Greetings! As a research assistant and AI enthusiast, I study a variety of industries, including sports, healthcare, and fintech. I begin my mornings with a cup of coffee and then go deeply into data to work on turning difficult problems into creative answers.I'm Praneeth Sunkavalli, a Pennsylvania State University master's student studying data analytics. I am enthusiastic about using data to find practical insights and inform strategic decision-making, and I have a strong interest in the fields of artificial intelligence and data science. I have a solid foundation in statistical analysis, machine learning, and making data-driven decisions thanks to my academic experience at Penn State. Through hands-on projects and internships, I have developed practical skills in Python, R, SQL, and various data analytics tools, which have enabled me to tackle complex data challenges and contribute to meaningful outcomes. I thrive in collaborative environments where innovative thinking and problem-solving are encouraged, and I am always eager to learn and adapt to new technologies and methodologies.My goal is to apply my expertise in Data Science and AI to solve real-world problems and create value for organizations. Feel free to connect with me to discuss data analytics, AI, or potential opportunities to collaborate!
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Data ScientistMyrainaMalvern, Pa, Us
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Research Assistant (Ppira Awardee)Penn State Great Valley Sep 2024 - PresentProject: Enhancing Cybersecurity Readiness in Non-Profit OrganizationsAwarded as the First recipient of the Presidential Strategic Initiative on Public Impact Research (PPIRA)• Scraped data from 80,000 non-profit organizations to extract financial information such as revenue, assets, and organizational types. Developed and implemented metrics to evaluate and measure the social impact of these NPOs.• Created a solution to filter non-profit organizations to 400 by leveraging cluster analysis and assessing criteria like revenue, assets, and tax form types, enabling the precise identification of relevant organizations for specific objectives.• Analysed survey data (descriptive questions and interviews), applying NLP techniques with the T5 LLM model to summarize the responses and quantifying information to categorize the NPOs into safe, at-risk, and in-progress categories. -
Research AssistantPenn State Scranton May 2024 - Sep 2024Project: Influence of Societal Readiness on Energy Marketplace• Developed a BeautifulSoup-based tool to gather the past 4 decades’ financial information of multiple energy sector companies, including energy production and consumption, and analyzed public sentiment towards nuclear and clean energy.• Constructed an OLS model to assess the impact of societal acceptance of sustainable energy on the Market Capital and Returns of energy companies achieving an R-squared value of 0.7 while accounting for energy production and consumption factors.• Conducted a thorough analysis to determine the relationships between staff expenses and energy production and consumption, as well as between return volatility and these energy metrics, resulting in a linear relationship. -
Research AssistantPenn State Scranton Mar 2024 - Jun 2024Project Title: Inflation Expectations Inferred from Economic News• Extracted 40 years’ worth of public information on the Federal Rate and Consumer Price Index, subsequently managing 10,000+ data points on a MySQL server database.• Implemented NLP and pre-trained embedding models such as Universal Sentence Encoder to transform the textual data into a numeric vector, followed by classification models to establish an AUC of 0.73 to predict the change in the inflation rate.• Evaluated diverse embedding techniques (tiktoken, sentencepiece) and deep learning algorithms including Transformers and advanced NLP models (BERT, GPT ), leading to a significant increase in model accuracy from 60% to 82%.
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Research AssistantPenn State University Sep 2023 - Mar 2024Pennsylvania, United StatesProject: High-Frequency Trading Forecast and Adversarial Attacks• Programmed a multivariate time series deep learning architecture, integrating CNN for feature extraction, coupled with an LSTM model, achieving an accuracy of around 78% and an F1-score of 0.7 on high-frequency trading (HFT) data. • Conducted gradient-based and optimization-based adversarial attack algorithms with varying epsilon values to evaluate model resilience, revealing a significant average accuracy reduction of 42%.• Managed and sustained Docker containers to ensure version control and streamlined deployment for 3 teams.• Implemented KPI dashboards and reports to monitor model performance, attack parameters, and security metrics, enabling initiative-taking adjustments and enhancements. -
Graduate Student AdvisorPenn State Nittany Ai Alliance Sep 2023 - Mar 2024• Provided mentorship and guidance to a 7-person undergraduate team throughout the development of predictive models for the American Red Cross, meeting all specifications for a year-long analytics project.• Secured and integrated supplementary data for model optimization, including critical details such as livelihood information, population density, weather details, and many more, which raised the accuracy by 7%.• Experienced in implementing various machine learning and deep learning models across diverse domains, focusing on optimizing model efficiency. Proficient in conducting data research to identify and integrate supplementary datasets for enhanced model performance.• Conducted bi-weekly progress meetings with students and coordinated updates with the partnered companies.• Partnered with multinational companies such as Microsoft, Accenture, and Lockheed to support prototype development and problem-solving and leveraged industry insights and resources to support the project. -
Machine Learning InternFeynn Labs Aug 2022 - Oct 2022Hyderabad, Telangana, India• Developed 10+ sustainable pipelines facilitating the seamless deployment of scalable machine learning models from research to production on the Google Cloud Platform.• Discovered crucial trends and patterns using statistical analytics and modeling, which enhanced strategic decisions.• Collaborated closely with 4 teams from various fields to analyze their workflows and suggest deep learning models that substantially improved accuracy and efficiency in data processing, thereby enhancing operational performance. -
Machine Learning InternVerzeo Apr 2020 - May 2020Hyderabad, Telangana, India• Engineered machine learning models with an accuracy of over 70%, and diagnosed to generate crucial insights that drive business decisions and organizational goals.• Created around 30+ detailed reports, 20+ engaging dashboards using Tableau, and visually appealing presentations to communicate data-driven information effectively. This helped convey complex information clearly and engagingly.• Cross-functional collaboration to achieve project goals, demonstrating strong communication and teamwork skills.
Praneeth Sunkavalli Education Details
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3.96/4.0
Frequently Asked Questions about Praneeth Sunkavalli
What company does Praneeth Sunkavalli work for?
Praneeth Sunkavalli works for Myraina
What is Praneeth Sunkavalli's role at the current company?
Praneeth Sunkavalli's current role is Data Scientist.
What schools did Praneeth Sunkavalli attend?
Praneeth Sunkavalli attended Penn State University, Jawaharlal Nehru Technological University.
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