PhD Candidate in Robotics and Machine Learning

Vishvesh Koranne

********@******.*** ● +1-352-***-****

www.linkedin.com/in/vishveshkoranne

EDUCATION School of Mechanical Engineering, Purdue University Aug 2018 – Jun 2024

■ Masters in Mechanical Engineering focused on Nonlinear Dynamics in Spider Webs CGPA 3.52/4.00

Indian Institute of Technology (IIT) Bombay Jul 2014 – Apr 2018

■ B.Tech with Honors in Mechanical Engineering

■ Completed Minors in Systems and Control Engineering CGPA 8.62/10.0

MASTERS

PROJECT

Analysis of Nonlinear Vibrations in Spider Web Architectures Sep 2018 – Jun 2020 Guide : Prof. James Gibert, ADAMS Research Group, Herricks Laboratory, Purdue University

■ Investigated role of web geometry in high damping in webs and in web shaking behavior exhibited by orb web spiders.

■ Linear modal analysis reveals webs with damage in radial strands or spiral strands (upto 25 %) still retain modal characteristics implying vibrational structural health monitoring could be used to determine functionality of damaged webs.

■ Tuning initial strain, stiffness and point mass at nodes can result in vibrational modes with frequencies in ratios 1:2 and 1:3 for nonlinear interaction. Developed nonlinear model accounted for internal resonances using reduced order analysis. Simulated the nonlinear response in MATLAB using ode45 DATA ANALYSIS Differential Analysis of Gene Expression in Space in ‘The Data Mine’ Jun 2022 – Jun 2023 Guide : Prof. Marshall D. Porterfield, Agricultural and Biological Engineering, Purdue University

■ Longer space missions and space tourism necessitates deeper understanding about the impact of outer space exposure on humans and plants.

■ Differential analysis of gene expression enables the study of mechanisms through which an environment can affect organisms by demonstrating its effects on homeostatis pathways of interest

■ Studied differential gene expression in space from NASA’s GeneLab Data repository. Analysis of the impact on human immune system and thale cress plant photosynthesis in space shows microgravity and radiation exposure in space adversely affects the species. Drug Drug Interaction Prediction using Machine Learning with ‘The Data Mine’ Jun 2023 – Present Guide : Dr. Peter Zhang, Merck & Co.

■ With more than 20,000 drugs approved by FDA in the US, testing adverse reactions to drug interactions with wet tests is expensive. Adverse reactions cost the US $136B annually.

■ Built Ensemble model comprised of graph neural networks (GNN) working on knowledge graph data, Molecular Graph-based networks based on chemical substructure data, and Neural networks utilizing enzyme-target-pathway data to predict these interactions and explain their potential mechanisms.

■ Fine-tuning Large Language Models (LLM) to extract relevant data from literature available in online datasets for feature engineering and classification using PEFT with LoRA PUBLICATIONS

AND

CONFERENCES

■ ”Exploring Properties of Edible Hydrolyzed Collagen for 3D Food Printing of Scaffold for Biomanufacturing Cultivated Meat.” Koranne, V., Jonas, O. L. C., Mitra, H., Bapat, S., Ardekani, A. M., Sealy, M. P., ... Malshe, A. P. (2022). Procedia CIRP, 110, 186-191. https://doi.org/10.1016/j.procir.2022.06.034

■ ”Cellular agriculture : An outlook on smart and resilient food agriculture manufacturing.” Bapat, Salil Koranne, Vishvesh Shakelly, Neha Huang, Aihua Sealy, Michael P. Sutherland, John W. Rajurkar, Kamlakar P. Malshe, Ajay P. In: Smart and Sustainable Manufacturing Systems, Vol. 6, No. 1, 11.01.2022, p. 1-11. https://doi.org/10.1520/SSMS20210020

■ ”Application of fresh beef tumbling to enhance tenderness and proteolysis of cull cow beef loins (M. longissimus lumborum).” Nondorf, Mariah J., Madison Romanyk, Ronald P. Lemenager, Vishvesh Koranne, Ajay Malshe, and Yuan H. Brad Kim. International Journal of Food Science Technology 57, no. 10 (2022): 6621-6632. https://doi.org/10.1111/ijfs.16007 Page 1 of 2

■ ”Nonlineat Vibrations in Web-like String Networks”, Koranne, Vishvesh Gibert James. Poster presented in ASME 2019 Conference on Smart Materials, Adaptive Structures and Intelligent Systems (SMASIS), Louisville, KY

KEY PROJECTS Identification of Soybean diseases based on plant and environment attributes Oct 2022 – Dec 2022 Course Project Guide : Prof. Jing Gao, Purdue University

■ Compared Random Forest, Categorical Naive Bayes, Linear SVM, and Logistical REgression classifiers in python utilizing pandas and numpy libraries for identifying soybean diseases

■ Used UCI Machine Learning Repository: Soybean (Large) Data Set. Cleaned and processed data using with KNN data imputation for missing data for training and validating the classification models

■ 270 instances with 19 attributes were trained to identify the likely disease with 66-34% training test split to get models with 90% accuracy prediction

■ All algorithms worked equally well. Naive Bayes and Logistical Regression Models preferred RELEVANT

TEACHING

EXPERIENCE

TA, ME 539 Introduction to Scientific Machine Learning, Jun 2022 – Aug 2022 Course Instructor : Prof. Ilias Bilinois,School of Mechanical Engineering, Purdue University

■ The course covered the basics of supervised (Bayesian generalized linear regression, logistic regression, Gaussian processes, deep neural networks, convolutional neural networks) and unsupervised learning

(k-means clustering, principal component analysis, Gaussian mixtures)

■ It also reviewed the state-of-the-art in physics-informed deep learning and automated Bayesian inference using probabilistic programming (Markov chain Monte Carlo, sequential Monte Carlo) TA, ME 375 System Dynamics and Modeling, ME, Purdue University Jan 2024 – May 2024

■ The course covers system modeling, analysis, and controller design for Linear Time Invariant Systems.

■ Using LabVIEW and Matlab, controller is designed and verified for electromechanical systems with second order transient response specifications

TECHNICAL

PROFICIENCY

■ Softwares and Languages: MATLAB, ImageJ, SAS, Python, git, R, LATEX Page 2 of 2

Contact this candidate