Ramesh Maddula
Data AnalystAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Software Engineer, Machine Learning at Meta
I have a passion for the seamless integration of technology into everyday life and I firmly believe in the ability of software to help millions of people in the developing world live healthier lives, and participate in the global economy. My Internships and projects provided me the required technical expertise to pursue a career in technology. I pursued my undergraduate research on applications of evolutionary algorithms in Computational Neuroscience. My Master's Thesis is on improving Deep Recurrent Convolutional Neural Networks in order to efficiently classify the P300 BCI signals. I have also had the opportunity to publish and present my research work at several esteemed conferences and journals. Moreover, the leadership opportunities and experiences I have been exposed to as a student of IIT Indore, have had a tremendous impact on my passions outside the circle of academics. I look forward to a truly transformational experience, which will hone my skills to enable me to use technology as a tool to improve the quality of life at an individual level and in a broader global context.
UC San Diego
Master’s Degree, computer science
January 1, 2015 – January 1, 2017
Indian Institute of Technology, Indore
Bachelor of Technology (B.Tech), Computer Science and Engineering
January 1, 2011 – January 1, 2015
narayana junior college, visakhpatnam
High School
January 1, 2009 – January 1, 2011
Meta
Software Engineer, Machine Learning
April 1, 2019 – Present
Menlo Park, California
Groupon
Software Development Engineer - Machine Learning
April 1, 2017 – March 1, 2019
San Francisco Bay Area
Groupon
Software Development Engineering Intern
June 1, 2016 – September 1, 2016
San Francisco Bay Area
University of California, San Diego
Graduate Student Researcher (Master's Thesis Student)
March 1, 2016 – March 1, 2017
San Diego County, California, United States
Systango
Software Developer Intern
May 1, 2014 – July 1, 2014
Greater Indore Area
Indian Institute of Technology, Indore
General Secretary, Academic Affairs
July 1, 2013 – May 1, 2014
Greater Indore Area
Student Ambassador
July 1, 2013 – May 1, 2014
Greater Indore Area
Microsoft
Student Associate
May 1, 2013 – June 1, 2014
Greater Indore Area
Avatar Enterprise Technologies Inc
Research Intern
May 1, 2013 – July 1, 2014
Charlotte Metro
Indian Institute of Technology, Indore
Founding President
May 1, 2013 – May 1, 2014
Greater Indore Area
Indian Institute of Technology, Indore
Branch Senator
May 1, 2012 – June 1, 2013
Greater Indore Area
Exploring Various Techniques for Rating Prediction from Review Text on Google Local Data
March 1, 2017 – Present
i. Predicted the rating of the restaurants listed in the Google Local Dataset. In particular, the semantics of the review are exploited in order to estimate the corresponding rating. ii. Employed several feature extraction strategies such as Unigrams, Bigrams, Term Frequency-Inverse Document Frequency (TF-IDF), Latent Dirichlet Allocation(LDA), LDA with a sentiment feature, and Word2Vec representation, and analyzed how performance varies across various regression models. iii. On an overall, ’LDA + Sentiment of a Review’ model when used in concert with Gradient Boosting Regression performed the best in terms of MSE.
Cache Simulator (Computer Architecture Course Project)
May 1, 2016 – Present
● Developed a simulation of L1, L2 and Victim cache hierarchy with a high-cost memory latency operation with the aim of minimizing Average Memory Access Time.
Perceptron + Gshare branch predictor (Computer Architecture Course Project)
April 1, 2016 – Present
● Implemented gShare, Bimodal and Tournament branch predictor (Combining gShare and Bimodal based upon the design employed by the alpha 21264) with dedicated memory which learns the pattern of branch instructions and predicted the outcome of the next instruction. ● Also Implemented a custom branch predictor, by combining gShare and Perceptron predictors. In the perceptron predictor, perceptrons are used as an alternative to the commonly used two-bit counters. On an overall, the Perceptron + Gshare predictor achieved higher accuracy while compared to the other predictors, on the SPEC'95 benchmark traces.
