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PhD Defence

less than 1 minute read

Published:

๐ŸŒŸ I am excited to announce that I have successfully completed my PhD defence! ๐Ÿ˜‡

PhD Defence Celebration

PDPS-Bench TPCTC2024@VLDB

less than 1 minute read

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โš ๏ธ ๐—ข๐—ป๐—ฒ ๐—ผ๐—ณ ๐˜๐—ต๐—ฒ ๐—ธ๐—ฒ๐˜† ๐—ฐ๐—ต๐—ฎ๐—น๐—น๐—ฒ๐—ป๐—ด๐—ฒ๐˜€ ๐—ถ๐—ป ๐—บ๐—ฎ๐—ฐ๐—ต๐—ถ๐—ป๐—ฒ ๐—น๐—ฒ๐—ฎ๐—ฟ๐—ป๐—ถ๐—ป๐—ด ๐—ฒ๐˜€๐—ฝ๐—ฒ๐—ฐ๐—ถ๐—ฎ๐—น๐—น๐˜† ๐—ณ๐—ผ๐—ฟ ๐—ผ๐—ฝ๐˜๐—ถ๐—บ๐—ถ๐˜‡๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—ฝ๐—ฟ๐—ผ๐—ฏ๐—น๐—ฒ๐—บ๐˜€, ๐—ถ๐˜€ ๐—ด๐—ฒ๐—ป๐—ฒ๐—ฟ๐—ฎ๐˜๐—ถ๐—ป๐—ด ๐—ต๐—ถ๐—ด๐—ต-๐—พ๐˜‚๐—ฎ๐—น๐—ถ๐˜๐˜† ๐—ฑ๐—ฎ๐˜๐—ฎ. This data directly impacts the accuracy of models. In scenarios like parallel and distributed stream processing, the need for high-quality training and evaluation data becomes even more crucial.

TPCTC PDSP-Bench Presentation

ZeroTune ICDE 2024

less than 1 minute read

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I had the incredible opportunity to present our paper, โ€œZeroTune: Learned Zero-Shot Cost Models for Parallelism Tuning in Stream Processing,โ€ at an A* venue IEEE ICDE Conference 2024 ๐ŸŽ‰

ICDE Zerotune

portfolio

projects

DCM IT & Security Analysis

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Supported IT security and infrastructure operations at DCM Shriram, focusing on Fortinet, server management, and ITโ€“business alignment.

Smart Kitchen and Weather Apps

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Developed and tested Smart Kitchen and Weather applications for Android tablets and phones, including backend communication and widget interfaces.

Sony DSLR & Camcorder Development

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Developed and customized key modules for Sony DSLR and camcorder devices including UI menus and camera focus features with embedded system testing.

NTTDocomo Phonebook Application

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Developed and tested a smart phonebook application for Android tablets, with automation using QTP and DTAF for NTTDocomo.

Voice over IP (VoIP)

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Developed and tested a cross-platform VoIP application for Android and iOS, including automation and communication feature testing for T-Mobile.

Smart Security Management Server (SSMS)

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Developed test automation frameworks and QA strategies for Kobilโ€™s Smart Security Management Server (SSMS), used by banks and retailers for secure mobile services.

Smart City Bonn

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Developed a real-time sensor data platform for the City of Bonn to deliver smart city services using event-driven architecture and interactive visualizations.

Beethoven Pastoral Project

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Designed and developed the multilingual and responsive frontend for the official Beethoven 250th Anniversary campaign website supported by UNFCCC.

Business Model of NB-IoT

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Developed NB-IoT-based prototypes and integrated CoAP-enabled devices into Deutsche Telekomโ€™s Cloud of Things for smart city applications.

DEBS 2019 Conference Website

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Designed and maintained the official website for DEBS 2019 conference, including full frontend implementation, responsiveness, and cross-platform compatibility.

OSCA โ€“ One Smart City App

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The aim of the OSCA project is to create an app that gives citizens convenient access to services provided by cities and third-party providers.

