CV

Master of Science in Data Science

Columbia University

3.87/4.0

• CourseWork
  • Representation Learning
  • Neural Networks and Deep Learning
  • Advanced Deep Learning
  • Representation Learing
  • Machine Learning
  • Statistical Inference
  • Cloud Computing (Audit)
  • Algorithms for Data Science

Bachelor of Engineering in Electronics and Communications Engineering

B.M.S College Of Engineering

9.37/10.0

• CourseWork
  • Data Structures and Algorithms
  • C
  • Discrete Maths
  • Python
  • Java
  • Operating Systems

NLP - Machine Learning Engineer

Lexalytics

• Optimized KeyPhrase Extraction for multi-lingual customer review data using Huggingface BERT model, improved F1 score to 0.85.
• Streamlined LLM training and fine-tuning pipeline with microservices and Django architecture, enhancing resource utilization and user accessibility.
• Improved LLM inference and validation pipeline by using ONNX runtime accelerator and ONNX quantization.

Graduate Machine Learning Researcher

AIModelshare, Institute for Social and Economic Research and Policy, Columbia University

• Created a fully integrated python library and web application to ease hosting ML models, creating competitions, and performing model analytics.
• Deployed aimodelshare python library on pip and conda-forge channels with 2000+ monthly downloads.
• Implemented model determinism and model replication framework using TensorFlow python with AWS Lambda and S3.
• Designed automated cloud storage, API hosting and Model analytics for Keras and PyTorch Models with Onnx framework.

Graduate Deep Learning Researcher

Columbia WiMNet Lab, Columbia University

• Increased classification accuracy by 30% using Convolutional Neural Networks on Fourier features of radar transmission.
• Developed Time Distributed CNN with LSTMs for image sequence classification, resulting in 35% increase in F1-Score.
• Optimized 5+ Random Forest Ensemble Models and Pipelines on Google Cloud for classification of wind speed from Datasets.
• Performed feature engineering with PCA and TSNE, analyzed 20+ experiment’s data to visualize spatial and temporal properties.
• Formulated and Implemented Data Extraction pipelines for 25+ Radar Measurements to develop range-velocity data.

Course Assistant - Machine Learning Security

Columbia University

Course Assistant - Deep Learning and Neural Networks

Columbia University

Network Engineer-II-Escalation Engineer

Cisco Systems

• Forecasted resource requirements with Regression Models for 8 Quarters. Analyzed Team Performance metrics for 15 Teams.
• Designed Data Pipelines for real-time monitoring of Application Centric Infrastructure labs, improved server utilization by 40%.
• Supervised hiring and mentoring of 28 engineers in Networking, DevOps technologies, Python, and MongoDB.
• Authored 5 technical briefs with a focus on ACI and its integration with Docker, Kubernetes, and OpenStack.
• Drove troubleshooting for ACI Anywhere, Multicloud integration with Amazon Web Services, Azure, and ACI integrations with Openstack, Kubernetes.
• Organized and Trained Engineers on various technologies like Docker, Kubernetes, Linux, Data streaming(Kafka), and Elasticsearch platforms.

Network Engineer-II

Cisco Systems

• Built models for anomaly detection in SSD performance for 500+ companies (9000+ switches), saving 3000+ work hours.
• Spearheaded 30+ projects to enhance Cisco product usability with containerized log analyzers, low-code and IaaC platforms.

Network Engineer-I

Cisco Systems

• Debugged and Troubleshot Cisco ACI’s RAFT and Linux Subprocesses on distributed computing systems for 400+ Customers.
• Integrated Docker and Kubernetes services with ACI on AWS and Azure cloud services.
• SME for ACI 3rd Party Integration such as VMware, Microsoft-SCVMM.

Cisco Data Science Green Belt

Cisco Data Literacy Green Belt

Amazon Web Services - AWS Solution Architect Associate

Cisco Certified Networking Professional - Routing and Switching

Cisco Certified Networking Associate - Routing and Switching