Hrishikesh Suresh
Software Engineer Werkstudent at Dassault Systèmes
Darmstadt, Hesse, Germany
Summary
👤
Senior🎓
Top SchoolHrishikesh Suresh is a software engineer with eight years of experience across networking, cloud and machine learning, currently working as a Werkstudent at Dassault Systèmes while pursuing an M.Sc. in Computer Science at TU Darmstadt. He spent several years at Cisco progressing from intern to Software Engineer 2, gaining strong systems and networking expertise and hands-on experience with AWS, Azure and GCP. His open-source contributions span C++ ML work—adding GAN training callbacks to the well-known mlpack library—as well as core back-end debugging for real-time audio streaming and optimized algorithm implementations in C. Comfortable across the full stack, he builds Python web apps and writes technical blogs exploring lesser-known corners of CS, demonstrating both practical delivery and technical curiosity. He’s actively seeking internships in data analysis, ML, web development, DBMS or networking to broaden his skill set and apply research-oriented problem solving in production contexts.
8 years of coding experience
4 years of employment as a software developer
Bachelor of Technology - BTech, Computer Science, Bachelor of Technology - BTech, Computer Science at PES UniversityTechnischen Universität Darmstadt
Stackoverflow
68reputation
5kreached
8answers
2questions
Github Skills (41)
algorithm10
algorithms10
c-language10
dcgan10
lintcode10
machine-learning10
cgan10
c1110
data-structure10
c1710
deeplearning-ai10
deep-learning10
data-structures10
cprogramming-language10
testing9
Programming languages (5)
Github contributions (5)
roc-streaming/roc-toolkit
Sep 2019 - Feb 2020
Real-time audio streaming over the network.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:5 commits, 6 PRs, 97 comments in 5 months
Contributions summary:Hrishikesh primarily focused on implementing and debugging backtrace functionality within the `roc-toolkit` repository, specifically targeting audio streaming. Their work included the initial implementation of backtrace printing for bionic and libunwind, along with signal-safe modifications. The user made numerous commits addressing code style, namespaces, and bug fixes related to the backtrace implementation, including demangling and format adjustments. Furthermore, the user contributed to build scripts and configuration files related to the dependencies of the project.
fecnetworkingstreamingwebrtcaudio
mlpack/mlpack
Oct 2019 - Oct 2019
mlpack: a fast, header-only C++ machine learning library
Role in this project:ML Engineer
ML EngineerContributions:12 commits, 1 PR, 7 comments in 7 days
Contributions summary:Hrishikesh contributed to the development and testing of a Generative Adversarial Network (GAN) within the mlpack library. Their work involved extending callback functionalities for the GAN training process, which included adding the ability to print the training loss. The user also focused on incorporating and testing a progress bar callback for improved training monitoring. Furthermore, the user made minor adjustments to the code, including style fixes and parameter descriptions.
regressionheaderdeep-learningscientific-computingc-plus-plus
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