Akshat Joshi

Software Engineer

Chennai, Tamil Nadu, India3 yrs 1 mo experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

Graduated from IIT Madras with a B.Tech in Electrical Engineering.
Contributed to ultra low latency trading systems at Graviton.
Research accepted at IEEE ICCP 2024.

Stackforce AI infers this person is a Software Engineer with a focus on AI and quantitative trading.

Contact

Skills

Core Skills

Artificial Intelligence

Other Skills

C++Data AnalysisDeep LearningMachine LearningPython (Programming Language)Quantitative FinanceQuantitative ResearchSoftware DevelopmentTime Series Analysis

About

I have graduated with a Bachelor's degree in Electrical Engineering from IIT Madras, one of the top engineering institutes in India. I currently work as a Software Engineer at Graviton, a quantitative trading firm, where I contribute to the firm's ultra low latency trading systems used for HFT. I am academically inclined with a deep passion for technology. My areas of interest include Software Engineering, Quantitative Trading and Artificial Intelligence. In my free time, I like reading books and papers around AI, Computer Vision and Computer Systems.

Experience

Graviton research capital llp

Software Engineer

Jan 2025 – Present · 1 yr 2 mos

Apt research private limited

Software Engineer

Jul 2023 – Sep 2024 · 1 yr 2 mos · On-site

Indian institute of technology, madras

Undergraduate Researcher

Oct 2022 – Jul 2023 · 9 mos · Chennai, Tamil Nadu, India

Researched on developing deep learning models for light field and novel view synthesis at Computational Imaging Lab, IIT Madras.
Our work got accepted at IEEE ICCP 2024

Deep LearningMachine LearningArtificial Intelligence

Apt research private limited

Software Engineering Intern

May 2022 – Jul 2022 · 2 mos · Bengaluru, Karnataka, India

Worked as a SWE intern for one of the top prop trading firms of India. Details under NDA.

Samsung india

Research Intern

May 2021 – Jul 2021 · 2 mos

Researched on the application of computational hyperspectral imaging for improving the signal to noise ratio of remote photopleythsmogram obtained from RGB videos of human faces.