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% -------------------- Document Begins-----------------------------------



\begin{document}
\begin{flushleft}
{\Huge\textbf{Koduru Suchith}} \\
\vspace{2pt} % Reduced vertical space here
\large\textbf{Computer Science Engineering Graduate, Indian Institute of Technology Delhi'25} \\
\vspace{4pt} % Reduced vertical space here
\faEnvelope \hspace{1pt} \href{mailto:suchith1646@gmail.com}{suchith1646@gmail.com} \hspace{4pt}\(|\)\hspace{4pt}
\faEnvelope \hspace{1pt} \href{mailto:cs1210572@iitd.ac.in}{cs1210572@iitd.ac.in} \hspace{4pt}\(|\)\hspace{4pt}
\faLinkedinSquare \hspace{1pt} \href{https://www.linkedin.com/in/suchith-koduru-34966022b/}{koduru-suchith} \hspace{4pt}\(|\)\hspace{4pt}
\faGithub \hspace{1pt} \href{https://github.com/suchith83}{suchith83} \hspace{4pt}\(|\)\hspace{4pt}
\faPhone \hspace{1pt} +91-8465073250
\end{flushleft}

\vspace{-0.3cm}

% ------- Academic Qualifications ------------

\noindent\rule[0.5ex]{\linewidth}{1pt}
\vspace{-0.85cm}
{\large \textbf{\begin{tcolorbox}[height= 0.6cm, width=20.00cm]\textsc{Academic Qualifications}\end{tcolorbox}}}
\begin{flushleft}
\vspace{-0.23cm}
\begin{center}
\begin{tabular}{|p{2.22cm}|p{5.9cm}|p{8.0cm}|p{2.0cm}|}
\hline

\centering{\textbf{Year}} & \centering{\textbf{Qualification}} & \centering{\textbf{Institute}} & {\hspace{5mm}\textbf{CPI/$\%$}}\\
\hline
\centering{2021} - {2025} & \centering{B.Tech} & \centering{Indian Institute of Technology Delhi} & \hspace{4mm}6.36/10.0\\
\hline
\centering{2021} & \centering{Class \Romannum{12} (SSC)} & \centering{Narayana Educational Institute, Hyderabad} & \hspace{5.5mm}98$\%$\\
\hline
\centering{2019} & \centering{Class \Romannum{10} (SSC)} & \centering{Viswabharathi High School, Gudivada} & \hspace{4mm}10.0/10.0\\
\hline
\end{tabular}
\end{center}
\end{flushleft}
% -----------------scholastic achievements-------------
\vspace{-0.05cm}
{\large \textbf{\begin{tcolorbox}[height= 0.6cm, width=20.00cm]\textsc{Scholastic Achievements}\end{tcolorbox}}}
\vspace{-0.4cm}
\begin{itemize}
    \item Achieved \textbf{All India Rank 479} in \textbf{JEE Advanced 2021}—a national-level engineering exam, among more than 1.2 lakh shortlisted candidates.
    \item Achieved \textbf{All India Rank 620} in \textbf{JEE Mains 2021}—a national-level engineering exam, among more than ten lakh candidates appearing.
    \item Achieved \textbf{Rank 201} in \textbf{TS-EAMCET 2021}—a state-level engineering exam, among over 2.2 lakh students conducted by TS State Board.
    % \item Achieved \textbf{Rank 201} in \textbf{AP-EAMCET 2021}—a state-level engineering exam, among over 2.5 lakh students conducted by AP State Board.
\end{itemize}

% -----------------Work Experience---------------------

\vspace{-0.55cm}

{\large \textbf{\begin{tcolorbox}[height= 0.6cm, width=20.00cm]\textsc{Work Experience}\end{tcolorbox}}}
\vspace{-0.5cm}

% \begin{tcolorbox}[colback=gray!15,height = 5.7mm, width= 20.00cm]

% {\textbf{Bosch Global Software Technologies}\(|\)\textbf{ \,AI/ML Summer Research Intern}}\hfill\hfill(\textit{May'24 - Jul'24})\end{tcolorbox} 

% \vspace{-0.4cm}
% \begin{itemize}

% \item Explored adversarial audio synthesis using various GAN models to generate various noises, time-series datasets, and realistic sounds.
% \item Applied GAN techniques to the MNIST dataset, achieving significant accuracy and demonstrating versatility in model implementation.
% \item Synthesized complex sounds such as drums and bird calls using architectures like \textbf{Simple GAN, GAN with LSTM, DC-GAN, }and\textbf{ WaveGAN}.

