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Mehul KalaMK
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Mehul Kala

@mehulkala

Software engineering intern at CVENT who cut Active Directory device-detail retrieval time by 75%.

India
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At CVENT, I optimized PowerShell-based Active Directory cleanup automation, reducing device-detail retrieval time from 60 minutes to 15. I also added buffered logging and redesigned cleanup checks to help protect devices and preserve LAPS/BitLocker credentials.

I developed a C#/.NET helper to migrate LAPS/BitLocker recovery data from CSV files to PostgreSQL, with per-device transactions, upserts, and duplicate-key handling. I also resolved 17 vulnerability-remediation tickets and supported Cyber Essentials audit readiness.

As a Student Research Fellow at Cyber Security Research Centre, Punjab Engineering College, Chandigarh, I evaluated an Isolation Forest model on a synthetic IPDR dataset covering 2,000 users, achieving an ROC-AUC of 0.8942. I also designed a proposed temporal anomaly-detection framework and a Kafka-based ingestion and parallel-processing pipeline.

In my projects, I built Linkora, a URL-shortening platform with Redis-backed click tracking and batched PostgreSQL synchronization, and SilentChat, a real-time chat platform. I also developed Sereniq, a wellness platform with an AI-powered weekly reflection system using LangChain.js and Groq.

Experience

Work history, roles, and key accomplishments

CC

Student Research Fellow

Cyber Security Research Centre, Punjab Engineering College

Developed and evaluated an Isolation Forest anomaly-detection model on a synthetic IPDR dataset, achieving an ROC-AUC of 0.8942. Designed a Kafka-based ingestion pipeline for streaming user-specific IPDR records.

Education

Degrees, certifications, and relevant coursework

PU

Punjab Engineering College (Deemed to be University)

B. Tech, Computer Science and Engineering

Grade: 8.34

Activities and societies: Relevant Coursework: Software Engineering, OOP, DBMS, Operating Systems, Computer Networks

Pursuing a B.Tech in Computer Science and Engineering with an expected graduation in 2027. Achieved a CGPA of 8.34 on a 10-point scale.

GB

Google Cloud Skill Boost

Generative AI Learning Paths, Generative AI

Completed Beginner, Intermediate, and Advanced Generative AI Learning Paths.

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