CV (Download)

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Currently : PhD Student

  • PhD Scholar in Joint Program at CIS, EECS, Queen Mary University of London, UK & Elios Lab, DITEN, University of Genova, Italy.

Wheelhouse : Machine Learning & Signal Processing

  • Second Place winner team – Urban Analytics Data Dive: Second place winner team for Urban Analytics Data Dive held at The Alan Turing Institute and hosted in collaboration with the Office of National Statistics -ONS Data Science Campus. 25-26 July 2017.
  • Second Place winner team – Person Identification from Audiovisual challenge in summer school 2017 held at Centre of Intelligent Sensing, Queen Mary University of London. 7-9 Sep 2017.
  • Data Study Group: A week-long event, worked with team for Urban Analytics posed by Defense Science and Technology Laboratory (DSTL) at The Alan Turing Institute, London. 22-26 May 2017. Blog about it can be seen here.
  • Online Competitions: I worked on Kaggle’s competitions of Machine Learning and Data Science, Profile is here https://www.kaggle.com/nikeshbajaj/competitions
  • Courses: I have done several courses online/offline in field of machine learning and signal processing– Courses are listed below
  • Training: I attended Faculty Development Program on Data Analytics by Cognizant Technology Solution, India
  • Tools and Languages: Python (Anaconda:-IPython-Notebook, matplotlib, numpy, scipy, pandas, Scikit-learn, Scikit-Image,TensorFlow), R, Matlab,Chuck, Java, C# – GithubRepo
  • Coursera Mentor : Currently mentor for coursera course –Audio Signal Processing for Music Applications

Experience:

  • July 2010 – Nov 2015 :  Worked as Asst. Professor for School of Electronics and Communication at Lovely Professional University (India) from July 2010 till Nov 2015
  • Oct 2006 – July 2008  :  Worked at Collwell & Salmon Communication, Noida (India) from Oct 2006 till July 2008
  • 2005 – 2006 : Worked in variouse BPOs
  • 2002 – 2005 : Worked in as Data Entry Operator in Courier Company and Worked in NGO from

   Teaching Assistant of Queen Mary University of London:

  • Digital Signal processing -2017/18
  • Coding for Scientist – 2017/18
  • Data Analytics – 2017/18
  • Signals and Systems Theory -2017/18
  • Security Engineering -2017/18

Education:

  • Masters in Technology (M.Tech) in Communication & Information Systems from Aligarh Muslim University
  • Bachelors in Technology in Electronics and Telecommunication Engineering from IETE – Institutions of Electronics and Telecommunications Engineering, New Delhi (India).

Awards & Honors:

  • Best Faculty Award 2014-2015 – Received Best Faculty award for outstanding performance by Cognizant Technology Solution
  • Best Faculty Facilitator Award 2015  – for being facilitator for ‘Uttara-Scientia Divina’ -Student Organization at LPU
  • Best Student Award at Sunrays Children High School, Itarsi, M.P. (India), 1999
  • Second Prize in ‘Hindi Gyan Pariksha’ by Akshar karmi Swayam Seva Santha on Hindi Diwas, 1997

Member

  • Associate Member of Institute of Electronics and Telecommunication Engineering – IETE, New Delhi (India)

Participations

  • Indian Robot Olympiad IRO- 2012 as coach for team Cryptons

Courses Taken Online/Offline:

Machine Learning

# Course Instructor Institutions
1 Machine Learning Andrew Ng Stanford University/Coursera
2 Neural Network for Machine Learning Geoffrey Hinton University of Toronto/Coursera
3 Probabilistic Graphical Model Daphne Koller Stanford University/Coursera
4 Statistical Learning Trevor Hastie, Rob Tibshirani Stanford University/Stanford Online
5 Machine Learning for Musicians and Artists Rebecca Fiebrink Goldsmiths University of London/Kadenze
6 Regularization Methods for Machine Learning Lorenzo Rosasco University of Genova & MIT
7 Machine Learning : A Computational Intelligent Approach Francesco Masulli University of Genova
8 Data Fusion and Bayesian Network Carlo Regazzoni University of Genova
11 Kaggle R Tutorial on Machine Learning Self-taught course DataCamp
9 Neural Network and Deep Learning Andrew Ng deeplearning.ai/Coursera
10 Improving Deep Neural Networks: Tuning Hyper parameters Andrew Ng deeplearning.ai/Coursera
11 Structuring Machine Learning Projects Andrew Ng deeplearning.ai/Coursera
.

Signal Processing

# Course Instructor Institutions
1 Image and video processing: From Mars to Hollywood with a stop at the hospital Guillermo Sapiro Duke University/Coursera
2 Introduction to Digital Sound Design Steve Everett University of Toronto/Coursera
3 Digital Signal Processing Paolo Prandoni École polytechnique fédérale de ausanne Switzerland/Coursera
4 Computational photography Irfan Essa Georgia Institute of Technology/Coursera
5 Computer Vision Jitendra Malik University of California, Berkeley/Coursera
6 Audio Signal Processing for Music Applications Xavier Serra Stanford University & UPF/Coursera
.

Fundamental courses and other courses for Fun

# Course Instructor Institutions
1 Cryptography -I Dan Boneh  Stanford University/Coursera
2 Applied Cryptography, Science of Secretes Dave Evans Udacity
3 Control of Mobile Roborts Magnus Egerstedt Georgia Institute of Technology/Coursera
4 An Introduction to Interactive Programming in Python Joe Warren, John Greiner, Scott Rixner Rice University/Coursera
5 Learn To Program: Fundamental Jennifer Campbell, Paul Gries University of Toronto/Coursera
6 The Data Scientist’s Toolbox Jeff Leek, Roger D. Peng,  Brian Caffo Johns Hopkins University/Coursera
7 Algorithms: Design and Analysis,Part 1 Tim Roughgarden Stanford University/Coursera
8 Engineering Self-Reflection for Human Completion Duck-Joo Lee Korea Advanced Institute of Science and Technology/Coursera
9 The Nature of Code Daniel Shiffman Processing Foundation/Kadenze
10 Introduction to Programming for the Visual Arts Chandler McWilliams, Casey Reas, and Lauren McCarthy University of California, Los Angeles, Department of Arts/Kadenze
11 Java Tutorial for Complete Beginners John Purcell Udemy
.

 

CV (Download)

 

 

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