% \item Enhanced model performance by leveraging \textbf{CNN}s and \textbf{RNN}s, implementing algorithms from \textbf{Adversarial Audio Synthesis} research paper.
% \end{itemize}
% \vspace{-0.3cm}

% \begin{tcolorbox}[colback=gray!15,height = 5.7mm, width= 20.00cm]
% {\textbf{Large Language Models}} \(|\)\textbf{ Undergraduate Project, Prof. Rohit Budhiraja}\hfill\hfill(\textit{Dec'24 - May'25})\end{tcolorbox}
% \vspace{-0.4cm}
% \begin{itemize}
% \item Executed large-scale conversion of 2TB 3GPP DOCX files into Markdown, reducing processing overhead and optimizing ingestion by \textbf{LLM}s.

% \item Explored and evaluated multiple conversion models (\textbf{Deepseek, Intern VL38B, LlamaVision}) before integrating \textbf{Simpletex} APIs.
% \item Developed custom code enhancements to drastically cut down on conversion time and ensure high reliability across the entire pipeline.
% % \item Explored processing techniques like \textbf{skeletonisation}, \textbf{hough transform} \& canny edge detection to calculate features of dimples
% \end{itemize}

\begin{tcolorbox}[colback=gray!15,height=5.7mm,width=20.00cm]
\textbf{AI Software Engineer – 10xscale.ai} \(|\)\textbf{ Hyderabad-based Startup} \hfill (\textit{June'25 – Present})
\end{tcolorbox}
\vspace{-0.2cm}
\begin{itemize}
    \item Contributed to the open-source agent framework \textbf{\href{https://github.com/10xHub/Agentflow}{Agentflow}}, collaborating on \textbf{large-scale codebases}, enforcing \textbf{code structure}, maintaining \textbf{unit test coverage}, and managing \textbf{pull requests (PRs)}—two of which (\href{https://github.com/10xHub/Agentflow/pull/17}{\#17}, \href{https://github.com/10xHub/Agentflow/pull/19}{\#19}) were successfully \textbf{merged} into the main project.
    
    \item Built a \textbf{Model Context Protocol (MCP)} server for \textbf{PostgreSQL}, enabling natural language querying of structured data. Integrated these tools within \textbf{Agentflow} to create a \textbf{database-aware agent} capable of reasoning over database queries.
    
    \item Designed and implemented a \textbf{multi-agent architecture} using \textbf{LangChain}, \textbf{LangGraph}, and \textbf{FastMCP}, enabling collaboration among specialized agents with contextual memory and scalable execution.
    
    \item Developed agents with \textbf{persistent short-term and long-term memory} using \textbf{Qdrant vector database} and \textbf{Mem0}, improving context retention and long-horizon reasoning across interactions.
    
    \item Utilized \textbf{Git} for version control and \textbf{GitHub Copilot} to improve development productivity. Maintained modular, production-ready code across multiple AI frameworks and services.
    
    \item Created a \textbf{robotic prototype} powered by \textbf{Raspberry Pi}, integrating AI-generated responses into a real-time display for live conversational demonstrations.
    
    \item \textbf{Technologies Used:} Python, Docker, PostgreSQL, Linux, Qdrant, LangChain, LangGraph, Agentflow, FastMCP, Git, GitHub Copilot.
\end{itemize}

