My strengths in this domain include Probability Theory, Descriptive Statistics, Linear Algebra, Statistical Inference,
Stochastic Processes, Multivariate Analysis, Time Series Analysis, Bayesian Statistics, Convex Optimization, Statistical Learning and
Pattern Recognition with a focus on Computer Vision and Natural Language Processing.
My programming strengths include R(+ggplot2), SAS and Python(+TensorFlow, Sklearn, OpenCv, Nltk)
I absolutely love solving problems from Combinatorics which include Graph Theory
and Ramsey Theory along with their applications in Network Analysis.
Knowing a bit of graph theory provides deep insights to problems in computer science like the 8-Queens Puzzle or the Knight Tour problem.
Take the Knight Tour Problem on a 11x11 board for instance. Anyone can backtrack, but asserting non-existence by realising that the Knight graph is bipartite and only bipartite graphs with an even number of vertices can have Hamiltonian cycles, saves a lot of time!
I have always found programming problems challenging and computational thinking enticing, especially the topics of Recursion and Dynamic Programming and Graphs!
I have solved numerous problems from Leetcode, Project Euler and Rosalind (for BioInformatics).
I have a firm hold of C++ and it's powerful STL comes handy while solving such problems.
Being from a statistics background, I cannot help but be intrigued in not only
Quantitative Economics which include topics like
Econometrics and Regression Analysis and Game Theory, but also in Micro and Macro Economics
which include themes like Fiscal and Monetary Policies and Public Finance.
Additionally, I am a part of the Student's Committee of Risk Management of IRM Global and I write regular blogs on Valuation and Risk Modelling and related topics.