assisted Dietary Management workshop @ ACM Multimedia Conference, September 2023.

  6. Alexander Wong, Yifan Wu, Saad Abbasi, Saeejith Nair, Javad Shafiee. Fast GraspNeXt: A Fast Self-Attention Neural Network Architecture for Multi-task Learning in Computer Vision Tasks for Robotic Grasping on the Edge. Neural Architecture Search workshop @ CVPR, June 2023, pp. 2293-2297.

  7. Chi-en Amy Tai, Matthew Keller, Mattie Kerrigan, Yuhao Chen, Saeejith Nair, Pengcheng Xi, Alexander Wong. NutritionVerse-3D: A 3D Food Model Dataset for Nutritional Intake Estimation. arXiv:2304.05619, Apr 2023. WiCV workshop @ CVPR, June 2023.

  8. Alexander Wong, Javad Shafiee, Saad Abbasi, Saeejith Nair, Mahmoud Famouri. Faster Attention Is What You Need: A Fast Self-Attention Neural Network Backbone Architecture for the Edge via Double-Condensing Attention Condensers. All Things Attention workshop @ NeurIPS, December 2022.

  9. Saeejith Nair, Saad Abbasi, Javad Shafiee, Alexander Wong. Maple-Edge: A Runtime Latency Predictor for Edge Devices. Embedded Vision workshop @ CVPR, June 2022 (Oral), pp. 3660-3668.

  10. Xueyang Yao, Saeejith Nair, Peter Blouw, Bryan Tripp. Inferring symbols from demonstrations to support vector-symbolic planning in a robotic assembly task. hal-03041290, November 2020. SMILES (Sensorimotor Interaction, Language and Embodiment of Symbols) workshop @ ICDL, November 2020.

Pronunciation guide

My first name is pronounced like sigh-jith (IPA: /ˈsaɪ-dʒɪθ/).

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