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Assistant Engineer

New York City, NY
March 09, 2020

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Alfred Ajay Aureate R

New York City, NY


Linkedin (alfredaureate) Github (orgate)


Courant Institute of Mathematical Sciences, New York University (NYU), New York, USA Sep 2018 – May 2020 MS in Mathematics (4th or final semester)

Relevant Courses: Time series analysis & statistical arbitrage, machine learning, analysis, multivariable analysis, scientific computing, stochastic calculus, methods of applied mathematics and deep learning (current) Indian Institute of Technology Madras (IIT Madras), Chennai, India Aug 2010 – Jul 2015 Dual Degree (Bachelor of Technology in Electrical Engineering & Master of Technology in Microelectronics and VLSI Design) Relevant Courses: Probability, statistics, theory and applications of stochastic process, data structures & algorithms, networks & systems, analog & digital signal processing, computer modelling & simulation and mathematical modeling in industry WORK EXPERIENCE

Graduate Research Assistant / Teaching Assistant / Tutor at NYU Courant, New York, USA Sep 2018 – Current

• Taught and graded Calculus - I course for about 30 undergraduate students over a semester and Math for Economics - II course for about 210 undergraduate students from different majors over the span of 3 semesters. Tutored for 3 undergrad courses.

• Studied the statistical leakage in the AES-GCM encryption of time series and explored ways to exploit it without using a key. Applications Development Engineer at KLA Tencor Software India Pvt. Ltd., Chennai, India Mar 2018 – Aug 2018

• Trained to review a semiconductor wafer (bare/patterned) and optimize imaging conditions to identify defects at nanoscale when viewed through a Scanning Electron Microscope, with more than 95% accuracy, 98% sharpness and throughput above threshold Research project assistant at The Institute of Mathematical Sciences, Chennai, India Dec 2016 – Mar 2018

• Analyzed power-law distributions of congestion times from a yearlong data of GPS traces of 3300 taxis in 3 Indian metropolises

• Characterized those heavy-tailed distributions by simulating the urban traffic using different novel & simple car-following models Business Analyst at Flipkart India Private Ltd., Bangalore, India July 2015 - Dec 2016

• Facilitated in launching about 40 products on Inventory model and about 1400 products from 6 different categories on Market Place, by enhancing the logistic capability of the in-house Supply Chain at all checkpoints for those products

• Designed, collaborated and documented standard procedures for various processes that advanced the end-to-end Supply Chain capacity and robustness. Analyzed millions of data points for optimization/rectification of different stages of the distribution PROJECT THEMES & INTERNSHIPS


• Alfred Ajay Aureate R. and Vaibhav Madhok, “Typicality in quasispecies evolution in high dimensions”

Accepted & published in a peer-reviewed journal: Phys. Rev. E arXiv preprint available here:

• Mohith D., Inavamsi B. E. and Alfred Ajay Aureate R.,

“Numerical Sequence Prediction using Bayesian Concept Learning” arXiv preprint available here: Accepted at Intellisys 2020 conference, Amsterdam, Netherlands

• Alfred Ajay Aureate R., Sitabhra Sinha and Subinay Dasgupta, “Dynamics of urban traffic congestion”

(To be submitted to Phys. Rev. Lett.)

Time series modelling and forecasting using RNNs and other statistical techniques June 2019 – Current

Modeled experimentally observed temporal shift in sequential activations of neurons by modifying dynamics on trained RNNs

Proposed a trading strategy based on correlation of returns over different days of the week observed across 300 stocks in 10 yrs.

Back tested using Quantopian API and forecasted using GARCH models about 224.84% increase in returns, without trade costs

Forecasted NYSE stocks’ returns using ARIMA, Neural Networks and LSTM based models and compared accuracies (GitHub). Numerical Sequence Prediction using Bayesian Concept Learning (NYU Course project) Feb 2019 – May 2019

Proposed a concept learning model using Bayesian method to predict subsequent terms in an uncorrupted/corrupted sequence

Matched results with 95.4% closeness to human data, while the deep learning - based LSTM model came only about 51.7% close Modeling of several Engineering phenomena (at IITM, India) Aug 2014 - May 2015

Modeled traffic flow, infectious disease, electronic circuits and filtered images using linear and non-linear drift-diffusion models

Simulated electron wavefunction in quantum wires in Python using variable separation technique, finite-difference method and LOBPCG method – that uses smoothed aggregation based multi-grid solver and the help of some preconditioners Summer Intern at Ittiam Systems Pvt. Ltd., Bangalore, India May 2013 - July 2013

Demonstrated 112% improvement in the recognition accuracy of an Automatic Speech Recognizer using beam-formed signals

Implemented CMU Sphinx - Java-based ASR for beamformed signals and showed improved performance even with noise at phone, word & sentence levels. Used Hidden Markov Models (HMM) - based inbuilt language & acoustic models, for the same Winter Intern at Dhvani Research (wireless tech.), Chennai, India Dec 2012 - Jan 2013

Simulated ultrasonic wave intersection on pipes of different shapes and materials using Visual C++ for non-destructible testing

Developed a Graphical User Interface (GUI) for the simulation with controllable geometric and physical parameters TECHNICAL SKILLS

Languages: C, C++, Java, Python (NumPy, SciPy, Pandas, Sklearn, PyTorch, TensorFlow & Keras), SQL (MySQL), MATLAB & R OS: MacOS, Linux (Ubuntu and Debian) & Windows

Online Courses: Microeconomics (edX - MIT) and Data analysis for Social Scientists (edX - MIT)

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