Lokesh Parasa

Lokesh Parasa

Student at Manipal Institute of Technology

Vijayawada, IndiaSoftware and Technology
4roles
50skills
4education
1credentials

About

Computer and Communication Engineering student at Manipal Institute of Technology with experience building full-stack applications, secure ticketing systems, AI evaluation frameworks, and automation workflows.

Experience

Web Technician / Technical Member

E-Cell, MIT Manipal

7 mos

• Event Ticketing System: Collaborated with a team to build a secure end to end ticketing platform using Next.js, scaling to support 1,500+ registered users and 1,000+ real-time verified tickets for a campus wide summit. Built RESTful APIs with Node.js and Express.js for user registration, ticket generation, and live ticket validation. • Innovation Policy Consortium (IPC) Portal: Led the development of the official submission dashboard using Next.js and Supabase, managing authenticated file uploads and real-time data synchronization for 15+ colleges. • Collaborating with cross-functional teams to deploy scalable web solutions under strict deadlines for high-traffic university events.

Student Staff

IEEE Student Branch Manipal

8 mos

• Active member of one of the largest technical societies on campus, engaging with peers on emerging tech trends. • Participating in technical workshops and seminars to stay updated with advancements in computer engineering.

Tech Head / Full-Stack Developer

E-Cell, MIT Manipal

Oct 2024 – Present · Manipal, India

Worked with a 5-member team to build a secure Next.js event ticketing ecosystem handling 1,500+ registered users and 1,000+ real-time verified tickets. Engineered OTP-based email authentication, Atom Payment Gateway integration with AES encryption, and dynamic QR ticket generation. Built a secure Next.js and Supabase IPC submission portal with authenticated file uploads and real-time synchronization for 15+ colleges.

Student Member

IEEE Student Branch Manipal

Aug 2024 – Present · Manipal, India

Engaging in technical workshops and peer-led seminars on emerging computer engineering trends.

Education

Manipal Institute of Technology

Bachelor of Technology, Computer and Communication Engineering

Jul 2024 - Jul 2028

Dr K K R s Gowtham Concept School

Class X (High School)

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Score: 94.4%

Sarada Educational Institutions

Class XII (Intermediate/Plus Two)

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Score: 92%

Manipal Institute of Technology (MIT)

B.Tech, Computer and Communication Engineering

July 2024 – June 2028 (Expected)

CGPA: 8.1. Relevant coursework includes Design and Analysis of Algorithms, Database Management Systems (SQL), Object Oriented Programming (Java), Digital System Design, and Computer Organization. Academic focus on NLP, Generative AI, Web Automation, and Scalable Backend Architectures.

Skills

Digital CommunicationAsyncData StructuresMachine LearningVersion ControlObject-Oriented Programming (OOP)Secure Network ArchitectureMatplotlibData CleaningDatabase DesignGoogle APIData ManagementApplied Machine LearningExpress.jsTypeScriptScalable Web ApplicationsBack-End Web DevelopmentCross-functional CollaborationsProgramming LanguagesHistogramsJSON Web Token (JWT)REST APIsJavaReact.jsPandas (Software)Next.jsGitHubTailwind CSSGitJupyterData Structures and AlgorithmsJavaScriptSQLPythonLLM IntegrationGemini APINLPPrompt EngineeringAPI Workflow AutomationNode.jsJWTMongoDBSupabaseVercelPostmanFastAPIOllamaServer Sent EventsDeep LearningConvolutional Neural Networks

Projects

Multimodal AI Evaluation Framework

Engineered a capability-aware benchmark dashboard unifying text, vision, audio, and agent tasks through a FastAPI backend. Optimized lmms-eval, faster-whisper, and inspect-ai execution using subprocesses, implemented real-time SSE streaming for evaluation logs, and normalized diverse engine outputs into a unified JSON schema.

AI Movie Insight Engine

Integrated the Google Gemini API into a React.js application to automate content summary generation and support dynamic user experiences.

Breast Cancer Detection Research

Contributed to a research paper focused on automating breast cancer detection using deep learning and CNNs applied to medical imaging datasets.