Sai Krishna Bala Email & Phone Number

Bengaluru, Karnataka, India

Projects at Ericsson:End-to-End ML Pipelines: Spearheaded the development of machine learning pipelines for managed service networks, encompassing problem formulation, exploratory data analysis (EDA), feasibility analysis, modeling, feedback loops, and productization.Test Case Generation Pipeline: Developed a code generation pipeline utilizing Mixtral 8x7b, Code Llama, and Tree-sitter for Java and Erlang languages, streamlining feature request handling.Conversational Assistant (RAG-based): Built a Retrieval Augmented Generation (RAG) conversational assistant for finance and accounting directives, achieving 96% accuracy in the retrieval stage using models such as MPNet, MiniLM, and Llama2 7b.LLM Evaluation: Conducted comprehensive studies on the evaluation of Large Language Models (LLMs), leveraging tools like RAGAS, Deepchecks, and Arize to ensure robust performance metrics.KPI Throughput & Latency Prediction: Developed predictive models for throughput and latency degradation in telecom networks (MBNL, T-Mobile, Verizon) using time-series data and models like PySpark, XGBoost, and LSTM.ML Ops Framework: Conducted a feasibility study on deploying IoT-related machine learning use cases using Kubeflow and Google Kubernetes Engine.Label Reader: Built a scene text detection and recognition pipeline using PaddleOCR and Azure Kubernetes Services (AKS) to extract product information from images at telecom site locations.Smart Forest Monitoring: Designed and deployed an ML pipeline using MobileNet and YOLOv5 on edge devices (Raspberry Pi) to detect and count animals in forest environments via Balena Cloud.

Bengaluru Area, India

Led and guided end-to-end development in content intelligence and user profiling initiatives:Doubt Resolution: Developed prediction capabilities to analyze academic images or text and retrieve the closest related question or concept.De-duplication Layer: Designed a parallel neural network architecture to detect and flag duplicate academic questions.Smart Tagging: Built prediction models to identify key attributes (subject, chapter, concept) related to academic questions.Concept Mastery: Created algorithms to predict skill or concept mastery for students using the platform.Academic Name Disambiguation: Implemented clustering techniques to map academic noun phrases to their respective concepts.Technologies used: Auto Encoders, Universal Sentence Encoders, Language Models, Xgboost, DeepCTR, BERT, UMLFit, Deep Knowledge Tracing

Bengaluru Area, India

Worked on a range of projects focused on healthcare analytics, building scalable machine learning models to address various challenges in the medical domain:Sentiment Analysis: Developed a sentiment analysis model to classify patient reviews of healthcare providers (physicians, payers) with high accuracy.Technologies used: LSTM, F1 Score: 0.97Prediction Layer in Medical Technology Devices: Implemented a prediction layer to forecast market trends in medical devices, reducing manual effort by 80%.Technologies used: Random Forests, F1 Score: 0.92Data Standardization: Designed a data standardization framework for medical procedure and test names using K-Means++ clustering algorithm.Disease Prediction: Built a classification model to predict diseases for patients based on their therapy or treatment group.Technologies used: LightGBM, AUC: 0.9, F1 Score: 0.94Patient Readmission Rate Prediction: Developed a model to predict unplanned hospital readmissions using historical US healthcare claims data.Technologies used: Logistic Regression, AUC: 0.87, F1 Score: 0.91

Bengaluru Area, India

Worked on implementing machine learning models to enhance HR optimization solutions by automating processes and improving decision-making efficiency:HR Optimization Platform: Integrated machine learning models into the HR platform to streamline candidate evaluation.Classification: Developed Naïve Bayes-based text classifiers to categorize resumes into domains such as IT, FMCG, Mining, Automobile, and Manufacturing.Performance: Achieved an F1-score of 0.88 on the test set.Clustering Algorithms: Designed and developed clustering approaches (DBSCAN and K-Means++) for analyzing a corpus of resumes, job descriptions, and company reports.Resume Parser: Built parsing algorithms using Naïve Bayes to extract personally identifiable information (PII) from resumes, achieving an F1-score of 0.95.Employee Joining Propensity: Developed a logistic classifier to predict the likelihood of a candidate joining a company, achieving an F1-score of 0.96 in offline datasets and 0.9 in production.Skill Repository: Created a semantic knowledge layer for skills in the IT industry using Neo4j graph database, enriched by word2vec embeddings.

Bangalore

Led the development and optimization of data-driven platforms and solutions:Batch Data Platform: Collaborated with the analytics team on feature extraction, model tuning, and production deployment of data models.Model Productization: Productized models using the PMML feature in Spark to streamline model deployment.MapReduce to Spark Migration: Converted the default MapReduce codebase to a more efficient Spark-based environment.Customer Targeting Models: Applied Logistic Regression and Random Forest to identify the right customers for product targeting.

Bangalore

Ad-hoc Search Tool: Developed a custom search tool over raw data using Elasticsearch to enhance data retrieval.PxOE Solutions: Designed and developed the client-side framework of the Px-OE platform. Migrated client-side storage to Cassandra and automated the deployment of Predictive Experience Solutions for service delivery teams.

Bengaluru Area, India

Contributed to the design and development of key distributed systems and internal frameworks:MapReduce Framework: Played a crucial role in the design and development of the internal MapReduce framework, optimizing the processing of large-scale data.Distributed System: Led the conversion of a standalone system to a distributed scenario, improving scalability and system performance.Monitoring Tools: Developed and implemented tools for monitoring the application processes across internal node networks.

Master'S Degree, Computer Science

Me, Data Mining

Activities and Societies: part of telugu samiti, swmming and passing time @ faculty clubCampus Life @ IISc rocks... most memorable days.

Bachelor Of Technology (B.Tech.), Computer Science

Education record