\vspace{-0.1cm}

\begin{tcolorbox}[colback=gray!15,height = 5.7mm, width= 20.00cm]
{\textbf{Maternal Health Risk Predictor}} \(|\)\textbf{ Summer Project, Prof. Kapil Tomar}\hfill\hfill(\textit{May'24 - Jul'24})\end{tcolorbox}
\vspace{-0.2cm}
\begin{itemize}
\item Developed a full-stack \textbf{Maternal Health Risk Predictor} under Prof. Kapil Tomar, integrating ML with a responsive web interface for real-time inference.
\item Performed thorough \textbf{data cleaning} and \textbf{outlier removal} on clinical datasets to improve model stability and input reliability.
\item Benchmarked multiple models (\textbf{SVM, RF, XGBoost, Gradient Boosting}); achieved \textbf{99\% accuracy} with Gradient Boosting and exported using \textbf{Pickle}.
\item Designed and deployed a Flask-based app with \textbf{Predict}, \textbf{Result}, and \textbf{Dashboard} pages using HTML, inline CSS, and JavaScript.
\item Highlighted out-of-range inputs in predictions for interpretability and integrated model outputs into a user-friendly result display.
\end{itemize}


\vspace{-6mm}



% -------------- Key Project ------------------

{\large \textbf{\begin{tcolorbox}\textsc{Key Projects}\end{tcolorbox}}}

\vspace{-0.6cm}


% \begin{tcolorbox}[colback=gray!15,height = 5.7mm, width=20.00cm]
% {\textbf{ Computer Networks}} \(|\)\textbf{ CS425A Course Project, Prof. Aditya Vadapalli}\hfill\hfill(\textit{Jan'25 - May'25})
% \end{tcolorbox}
% \vspace{-0.4cm}
% \begin{itemize}
% \item Developed \textbf{multi-threaded C++ chat server} with authentication, group messaging; stress-tested stable at 225 concurrent clients.
% \item Built Python \textbf{iterative/recursive DNS} resolver with timeout / NXDOMAIN handling, sustaining 100+ parallel lookups under 20 ms.
% \item Engineered raw-socket C++ TCP client, hand-crafted IP/TCP headers to complete three-way handshake without kernel stack.
% \item Implemented C++ DV/LS routing simulators \textbf{(Bellman-Ford, Dijkstra)}, parsing adjacency matrices and outputting iterative \& final tables.
% \end{itemize}
% \vspace{-0.3cm}

\begin{tcolorbox}[colback=gray!15,height = 5.7mm, width=20.00cm]
\href{https://github.com/suchith83/Churn-Prediction}{\textbf{ Customer Churn Prediction using Random Forest (Telecom Domain)} \large\faGithub} \hfill\hfill(\textit{May'25 - May'25})
\end{tcolorbox}
\vspace{-0.2cm}
\begin{itemize}
\item Developed an end-to-end \textbf{customer churn prediction} system using the Telco dataset, combining EDA, feature engineering, and model interpretability.
\item Addressed \textbf{class imbalance} using SMOTE and ADASYN; encoded categorical variables and engineered meaningful features from raw attributes.
\item Tuned a \textbf{Random Forest classifier} with grid search over 7+ hyperparameters using stratified k-fold CV.
\item Applied SHAP for model interpretability and implemented \textbf{threshold optimization} to align predictions with business objectives.
\end{itemize}

\vspace{-0.1cm}

\begin{tcolorbox}[colback=gray!15,height = 5.7mm, width= 20.00cm]
{\textbf{Multi-Class Image Classification}} \(|\) \textbf{Machine Learning, Prof. Rahul Garg} \hfill(\textit{Sep'24 - Nov'24})
\end{tcolorbox}
\vspace{-0.2cm}
\begin{itemize}
\item Developed a high-confidence image classification model on the \textbf{CIFAR-100} dataset by experimenting with various architectures and calibration methods.
\item Implemented \textbf{WideResNet (WRN-28-10)} and optimized generalization performance using \textbf{Sharpness-Aware Minimization (SAM)}.
\item Enhanced prediction reliability through \textbf{temperature scaling}, improving calibrated accuracy on high-confidence outputs.
\item \textbf{Technologies Used:} PyTorch, torchvision, NumPy, Matplotlib, pandas
\end{itemize}
\vspace{-0.1cm}
\begin{tcolorbox}[colback=gray!15,height = 5.7mm, width= 20.00cm]
{\textbf{Academic Database System}} \(|\) \textbf{DBMS, Prof. Kaustubh Beedkar} \hfill(\textit{Feb'24 - Mar'24})
\end{tcolorbox}
\vspace{-0.2cm}
\begin{itemize}
\item Designed and implemented a \textbf{PostgreSQL} academic administration database inspired by IIT Delhi’s internal system.
\item Integrated stored functions, triggers, and auto-update mechanisms to streamline academic record management.
\item Built a relational schema and executed SQL queries for efficient data handling and consistency.
\item \textbf{Technologies Used:} MySQL, PostgreSQL
\end{itemize}





