Problem Solving & Competitive Programming
Building strong foundations through algorithms and data structures.
A dedicated journey of tackling complex computational challenges, mastering data structures, and refining algorithmic efficiency. My approach focuses on writing clean, optimized code that bridges the gap between theoretical computer science and practical software engineering.
Coding Profiles
LeetCode
Focused on Medium and Hard difficulty problems involving Dynamic Programming, Graph Theory, and advanced Data Structures.
Codeforces
Active participant in Div 2 and Div 3 contests with focus on algorithmic thinking, time-complexity optimization, and mathematical problem-solving.
Technical Content Contributor — GeeksforGeeks
Published articles related to Data Structures and Algorithms.
Problem Solving Methodology
Understand the Problem
Deconstruct requirements, identify edge cases, and determine input constraints before writing a single line of code.
Algorithm First
Design the solution using pseudocode. Evaluate time and space complexity to ensure the approach fits within problem limits.
Optimize & Refactor
Implement the solution and iteratively refactor for readability and performance while maintaining correctness.
Teaching & Mentoring
DSA Mentor @ Coder's Cafe
- Conducting weekly DSA mentoring sessions for beginners and intermediates, covering core data structures and algorithms.
- Teaching recursion, backtracking, and graph algorithms through structured deep-dive discussions.
- Helping juniors build interview confidence through 1-on-1 technical interview preparation sessions.
Core Areas of Practice
Why Algorithms Matter
“Algorithmic thinking is more than just passing coding interviews — it is the discipline of breaking down complex system requirements into discrete, solvable components. In backend engineering, this mindset translates to building highly performant APIs, optimizing database queries, and designing scalable system architectures that can handle millions of operations with minimal latency.”