Data Science Machine Learning

Laxmi Vatsalya Daita ********@***.*** **********@*****.***

MS Data Science github.com/LaxmiVatsalyaDaita

East Lansing, USA linkedin.com/in/laxmi-vatsalya-daita

+1-517-***-**** kaggle.com/laxmivatsalyadaita

Education

Degree University CGPA Year

MS, Data Science Michigan State University 4.0/4.0 2024-2026 B.Tech., Electronic and Computer

Engineering

Amrita Vishwa

Vidyapeetham

8.73/10 2019-2023

Research Interests and Publications

Attention Optimization, Transformer Architectures, Machine Unlearning, Natural Language Processing, Computer Vision, Time Series Analysis

• An Improved Clear Channel Assessment Technique for Interference Mitigation in FMCW Radars - Link This paper examines real-only vs. complex baseband mixer architectures in FMCW radars, utilizing statistical analysis and advanced machine learning. A Bayesian-enhanced Clear Channel Assessment (CCA) technique for mitigating interference is proposed, leveraging CSMA protocols. Research Experiences

• Spacelabs Healthcare - OSI Systems Feb 2024 - July 2024 Data Analytics Intern - Research and Development Hyderabad, India

Built 10+ comprehensive dashboards using Azure DevOps and PowerBI to analyze project planning for Q1, Q2, and Q3 of the year 2024; conducting team-wise and feature-wise progress analysis to ensure efficient project tracking and management.

Corresponded with the Director of Engineering and team to deliver actionable insights on project data across 30+ different teams, aiding in strategic decision-making.

Identified a potential risk within the Heart-rate Monitoring System prototype and developed a PoC for anomaly detection using VAEs, LSTM-Autoencoder and statistical modeling, resulting in an increased detection efficiency by upto 17x.

• Aqura Infotech Oct 2023 - May 2024

Data Science and Machine Learning Associate Faculty Visakhapatnam, India

Designed the curriculum for various courses such as Python Programming for Machine Learning, Advanced Machine Learning, Foundations of Data Science and Data Analytics Bootcamp.

Conducted classes 5 days a week and mentored over 100 students in Data Science and Machine Learning. Developed and graded question papers, written assessments, continuous tests, and final exams.

• Indian Institute of Science Sept 2022 - Feb 2024 Research Intern Bengaluru, India

Studied 10+ interference mitigation schemes in FMCW radar networks and the impacts of wideband interference on radar performance. Co-authored a research paper (available on IEEE Xplore)

Responsible for ideating and designing a novel MAC approach for mitigation of narrowband interference using CSMA/CA protocol with CCA enhancements resulting in an increase in throughput upto 3.28x.

Designed real-time simulation scenarios using MATLAB for Self-Drive Cars to test and evaluate the performance of various interference mitigation schemes.

• Microsoft June 2021 - Aug 2021

Engage Mentorship Program Hyderabad, India

Implemented a 1:1 video-chat web application with active facial recognition and a chatbox feature using Node.js, React.js, Chatengine.io.

Utilized Agile Methodologies, Scrum Principles and Kanban Boards for project tracking and optimizing workflow; was one of top 10 participants in the program. Key Projects

• Automatic Caption Generation (MSU - Human Analysis Lab) (In Progress) PyTorch, HuggingFace

Contributed to the Human Analytics Lab’s text-to-image (TTI) project by developing an automated captioning system using a fine-tuned version of Llama 3.2-1B to transform structured facial attribute data

(40 binary labels) into natural, coherent text descriptions for training. Built a data pipeline to preprocess, filter, and convert raw numerical attributes into structured text, leveraging prompt engineering and NLP inference for dataset optimization and improved model performance.

• Text-to-Speech using Transformers (In Progress)

PyTorch

Designed and implemented a deep learning-based text-to-speech (TTS) system using an Encoder-Decoder transformer with multi-headed attention to generate Mel-Spectrograms, and integrated WaveNet for high-quality audio synthesis, leveraging datasets like WMT-2014 and LJ-Speech with preprocessing pipelines for efficient parallel training and near-human speech quality.

• IBM HR Analytics Dashboard Link

MS Excel, PowerBI

Created an interactive visualization dashboard that provides detailed insights into attrition analysis, monthly income distribution, workplace impact analysis, and performance analysis of the employee data, enabling more informed decision-making.

• Sleep Health and Cardiovascular Health Analytics Web App Link Streamlit, Sklearn, Statsmodels, Tensorflow

Developed an interactive Streamlit-based web application integrating advanced machine learning models for sleep disorder and heart risk prediction, BMI calculation, and personalized nutrition advice via an AI-powered chatbot. Designed a user-friendly, self-contained interface with actionable insights, clear visualizations, and ensemble modeling, emphasizing cardiovascular and sleep health analytics.

• Political Speech Analysis Link

Sentiment Analysis using NLTK, LDA, SpaCy, KeyBERT, NRCLex Performed sentiment analysis on Prime Minister’s speech using natural language processing techniques. Utilized Python libraries to pre-process text, analyze positive, negative and neutral sentiments, and visualize results, providing insights into political speech patterns and public sentiment.

• Airport Traffic Analysis during COVID-19 Link

EDA using MapReduce techniques

Applied MapReduce techniques to generate key-value pairs for tasks such as average percentage of baseline calculations, airport listings, and monthly traffic analysis. Conducted EDA to reveal trends and insights across 4 countries: Australia, Chile, Canada, and the USA. Skills

• Programming Languages and Frameworks:Python, SQL, R, MATLAB, C, Jupyter Notebook

• Libraries: Numpy, Pandas, OpenCV, Seaborn, Tensorflow, HuggingFace, Pytorch, Scikit Learn, Statsmodels, NLTK, SpaCy, Streamlit.io, MATLAB Radar Toolbox

• Tools:Git, MS Office Suite, Azure DevOps, MS SQL Server, PowerBI, Tableau, Windows Relevant Coursework

• Deep Learning:AI, ML, Deep Learning, NLP, CV, LLM, MLOps, Data Science, Big Data Analytics, Pattern Recognition

• Mathematics:Probability and Statistics, Linear Algebra and Optimization, Discrete Mathematics

• Computer Science:Data Structure, Advanced Algorithms and Analysis, Cloud Computing, Computer Organization and Architecture, Operating Systems, Computer Networks, Data Base Management Systems Additional Courses

Data Analytics and Visualization (Accenture), Advanced Computer Vision (Udemy), Tensorflow (Udemy) Achievements and Extracurriculars

• Member of the AI Club at Michigan State University.

• Advisor and Coordinator for the robotics club ACROM-IEEE RAS at Amrita Vishwa Vidyapeetham.

• President of the IEEE-Sensors Council at Amrita Vishwa Vidyapeetham.

• Scored in the top 1 percentile in the JEE, exemplifying academic excellence in one of the world’s most competitive exams.

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