Photo of Lokesh Manideep Boggavarapu

Lokesh Manideep Boggavarapu

Graduate Research Assistant, Biostatistical Research Program

Department of Psychiatry, UIC

Masters Student, Department of Computer Science

he/him

Contact

Email:

lbogg [at] uic.edu

Office Phone:

(312) 593-4531

Building & Room:

School of Public Health / Psychiatric Institute (SPHPI) 478

Address:

1601 W. Taylor St. SPHPI MC 912 Chicago IL 60612

Related Sites:

About

Lokesh is a seasoned software developer with experience in web and iOS development specializing in developing scalable and user-friendly apps. With a strong foundation in backend systems, cloud computing, and data analytics, he has been able to design and deploy intricate solutions in various fields. His experience encompasses development with Python, AWS, Swift(UIKit) and Spring Boot, enabling him to develop high-performing applications that enhance user experience and business efficiency. Lokesh has also done AI-based projects, refining models like LLAMA and Mistral to more effectively classify posts regarding mental health on Reddit.

Besides programming skills, Lokesh is also highly trained in research, having used advanced machine learning techniques to examine crowdfunding campaigns and optimize fundraising techniques. He has also created innovative platforms like the UIC Calendar web application, which combines university events by utilizing web scraping in an automated way.With a passion for applying technology to solve real-world problems, Lokesh is constantly on the lookout for ways to innovate beyond boundaries.

Software Engineering, Machine learning, Artificial Intelligence, Healthcare Analytics

UIC RRTC DISCOVER Chatbot Project (funded by NIDILRR)

This project takes place at government-funded Rehabilitation Research and Training Centers (RRTCs) on mental health conditions at Boston University, Temple University, University of Massachusetts, and University of Illinois Chicago (UIC). For decades these centers have designed and tested psychiatric rehabilitation interventions, created products for use by the field, published influential articles, and informed public policy. Each RRTC offers a wealth of information, tools, research findings, and other products to the mental health workforce and public. However, accessing this information requires combing through multiple web sites, reducing the likelihood of finding and using them. Our project will design and implement a customized Artificial Intelligence (AI) chatbot called Discover, to both personalize the search experience and efficiently guide users to each RRTC’s high-quality information.

    • Evaluating Enhanced LLMs for Precise Mental Health Diagnosis from Clinical Notes - Read the PDF Article
    • Towards Understanding Bipolar Disorder Through Social Media and Transformer Models: Challenges and Insights - Read the PDF Article
    • Robust cancer crowdfunding predictions: Leveraging large language models and machine learning for success analysis - Read the PDF Article