Aravind Cheruvu

Graduate Student (Ph.D.)
Department of CS, Virginia Tech
acheruvu@vt.edu

About Me

I am Aravind Cheruvu, a graduate student (MS + Ph.D.) from the Dept. of C.S. at Virginia Tech. I am advised by Dr. Bimal Viswanath.
I look into the security aspects of Generative AI models. I have experience working with GANs, and diffusion models in the vision domain and state-of-the-art Large language models (LLMs) in the text domain. I am currently investigating toxicity injection attacks and mitigation in open-domain chatbots.

I have completed my Bachelors in Information Technology in 2016 from VNR VJIET, Hyderabad (affliated to JNTU) where I have gained research experience in the areas of Temporal Data Mining and Network Security.

Apart from my research experience, I have 4.5 years of work experience as a Oracle payroll implementation specialist at Deloitte Consulting. I have worked on several large scale projects with several US-based clients.


Check out my resume here.

Latest News

Publications

Ph.D. Publications
  • A First Look at Toxicity Injection Attacks on Open-domain Chatbots
    Aravind Cheruvu, Connor Weeks, Sifat Muhammad Abdullah, Shravya Kanchi, Daphne Yao, and Bimal Viswanath
    ACSAC 2023, Austin, Texas, December 2023.
    PDF Code and dataset

  • An Analysis of Recent Advances in Deepfake Image Detection in an Evolving Threat Landscape
    Sifat Muhammad Abdullah, Aravind Cheruvu, Shravya Kanchi, Taejoong Chung, Peng Gao, Murtuza Jadliwala and Bimal Viswanath
    IEEE S&P (Oakland) 2024, San Francisco, CA, May 2024.
    PDF Code and dataset

Prior Publications
  • Estimating temporal pattern bounds using negative support computations
    Aravind Cheruvu, V Radhakrishna
    International Conference on Engineering & MIS 2016

  • VRKSHA: A novel multi-tree based sequential approach for seasonal pattern mining
    Shadi Aljawarneh, V Radhakrishna, Aravind Cheruvu
    International Conference on Engineering & MIS 2018

  • Feature clustering for anomaly detection using improved fuzzy membership function
    Gunupudi Rajesh Kumar, Nimmala Mangathayaru, Gugulothu Narsimha, Aravind Cheruvu
    International Conference on Engineering & MIS 2018

  • A dissimilarity measure for mining similar temporal association patterns
    Vangipuram Radhakrishna, PV Kumar, Vinjamuri Janaki, Aravind Cheruvu
    IADIS International Journal on Computer Science and Information Systems 2017

for more publication list refer to my Google Scholar link.

Education

  • Virginia Polytechnic Institute And State University (Virginia Tech)

    Ph.D. in computer Science (M.S. along the way)

    Aug 2021 - Present

    CGPA: 3.71 *

    Graduate courses: Data Analytics, Deep Learning, Hot Topics in Security and AI, Theory of Algorithms, Advanced Machine Learning, Security risks of Generative AI

  • Jawaharlal Nehru Technological University (VNR VJIET)

    Bachelors in Information Technology

    Sep 2012 - May 2016

    CGPA: 8.51/10.0 "Gold Medal for best outgoing student from the Department of I.T."

Work Experience

  • Deloitte Consulting

    Certified Techno-Functional payroll consultant with 4.5 years of experience in RICEF delivery and Payroll data analysis working for many US based large scale clients in the Financial, Health, Security and Government sectors.

    Senior Consultant

    Jun 2021 - Jul 2021

    Planned and executed Payroll compare and Provider Compensation compare cycles for Healthcare client with 120k+ workforce using a custom tool designed to compare compensation rules for providers pay between Legacy and test system.

    Consultant

    Sep 2018 - Jun 2021

    Payroll Reconciliation: Led planning and execution of Payroll Compare cycles to analyze $MM payroll data working closely with multiple stakeholders, identify system implementation defects, Go-Live and Post Production impacts mitigating risks of Production Go-Live.

    Developed and streamlined Payroll Compare Tool which uses payroll run data between Legacy and simulated Test systems to produce Payroll Compare reports and Executive Dashboards to extensively perform Payroll data analysis and understand system quality.

    Payroll RICEF: Supported payroll configuration, Coordinated and executed SIT and UAT testing cycles and proposed functional design solutions for nearly 30 RICEF objects.

    Business Analyst

    Dec 2016 - Aug 2018

    Technical Developer: Worked as a Technical team member implementing key out-of-box integrations using HCM Extracts, BI Publisher Reports and developed Payroll Fast Formulas.

  • Tata Consultancy Services

    Assistant System Engineer - Trainee

    Jun 2016 - Sep 2016

    Trained in E-Business Suite, Oracle Business Intelligence EE and Oracle Data Integrator tools.

Achievements

Skills

  • Machine Learning tools: GANs (StyleGAN), Diffusion models (Stable Diffusion), Large language Models (LLAMA2, FALCON, Vicuna, FLAN)
  • Machine Learning libraries: Huggingface, Large language Models,PyTorch, Numpy, Scikit-Learn, Pandas
  • Programming Languages: Python, Java, C, C++, HTML/CSS
  • Developer Tools: SQL Developer, VS Code, Eclipse, Netbeans, Android Studio, Weka
  • Technologies/Frameworks: Linux, GitHub, Java Swing, AWT
  • Oracle Tools/Software: Oracle SQL, Oracle HCM Cloud HR And Payroll Module, Payroll Parallel/Reconciliation Tool (Data Analysis), HCM Extracts, Oracle BI Reports, Fast Formulas