Nagendra Chaudhary

• Developed a RESTful Weather API aggregating METAR/forecast data, reducing data fetch time by 70%. • Built an Airport Status API with METAR failover and health checks, improving system availability to 99%+. • Cut API latency by 94% (800ms to 50ms) with Redis caching layer with TTL policies and cache-key indexing.

Designing and implementing machine learning models to enhance cybersecurity systems, leveraging frameworks such as TensorFlow and PyTorch. Conducting research on AI-driven cybersecurity applications, collaborating on the development of tools and datasets for advanced threat detection. Enhanced anomaly detection precision by implementing unsupervised machine learning models, reducing false positive alerts in SIEM systems by 85%, improving incident response efficiency. Developed and optimized clustering-based techniques (e.g., DBSCAN, Isolation Forest, Autoencoders) to detect network anomalies in real-time, minimizing manual intervention. • Engineered a feature extraction pipeline leveraging time-series analysis, statistical heuristics, and deep learning embeddings to improve anomaly classification in high-throughput environments. • Integrated ML-driven anomaly detection into SIEM workflows, enhancing security event correlation and reducing noise for security analysts. • Optimized detection latency by leveraging streaming data architectures (e.g., Apache Kafka, Spark Streaming) to process high-volume network logs efficiently. • Implemented adversarial testing frameworks to assess model robustness against evasion techniques, improving resilience to sophisticated cyber threats. • Conducted comparative benchmarking of multiple unsupervised learning models on large-scale network datasets, improving anomaly detection recall and precision. • Designed an explainable AI (XAI) framework to interpret ML-driven alerts, increasing SOC (Security Operations Center) trust in automated anomaly detection insights.

• Led a diverse residential community of 400 students, fostering an inclusive and collaborative environment while resolving conflicts and enforcing university policies. • Organized and facilitated leadership workshops, community events, and mentorship programs, enhancing student engagement and problem-solving skills.

• Provided comprehensive tutoring and academic support to over 20 students across various subjects, including Elementary Statistics, Discrete Mathematics, and others; collaborated closely with faculty and coaching staff to align academic goals with athletic commitments, ensuring the success of student-athletes; • Facilitated exam preparation sessions and offered personalized guidance during critical assessment periods, resulting in a 25% average increase in student performance; • Developed and implemented tailored learning strategies, leading to a 30% improvement in understanding complex concepts among students.

-Resolved over 500 individual tickets, achieving 90% satisfaction rate by delivering accurate troubleshooting for software issues. - Flashed operating system images on over 300 computers, reducing setup time by 25% and improving deployment efficiency by standardizing system configurations across all devices. -Enhanced the campus Wi-Fi network by collaborating with the network operations team, resulting in a 30% improvement in signal strength through strategic point placements

Developed and maintained RESTful APIs using JavaScript (Node.js) and SQL, powering real-time profile matching for 10,000+ users. Built scalable data pipelines to automate lead processing and improve match accuracy by 30%. Deployed and managed backend services on DigitalOcean using Docker and Nginx for secure, efficient cloud infrastructure. Collaborated with cross-functional teams to optimize performance, enhance security, and deliver high-impact user features.

Designed and launched Umoja, an AI-powered student engagement and pod-matching platform, serving 200+ students from kindergarten through college. Built a scalable multi-age assessment engine and automated group-matching workflow using Next.js, Supabase, and PostgreSQL. Improved group cohesion and learning outcomes by enabling personalized, interest-based student pods and dynamic survey analytics. Led a cross-functional team to pilot, iterate, and deliver features based on user feedback, driving higher engagement and satisfaction.

Developed 5+ AI-powered apps and APIs using Next.js, OpenAI, Pinecone, Clerk, Azure, Python, and Stripe API, reaching 1,000 users with 98% accuracy. Optimized API response times by 45% with multi-threading and enhanced application performance.