Actively looking for internships and research projects

1.
Kshitij Patil Senior Undergraduate,
Dept. of Computer Engineering,
Pune Institute of Computer Technology
kshitijpatil98@gmail.com
+919423706080
www.linkedin.com/in/kshitijpatil98
www.github.com/Kshitij09
EDUCATION
B.E. Computer Engineering
Pune Institute of Computer Technology
Aug 2017- Present
CGPA: 8.3
Diploma in Information Technology
Government Polytechnic, Kolhapur
Aug 2014 - May 2017
Percentage: 90.88%
EXPERIENCE
Periwinkle Technologies, ​Pune - ​Project
Intern (Medical Imaging)
Sept 2019 - present
- Working on Cervical Cancer Screening VIA
using Deep Learning based Multimodal
classification techniques to develop a visual
evaluation algorithm that accurately recognizes
Cervical Precancer/Cancer.
PICT ACM Student Chapter, ​Pune ​—
Technical core committee member &
Domain Director of Android
Sep 2018 - Sept 2019
- Guiding fellow PASC members by conducting
seminars and mentoring projects. Keeping them
abreast of recent trends in software
development.
CoReCo technologies, ​Pune — ​Intern
May 2016 - June 2016
- ​Explored Docker technology with the
deliberate study of containerization. Ascertained
how the effective usage of Docker containers
could reinforce application deployment.
PROJECTS
CNN based Forest Fire Detection
(Nov 2019 - present)
- Working on a CNN based Forest Fire Detection
algorithm intended to be deployed on camera enabled
edge devices. Dataset is created by extracting frames
from YouTube videos and under refinement. Initial
results have shown MobileNetv2 as the ideal model
(2MB -86% accuracy) for deployment. ​[​source code​]
- ​Technologies Used: Tensorflow, Keras, Pytorch, fastai, opencv
OCR for Handwritten Forms ​(June 2019)
- Developed a system to extract Account No. and Date
from Bank Payment Receipt using OpenCV and correctly
recognizing the digits using CNN based algorithm. The
model was trained over EMNIST dataset and various
preprocessing steps were applied to make the digits
discernable.
- ​Technologies Used: OpenCV, Tensorflow, Keras
Image restoration without clean data​ ​(Mar 2019)
- Conducted a survey on image restoration techniques
capable of restoring images by only looking at
corrupted examples. An algorithm from 'Noise2Noise'
(Jakko et.al.) research paper implemented using
convolutional auto-encoders with symmetric skip
connections was giving SOTA results. ​[​report​]
- ​Technologies Used: LaTeX, Tensorflow, Keras
Crowd Counting for disaster management
(Aug 2018 - Sep 2018)
- Developed a system based on the novel deep learning
architecture - CSRNet (Y.Li et.al. CVPR '18) to output a
crowd density map corresponding to an input image,
and hence deduce the count from the density map.
- ​The model was then deployed on an Android platform
using quantized version of model (TFLite).
- ​Technologies Used: Tensorflow, Keras, Android, Firebase

2. SKILLS
Deep Learning: Computer Vision, thorough
understanding of standard deep learning
architectures.
Deep Learning frameworks: ​tensorflow, keras,
pytorch, fastai
Machine Learning: ​Supervised and unsupervised
algorithms on text data using python libraries
Programming: ​Java, Kotlin, Python, C++, Swift
Front end development: ​HTML, CSS, Javascript
Backend development: ​Angular, Spring-boot,
Flask
Database: ​MongoDB, Mysql, Hibernate(basic)
Miscellaneous: ​Android, Firebase, Docker
- Able to deploy machine learning models on
Android, web and edge devices using tensorflow
ecosystem..
- Design and deploy Microservices using Docker
and Kubernetes
RELEVANT COURSES AND CERTIFICATIONS
Linear Algebra - ​MIT OpenCourseWare
Course Number: 18.06
CS20 -​Tensorflow for Deep Learning
Research
Stanford University
Machine Learning - Stanford
University
Coursera
Grade achieved: 95.7%
Convolutional Neural Networks -
deeplearning.ai
Coursera
Grade achieved: 98.4%
Google Cloud Training​ -
Qwiklabs
1. GCP Essentials
2. Baseline: Data, ML, AI
3. OK Google: Build Interactive Apps with
Google Assistant
RELEVANT COURSES AND CERTIFICATIONS
CS231 - Stanford University
Assignment solutions - [​source​]
Practical Deep Learning for Coders​: part-1
Fast.ai
ACHIEVEMENTS
Winner: MindSpark Hackathon 3.0:
College of Engineering, Pune
- Part of 4 member team who stood first amongst
52 participant teams at Mindspark Hackathon, the
biggest technical event in Pune.
Winner: Software Development - Credenz’18:
PICT IEEE Student Branch, Pune
- ​Winner of senior category in software
development at Credenz, organized by PICT IEEE
Student Branch(R10) for the headcount
monitoring system.
Software Development - Credenz’17:
PICT IEEE Student Branch, Pune
- ​Winner of junior category in software
development at Credenz, organized by PICT IEEE
Student Branch(R10) for the project ‘FrameIT’.
CodeTrix - Avishkar 2016:
Government College of Engineering, Karad
- Winner of coding competition organized by
Government College of Engineering, Karad.
Best Outgoing Student: (2017 batch)
Government Polytechnic, Kolhapur
- Recognised as ​‘Best Outgoing Student’​ of IT
Department from Government Polytechnic,
Kolhapur
EXTRA CURRICULAR ACTIVITIES
Speaker at Punecommunity.AnitaB.org
- Delivered a session on ​‘Exploring the World of
Android Apps’​.