About me
I am currently working as a postdoctoral researcher in the HPDC group at VU Amsterdam, under the guidance of Prof. Henri Bal and Prof. Lin Wang (Paderborn University, Germany). My research focuses on developing efficient [networked] systems for machine learning (ML) [inference]. Along with this, I am also working on tackling communication challenges in networks of battery-less devices, with an ultimate goal of enabling distributed computation within device clusters (e.g., for running ML inference locally).
During my PhD at VU Amsterdam, I focused on developing a DL inference serving system for latency-sensitive video analytics applications by leveraging the strengths of various modern computing platforms (spanning end devices, the edge, and the cloud). Our paper, Jellyfish, received an Outstanding Paper Award at IEEE RTSS 2022. I also received a hardware grant from NVIDIA, which includes two A30 GPUs.
I received my Master’s in Parallel and Distributed Computer Systems (PDCS) from VU Amsterdam with Cum Laude honors. I have around five years of industrial experience in computer systems, specifically in distributed and data storage systems.
Note: I am actively looking for research positions, preferably in industrial labs. However, I am also open to academic and deep-tech startup positions. Here is my CV.
Publications
Inference Serving with End-to-End Latency SLOs over Dynamic Edge Networks
Vinod Nigade, Pablo Bauszat, Henri Bal, and Lin Wang
Real-Time Systems, 2024Distributed DNN Serving in the Network Data Plane
Kamran Razavi, George Karlos, Vinod Nigade, Max Mühlhäuser, and Lin Wang
EuroP4, 2022Jellyfish: Timely Inference Serving for Dynamic Edge Networks [slides] [code]
Vinod Nigade, Pablo Bauszat, Henri Bal, and Lin Wang
IEEE RTSS, 2022
Outstanding Paper Award
Artifact EvaluatedLive Video Analytics as a Service
Guilherme Henrique Apostolo, Pablo Bauszat, Vinod Nigade, Henri Bal and Lin Wang
ACM EuroSys EuroMLSys, 2022Better Never Than Late: Timely Edge Video Analytics Over the Air
Vinod Nigade*, Ramon Winder*, Henri Bal, and Lin Wang
ACM SenSys AIChallengeIoT, 2021Clownfish: Edge and Cloud Symbiosis for Video Stream Analytics [slides] [code]
Vinod Nigade, Lin Wang, and Henri Bal
ACM/IEEE Symposium on Edge Computing (SEC), 2020
(Acceptance Rate: 21.9%)Neural Representation of Motor Output, Context and Behavioral Adaptation in Rat Medial Prefrontal Cortex During Learned Behavior [code]
De Haan, Roel, Judith Lim, Sven A. van der Burg, Anton W. Pieneman, Vinod Nigade, Huibert D. Mansvelder, and Christiaan PJ De Kock
Frontiers in Neural Circuits, 2018Dangsan: Scalable use-after-free detection [code]
Erik Van Der Kouwe, Vinod Nigade, and Cristiano Giuffrida
ACM EuroSys, 2017
Patents
Distributed replication in cluster environments
Vinod Nigade, Mahesh Soundalgekar
US Patent 9,600,553, 2017
Theses
Efficiently Detecting Use-after-Free Exploits in Multi-Threaded Applications [code]
Master Thesis
Vrije Universiteit Amsterdam, 2016
Awards
- Outstanding Paper Award, IEEE RTSS, 2022
- Academic Hardware Grant (two A30 GPUs), NVIDIA, 2022
- VUFP Scholarship, VU Amsterdam, 2014-2015 and 2015-2016