I am a pseudo‑introvert who is passionate about esoteric technologies and is a life‑long learner. I like to spend majority of my time learning new things related to Development, Web3Security, DevSecOps, Eth-Protocol Research, Vulnerability Research and Secure Code Reviews. Sometimes I make things, sometimes I break things.
Jun 2023 - Jun 2024
Pune, India (Remote)
SecurityBoat Pvt. Ltd. specializes in security consulting and solutions for various sectors including web and network security.
Jun 2023 - Jun 2024
Jun 2023 - Apr 2024
Antwerp, Belgium (Remote)
Cleared Europe Services provides comprehensive security solutions, focusing on SIEM, threat detection, and Purple Teaming.
Jun 2023 - Apr 2024
Jun 2023 - Jul 2023
Discord (Remote)
TheCyberHub provides a platform for pentesting and exploit development, supporting a community of cybersecurity professionals.
Jun 2023 - Jul 2023
May 2023 - Aug 2023
Pune, India (Remote)
Null Community is a platform focusing on cybersecurity, including web development and event management.
May 2023 - Aug 2023
Jan 2023 - May 2023
Pune, India (Remote)
MI7 & XCOODE specializes in OSINT and threat analysis, focusing on security assessments and intelligence gathering.
Jan 2023 - May 2023
Dec 2022 - Mar 2024
Discord (Remote)
TWC Discord focuses on CTF competitions, providing a platform for participants to engage in various cybersecurity challenges.
Dec 2022 - Mar 2024
![]() 2020-2024 B.Tech in Electronics And Telecommunications EngineeringCGPA: 8.82 out of 10 | ||
![]() 2020-2024 Honors in Cloud ComputingCGPA: 9 out of 10 | ||
![]() 2017-2019 Intermediate Public Examination (12th Grade)Percentage: 83 out of 100 |
SIH brings the next generation evolution by inclusion of new methodology to inculcate the culture of startup and innovation ecosystem.
This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI).