Kanika Rajput

AI graduate with hands on experience in cybersecurity and data-driven risk management. Skilled in Python, MATLAB, Tableau, and Excel, with expertise in predictive modeling, NLP, graph analytics, Monte Carlo simulations, and risk assessment. Applied AI to cybersecurity (DDoS mitigation, ISO 27001/27005, MEHARI, NIS2) and data science projects including temporal graph embeddings, human-robot interaction, and data mining systems. Certified in Google Data Analytics, Microsoft Advanced Excel, Python Programming, and UI/UX Design. Passionate about leveraging AI for cybersecurity, analytics, and practical problem-solving.

Cybersecurity AI Coach (Thesis) | MATLAB, Monte Carlo Simulation

• Real time AI decision support for cyber risk mitigation of high intensity DDoS attacks.
• Risk quantification through scenario modeling to inform strategic cybersecurity response.

Temporal node2vec for Dynamic Networks (ML for Graphs) | Python, NetworkX, Embeddings

• Extended node2vec algorithm for temporal dynamics, improving link prediction (AUC: 0.83) and multi label classification (F1: 0.82).

Autonomous Social Robot | Python, NAO Robot, Dialogflow, Human-Robot Interaction (HRI)

• Developed detailed interaction designs to give robots autonomous, realistic personalities.
• Implemented NLP features (Dialogflow) for seamless conversational interactions.
• Conducted thorough literature research to enhance realism and user engagement.
• Managed experimental setups including ethical consent forms, participant briefings, and data collection.
• Improved user perceptions significantly in anthropomorphism, likability, and intelligence, as measured by the Godspeed Questionnaire Series.

Hotel Recommendation System (Data Mining) | ALS, Python, Collaborative Filtering

• Built and optimized implicit-feedback-based recommendation model, addressing large scale dataset challenges.

Mood Prediction & Analytics (Data Mining) | Python, Random Forest, LSTM

• Performed data driven mood prediction achieving 80% accuracy; evaluated strengths and weaknesses of RNNs vs. Random Forest models.

Web Scraping & Sentiment Analytics | Python, NLTK, BeautifulSoup

• Developed automated scraping tools extracting and analyzing sentiment data.
• Performed NLP sentiment analysis to derive actionable insights from textual data.

2D Platformer Game | Unity

• Engineered a narrative driven game with multiple endings based on user interaction.
• Leveraged programming and creative storytelling to enhance user engagement.

• Google Data Analytics (Google)
• Programming for Everybody (Getting Started with Python) (Coursera)
• UI/UX Design (Certification Platform)
• Microsoft Digital Skills Program (Advanced Excel) (Microsoft)

Utilization of AI in Graphic Designing | Global Scientific Journal
(DOI: 20.18001.GSJ.2021.V8I4.21.36940)
Explored integration and impact of artificial intelligence methodologies within graphic design workflows.

I enjoy creating detailed, expressive 3D visuals and abstract art as a personal passion.

Check out some of my work on Behance [https://www.behance.net/kr37].