Convolutional Neural Networks For Learning P300 EEG Signal Representations
January 1, 2016 – Present
● Designed a model based on convolutional neural network to detect the presence of P300 in an EEG Signal. ● With an accuracy of 80%, the model outperformed other benchmark models based on traditional machine learning techniques.
Video Classification by combining Convolutional Neural Networks and Recurrent Neural Networks
January 1, 2016 – March 1, 2016
1. Video classification on UCF-101 Dataset using transfer learned frame representations from Convolutional Neural Nets (CNN) fed into different configurations of Recurrent Nets. 2. Combined a proven CNN model with different Recurrent Neural Networks (RNNs) such as Vanilla RNN, Bidirectional RNN, Long Short Term Memory Networks (LSTM), Bidirectional LSTM and deep LSTM. 3. Results demonstrated significant performance improvements over recently published results on UCF-101 obtained by using similar CNN+RNN architecture.
Pac Man Clone
May 1, 2014 – Present
• Developed a 3D Pac-Man game using C++ and OpenGL by remodeling the objectives of the game, behavior of the objects, and the movements of Pac-Man. Improved the original Pac-man game by enhancing real-time artificial intelligence and adding more challenging game play to the classic game.
JSON Parser
May 1, 2014 – Present
• Designed framework for a JSON Parser using lex and yacc tools for understanding the JSON language syntax, validating the JSON script and parsing the JSON data.
Brain Computer Interface System for Automatic Epileptic Seizure Detection
May 1, 2014 – April 1, 2015
● Designed a Windows application & Android App for real time automatic detection and prediction of epileptic seizures. ● Proposed and developed a Hybrid Genetic Programming classifier, improved classification accuracy and achieved higher computational speed compared to the existing Genetic Programming classifiers.
Online Shopping Portal
December 1, 2013 – Present
● Designed an E-Commerce website which enables customers to buy online and provide a soothing shopping experience for customers, while at the same time allowing them to post queries and manage discussion forums. ● A Relational Database design was implemented for storage and information retrieval, query processing, multiuser transaction processing. Triggers and Assertions are used for enforcing restrictions on the database
Efficient Class Scheduling
December 1, 2013 – Present
● Designed a Software tool to automate the process of course scheduling in IIT Indore using linear optimization. ● The Global course scheduling problem (NP Hard) was separated into several local linear problems by adding constraints. The final model allows for the improvement in the efficiency of the course schedule by optimizing a sequence of local linear problems.
Resistivity Measurement System
April 1, 2013 – Present
● Developed a Software application using an agile approach for controlling scientific instruments and for data acquisition for them, to study the temperature dependency of the resistivity of a material. ● This involves the automation of a physics project in a manner that would help the experimenter to take readings and also set the scientific instruments to desired values via a GUI and observe the real time plotting
Cultural Fit Analysis
The candidate's project portfolio is heavily skewed towards academic and personal projects, with a strong emphasis on computer architecture, machine learning, and algorithm design. While these demonstrate strong technical capabilities, the direct relevance to a typical 'Data Analyst' role, which often involves more business intelligence, reporting, and specific domain analysis, is not explicitly highlighted. The professional experience at Meta and Groupon as a 'Software Engineer, Machine Learning' and 'Software Development Engineer - Machine Learning' indicates a strong fit for ML Engineering or Data Scientist roles, but less direct alignment with a pure Data Analyst role. The breadth of projects and leadership roles suggest a proactive and engaged individual.
Soft Skills & Operational Fit
The candidate's project descriptions and experience show initiative and leadership (e.g., General Secretary, Academic Affairs; Founding President of Quiz Club; Google Student Ambassador). The ability to work on diverse projects, from computer architecture simulations to mobile app development and machine learning, indicates adaptability and a broad technical interest. The descriptions suggest a problem-solving mindset and a focus on improving existing systems.