Rajat Jaiswal

I am a Senior Undergraduate in the Department of Computer Science & Engineering at IIT Delhi.

My interests lie in the financial market. I am currently building AlgoTest, a platform for backtesting trading strategies for free on Nifty & Banknifty index options and futures.

I’ve always enjoyed mathematics and its application in solving complex and challenging problems. I have a very keen interest in the field of machine learning.

Email / Curriculum Vitae / LinkedIn / Github

Work Experience

Co-founder, AlgoTest September 2021 - Present

At AlgoTest, we are continuously building tools to help retail traders make better decisions for their investments. Our first product is a free options backtester for India.

AlgoTest.in is a platform that offers free backtesting for trading strategies in India. Built by expert traders with 10+ years of experience in the markets, both in India and on Wall Street. We invite you to leverage our extensive experience and evaluate your trading strategies for free.

Quantitative Analyst, TradeScience August 2020 - May 2021

I am engaged in technical analysis of derivatives market to design systems based on momentum and volatility of underlying asset. My responsibilities include implementing & backtesting trading strategies, and reviewing trade statistics to optimize strategy performance. It also involves triangulating novel solutions to increase profit, reduce drawdown, for maintaining strong risk-adjusted portfolios.

Internships

	Data Platform, Disney+ Hotstar Data Engineering Intern, Summer 2021 Hosted by Kushal Khandelwal and Samrat Deb
	BigData Experience Labs, Adobe Research Research Intern, Summer 2020 Hosted by Kuldeep Kulkarni and Sharmila Nangi
	Graduate Institute of Biomedical Informatics, Taipei Medical University Visiting Student, Summer 2019 Hosted by Yu-Chuan Li and Shabbir Syed-Abdul

Projects

Here are some selected projects that I have worked on

	Motion Planning for Mobile Robot code A reinforcement learning model for an autonomous agent in a grid world domain. The problem is modeled as a Markov Decision Process and policy for states is determined using value iteration. Covergence is determined by combined criteria of policy change and max norm of value change.
	PageRank using MapReduce code A pipeline to solve Google's PageRank algorithm using the MapReduce paradigm for distributed computing. Multi-threaded MapReduce library is developed utilizing the MPI for split-apply-combine strategy, outperforming the standard MapReduce-C++ & MapReduce-MPI libraries. Picture Credit
	Advanced RISC Machine based Processor code A 32-bit CPU designed for complete ARMv7 instruction set, writtten in Very High Speed Integrated Circuit Hardware Description Language(VHDL), and implemented on Basys3 Field Programmable Gate Array(FPGA) Board Picture Credit
	Traffic Simulator code A C++ simulator for Indian road traffic intersection, using OpenGL for GUI rendering. It supports realistic lane change behavior for Indian traffic. The simulator can be visualized on terminal as well as OpenGL. Picture Credit
	Platform Game code A multi-leveled role-playing based arcade game developed using impact.js. Fun to play for people like me who loved the 8-bit retro world and always look back to the games we played as a child to unwind.
	Functional Language Interpreter code A compiler with call-by-name(Krivine Machine) and call-by-value(SECD Machine) semantics, implemented in OCaml. It takes tokens generated from a Lexer to create an Abstract Syntax Tree using recursive Parser. Picture Credit

Teaching Assistantships

COL106: Data Structures and Algorithms Fall 2020 Instructors: Rahul Garg, Rijurekha Sen, and Yogish Sabharwal	MTL106: Probability and Stochastic Processes Spring 2021 Instructors: Ananta K. Majee, and S. Dharmaraja
COL334: Computer Networks Fall 2021 Instructors: Abhijnan Chakraborty, and Huzur Saran	COL380: Parallel & Distributed Programming Spring 2022 Instructors: Subodh Kumar

I used to be web blind, but now I have a website

Last updated on 8^th August 2021

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