Dhruv Kimothi
VIT' 26 | Final Year
About
I’m a final-year Computer Science student who genuinely loves learning, building, and working with people. I’m excited to start my journey with a team where I can grow and contribute to something meaningful and learn every step of theway. I care about doing good work and doing it together by sharing every piece of experience with my fellows.
Experience
Member of IETE
IETE VIT-AP
2 yrs 9 mos
Google Cloud Facilitator Program (Cohort-1)
Google Cloud Arcade Facilitator Program
3 mos · India
Successfully completed the Google Cloud Facilitator Program (Cohort-1), gaining hands-on expertise across core Google Cloud Platform services. Earned multiple Google Cloud skill badges, demonstrating proficiency in cloud infrastructure, data, and machine learning
Summer Internship
Defence Research and Development Organisation (DRDO)
2 mos · Jodhpur, Rajasthan, India
Summer Intern
Defense Research and Development Organization (DRDO)
May 2024–June 2024
Designed and developed a realistic 3D office simulation using Blender, improving rendering efficiency by 25% through optimized lighting and texture mapping. Collaborated with the design and simulation team to automate layout configurations for model scaling and asset reuse.
Business Analytics Intern
Finlatics
June 2024–September 2024
Processed and cleaned over 50,000 data points using Excel and SQL to generate performance insights and KPIs. Built interactive Power BI dashboards using DAX and data models to visualize trends and support strategic decision-making.
Education
VIT-AP University
Bachelor of Technology - BTech, Computer science
Sep 2022 - Jun 2026
CGPA: 8.75
delhi public school jodhpur
Pcm
Apr 2021 - Jul 2022
delhi public school jodhpur
Matriculation
Apr 2019 - Mar 2020
Delhi Public School, Jodhpur
Class 12 (CBSE)
2021–2022
90.8%
Delhi Public School, Jodhpur
Class 10 (CBSE)
2019–2020
94%
Skills
Projects
Fasal Rakshak (Agentic AI Advisor)
Developed an AI-based advisory system for farmers using LangChain, Google Gemini, and RAG architecture to provide real-time insights based on live weather APIs. Deployed on Streamlit and Telegram for accessibility.
Veritas Engine (Phishing Detection)
Engineered a context-aware phishing detection system by fine-tuning a DistilBERT transformer model, achieving 98% accuracy. Deployed the NLP model as a real-time inference API using Flask.
MalwareGPT (ASM Threat Intel)
Engineered an automated malware classifier analyzing N-gram OpCode heuristics to identify threat families. Built a real-time async API using FastAPI and Next.js, featuring Explainable AI with SHAP and live LLM report streaming via Server-Sent Events.