Strategy Consulting for PIB Presentation

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The project aimed to deliver strategy consulting in preparation for the upcoming PIB (Project Investment Board) meeting and final presentation.

DFG MAKI Subproject C2

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Investigating transition-aware adaptation techniques for event-based systems to enhance Quality of Service in dynamic communication environments.

publications

Efficient Crowd Sensing Task Distribution Through Context-Aware NDN-Based Geocast

Published in , 2017

Recommended citation: Nguyen, The An Binh and Agnihotri, Pratyush and Meurisch, Christian and Luthra, Manisha and Dwarakanath, Rahul and Blendin, Jeremias and Bรถhnstedt, Doreen and Zink, Michael and Steinmetz, Ralf. (2017). "Efficient Crowd Sensing Task Distribution Through Context-Aware NDN-Based Geocast." 2017 IEEE 42nd Conference on Local Computer Networks (LCN).
Download Paper | Download Bibtex

Accurate Performance Modeling for Distributed Stream Processing: Methods for Performance Benchmarking and Zero-shot Parallelism Tuning in Distributed and Heterogeneous Environments

Published in , 2024

Recommended citation: Agnihotri, Pratyush. (2024). "Accurate Performance Modeling for Distributed Stream Processing: Methods for Performance Benchmarking and Zero-shot Parallelism Tuning in Distributed and Heterogeneous Environments." Technische Universitรคt Darmstadt.
Download Paper | Download Bibtex

talks

teaching

Supervised Labs, Seminars, and Projects

Bachelor and Masters course, Multimedia Communication Lab, TU Darmstadt, 2021

Student(s)TitleTypeYear
Michael, Paula, Katrin, RafikParallel and Distributed Streaming BenchmarkingLab2024
RhivuAuto-Scaling for Distributed Stream Processing using Reinforcement LearningLab2024
Hamna (TU Ilmenau)Efficient Memory Management for Large Language Model Serving with PagedAttentionSeminar2023
Daniel (TU Ilmenau)gSampler - General and Efficient GPU-based Graph Sampling for Graph LearningSeminar2023
Daniil (TU Ilmenau)Parallel Stream Processing in Distributed Stream Processing SystemsSeminar2023
MouayadParallelizing Intra-Window Join using Hardware AcceleratorProject2023
Mouaz, Jinyao, ZongdiParallel Stream Processing and Data Analytics using FlinkLab2023
Chippy, NishchayParallel Stream Processing using Reinforcement LearningSeminar2022
Mouayad, OzcanReal-time query validation and performance visualizationLab2022
Sravya, Gayatri, HarshaBig Data Analysis and Performance EvaluationLab2022
Aastha, SushimithaLearned Operator Parallelization and Stream ProcessingSeminar2022
Chengbo, Xiangyu, XingzhouNetwork Security Monitoring in SDNLab2022
AntonPerformance Evaluation of Windows Join in Stream Processing SystemProject2022
Sushimitha, ChristianQuery processing and performance analysis using FlinkLab2022
MarvinHardware Accelerated Stream ProcessingSeminar2021
AliResources Elasticity and Computation Offloading Techniques in Stream Processing SystemsSeminar2021
CorinnaTelcaria Alviu- Network Traffic Monitoring and ProfilingLab2021

Supervised Students

Bachelor and Masters course, Multimedia Communication Lab, TU Darmstadt, 2021

Student NameTitleTypeYear
Daniel DirkBenchmarking Parallelism and Heterogeneity in Distributed Stream ProcessingMaster2024
Mizuki HashimotoFeature Selection Strategies for Parallel Stream ProcessingMaster2024
Paul StiegeleLearned Parallel Stream ProcessingMaster2022

Teaching Assistant

Bachelor and Masters courses, TU Darmstadt, 2025

YearsCourseRole
2021โ€“2024Communication NetworksTeaching Assistant
2014โ€“2017Distributed SystemsStudent Tutor