\vspace{-5.5mm}


%  -----------Technical Skills------------------


{\large \textbf{\begin{tcolorbox}[height= 0.6cm, width=20.0cm]\textsc{Technical Skills}\end{tcolorbox}}}
\vspace{-0.35cm}
\begin{center}

\begin{tabular}{|m{1.6cm}|m{7.97cm}|m{1.5cm}|m{7cm}| }
\hline
\textbf{Languages} 
&C, C++, Python, SQL, javascript
& \textbf{OS} 
&Linux(ubuntu),Windows
\\
\hline
\textbf{Libraries}
& Langchain, LangGraph, LiteLLM
& \textbf{Utilities} 
&Git, \LaTeX, Docker
\\
\hline
\end{tabular}
\end{center}

\vspace{-0.55cm}

% % -----------------Relevant Courses------------


{\large \textbf{\begin{tcolorbox}[height= 0.6cm, width=20.0cm]\textsc{Relevant Courses}\hfill\small {}\end{tcolorbox}}}
\vspace{-0.4cm}
\begin{center}
\begin{tabular}{|p{4.22cm}|p{7.84cm}|p{6.42cm}|}
\hline
Linear Algebra & Data Structures and Algorithms & Machine Learning \\
Operating Systems & Introduction to Database Management Systems & Computer Architecture \\
Signals and Systems & Analysis and Design of Algorithms & Computer Networks \\
Digital Logic & Introduction to Automata and Theory of Computation & Programming Languages \\
Logic for Computer Science & Probability and Stochastic Processes & Parallel Programming \\
\hline
\end{tabular}
\end{center}
% \vspace{-0.3cm}





\vspace{-0.55cm}

% -----------Positions of Responsibility--------

% {\large \textbf{\begin{tcolorbox}[height= 0.6cm, width=20.0cm]\textsc{Positions of Responsibility}\end{tcolorbox}}}

% \vspace{-0.6cm}

% \begin{tcolorbox}[colback=gray!15,height = 5.7mm, width= 20.00cm]
% \textbf{Secretary, Sports}
% \(|\) \textbf{Hall IX, IIT Kanpur}\hfill(\textit{Aug'24 - Present})
% \end{tcolorbox}
% \vspace{-0.4cm}
% \begin{itemize}   
%         \item Launching and managing \textbf{Volleyball, Basketball, Indoor Sports, and E-sports leagues} to promote physical fitness and community bonding
%         \item Leading the renovation of the badminton court to ensure year-round access and improve the quality of sports facilities for residents
%         \item Organizing exciting sports tournaments and engaging events to enhance participation and community bonding within the hall environment.
%         \item Developing initiatives to ensure access to sports equipment and activities for all hall residents, creating an inclusive sports environment
% \end{itemize}

% \vspace{-0.3cm}

% \vspace{-0.55cm}

% {\large \textbf{\begin{tcolorbox}[height= 0.6cm, width=20.0cm]\textsc{Extra Cirriculars}\end{tcolorbox}}}
% \vspace{-0.35cm}
% \begin{itemize}   
%         \item Volunteered at the Student Placement Office, assisting with logistics for interviews and recruitment processes for major companies.
%         \item Contributed to the winning cricket team in the Cricket Tournament conducted by TSS, IIT Kanpur, showcasing teamwork and sportsmanship.
%         \item Won multiple intra-school running competitions, including 100m, 200m, and 4x100m relay races, demonstrating athletic excellence.
%         \item Played a key role in the runner-up volleyball team during intra-school sports events, fostering collaboration and competitive spirit.
% \end{itemize}

% \vspace{-0.3cm}
\end{document}