Vishakan S

Passionate and results-driven final-year B.Tech Computer Science student with a strong foundation in Data Analytics, Cloud Computing, and Artificial Intelligence.

Proficient in Python, R, HTML, and CSS, with a solid grasp of core programming and analytical concepts.

Recognized for consistent academic performance and a proactive approach to learning emerging technologies. Eager to contribute to innovative projects and build a successful career in the technology and engineering domain.

• Amazon Web Services: Completed AWS cloud practitioner certification
• Google: Completed a course in Data Analytics
• IBM: Completed a python Machine Learning and Deep Learning certification
• My Captain Data Analytics: Completed external certification on data analytics on My Captain platform and possessing a letter of recommendation from the co founder and Appreciation letter from the expert in the field

Dynamic Traffic Route Planner with Live Simulation

• Built a modular traffic routing engine in Python leveraging advanced graph data structures for dynamic path finding.
• Implemented Dijkstra, A*, and multi-objective routing algorithms to compute optimal paths across city networks.
• Modeled traffic conditions using custom Node and Edge classes with real-time updates based on weather, time, and congestion.
• Utilized heaps, priority queues, and adjacency maps for efficient path computations and K-shortest path retrieval.
• Visualized route performance, congestion heatmaps, and network stats using Plotly Dashboards and Matplotlib animations.

Quantum vs Classical Maze Pathfinding

· Designed a comparative pathfinding framework using classical A* and quantum Grover’s algorithm across procedurally generated mazes.

· Demonstrated theoretical quadratic speedup of Grover’s search (O(√N)) over A* in complex maze environments, using Qiskit simulations.

· Analysed scaling behaviour, simulated performance, and practical limitations of quantum algorithms for spatial navigation tasks.

Mental Guardian- The Mental health Assessment Web App:

Tech Stack: React.js, CSS, JavaScript

• Designed a web-based mental health assistant to assess users’ mental well-being through online tests.
• Implemented questionnaire modules using aptitude and psychometric analysis methods.
• Developed a responsive frontend in React.js to dynamically evaluate and present results.