Vijay Krishna Menon, Ph.D. Email & Phone Number

A data scientist unicorn with over 18 years of disparate (predominantly) academic and industrial problem solving, research and teaching experience; fundamentally trained in computer science and multidisciplinary sciences with a huge aptitude for programming and an ineffable understanding of mathematics that enables one to visualise and envision knowledge generation from data.1. Programming: Expert level programming skills with over 20 years of experience in Java, over 9 years in Scala and Python; Handsome knowledge of R . Expertise in data structures of all kinds, representation, Object oriented Analysis and Design and Functional Programming.2. Mathematics: In-depth understanding of Linear Algebra, Vector Spaces, Matrix operators and Eigen Spaces. Thorough knowledge of mathematical optimisation process and algorithms especially at formulating problems. Excellent understanding of Set Theory and Discreet Maths leading to Formal Methods, Language and Automata theory. Iterative and Computational solutions. Well acquainted with Chaos Theory, Fractal Geometry and Network Theory. 3. Statistics: A thorough understanding of fundamental statistics such as central tendencies, distributions, models, parameters, estimators, functionals and sampling distributions. Well-versed in statistical inference; Bayesian and Frequentist approaches, parametric and non-parametric models. Well placed in understanding the shape of data and various parameter estimators; confidence intervals and Hypothesis testing, ANOVA and probabilistic and graphical models (PGMs).4. Algorithms: Expertise in analysing algorithms for computational complexity and comparing them at various levels to tweak performance. Specialised in formulation of exponentially scaling and intractable problems, as evolutionary searches to find working solutions. Well-versed in most Machine Learning algorithms; to mention a few, Dynamic Mode Decomposition (DMD), Support Vector Machine (Supervised Machine Learning), K Means clustering, SOMs, Deep Learning and Dynamic Programming algorithms. Very comfortable with t-SNE, PCA based dimensionality reduction. 5.  Technology: Expert in most enabling technologies for AI . Wide expertise in Big-data analytics and processing using Scala and Apache Spark ecosystem at all levels; aggregate joins, higher Data frame abstractions and Spark SQL, NoSQL, real-time stream analysis . Experience with Azure and AWS. Deep understanding of Blockchain, Crypto. Knowledge and hands on experience in Gen-AI; LLMs, Vector DB’s and Embeddings along with Hugging-Face™ API and OpenAI

Listed skills include Cloud Security, Network Engineering, Security Systems Integration, Virtualization, and 35 others.