Shreenaga Tejas Chikoti

Class of 2026

Bio

I am Shreenaga Tejas Chikoti, an upcoming Master of Science in Computational Finance (MSCF) graduate from Carnegie Mellon University. I hold a B.S. in Mathematics and Scientific Computing from IIT Kanpur, where I maintained a CGPA of 8.7 and earned the Academic Excellence Award for Outstanding Academic Performance. My academic journey began with achieving an All India Rank of 464 in the highly competitive JEE Advanced exam.

My professional experience includes a summer internship at Qube Research and Technologies, where I excelled as a Quantitative Researcher. During my tenure, I specialized in designing alphas for the R1k universe within the Medium Frequency Trading Domain. I developed and tested strategies using technical indicators and implemented machine learning techniques that significantly enhanced performance metrics. My contributions were acknowledged with a full-time offer from Qube Research and Technologies.

Equipped with proficiency in programming languages such as C, C++, Python, and R, alongside deep learning frameworks like TensorFlow and PyTorch, I aspire to pursue a career as a quantitative researcher and trader at a leading firm. My coursework has provided a solid foundation in essential quantitative disciplines including probability theory, linear algebra, machine learning, and big data visualization. I am driven by a passion for creating innovative and profitable trading strategies across diverse markets.

I have also conducted significant research in various domains, including developing LLAMA, a novel approach for active learning acquisition functions in deep learning, and participating in the SemEval Task 4 for detecting persuasion techniques in memes. My work has been published and presented at prestigious conferences, such as NAACL and IEEE ICRA.

Kindly contact me at tchikoti@andrew.cmu.edu or reach out to me at LinkedIn to discuss opportunities in quantitative research, algorithmic trading, and beyond.