Hrishikesh Kulkarni here!

I am interested in solving pressing problems using interesting techniques and like to implement ideas and built products around them...
I am keen to learn and research in the areas of Machine Learning, Cognitive Computing, NLP and Information Retrieval...


Impact on human behavior with exposure to different cultures and presenting it in association and closeness using graphical methods

Oct 2018 to Mar 2019

In this project, we have captured human expressions through questions and responses in pictorial form. The personality is mapped to responses. This work is further developed to associate relationships between clusters and depression. We have proposed a graphical association method for clustering candidates and mapping them to cultures. In graphical association method (GAM) each candidate is represented as a graph with core node and multiple nodes associated with the core node. Core node is the node associated with maximum number of nodes and it changes as more information about candidate is made available. Reinforcement Machine learning is used in this case. Thus, multiple graphs are associated based on closeness among graphs. This closeness is calculated using distance between corresponding nodes. The clustered graphs are represented using a representative graph and mapped to culture cluster. This mapping is used for task selection and recommendation. In this particular application dynamic scenarios are handled using special event related data.

Mentor/Supervisor: Dr. Bradly Alicea

Kansei Engineering - Embedding emotions into products, News, and Advertisements in order to respond emotions of customers

Oct 2017 to Dec 2017

Embedding emotions into product is very interesting and equally challenging concept. Emotions can be embedded in the form of color, text inscription, sound and even pictures. The first and most important part of this project is to determine emotional traits of individuals. This is determined using analysis of expressions, responses and social media posts. Based on emotional traits the candidates are clustered and a set of emotions are determined. In some cases, those are context specific. Thus, emotional traits and context is used to identify the emotional requirements. For any product based on emotional traits basic theme is determined while context helps us to determine sub theme. Here Affinity is determined using mathematical models based on closeness factor. Closeness between two or more emotions is determined using combination of Manhattan and Euclidean distance. In static model basic emotional trait based features are used. The context-based features can be dynamically included in the product. The work is in the area of Computational Psychology and Computational Behavior. The association between products and emotions is used for recommending products and context specific emotions are embedded in products.

Mentor/Supervisor: Dr. P. Chande, Dr. P. Joshi

VicharDhara - A Thought Mapper

Jun 2017 to Aug 2017

Idea "VicharDhara" Selected in top five for Accenture Innovation Challenge - 2017 among 7000 entries across the country. Specially appreciated as one of the most innovative projects by juries.

Thinking and thought process measurement is very subjective. Can we find out and rank thought process of students, faculties or researchers? In case we could do this it can revolutionize the education system. It can change the way we measure and rank performances. Measuring and Ranking thought process remains a challenge. We teach Physics, we teach Math but we always fail to teach thinking. There are psychometric tests to evaluate thinking. But these tests are very subjective. Thoughts have associations with actions. Capturing this thought process is what we are trying to achieve using this innovation.

Mentor/Supervisor: Dr. N. Rajopadhye

Multi-Agent System for Customer Behavior Tracking Using Shoppers' Path or Traversal

Jan 2018 to Mar 2018

The path followed by consumer is depictive of his behavioral pattern, his likings and needs. Overall path tells us about his buying pattern and can help us to learn about articles he/she is planning to buy. Associations among these traversal paths could help us to predict traversal path of similar customers. This can allow us to suggest personalized paths for customers and also to rearrange articles dynamically based on majority of customers expected on a particular day. This is based on algorithm for associating traversal paths and consumer psychology to predict behavior of customers. The traversal path is represented as a graph. The major nodes are the products of significance where buyer spend time more than 1 minute. This traversal path decides association among objects mapped to the buying patterns of individuals. In this project we clustered a number of such traversal paths and associated it with customer representative data. This information is used to determine traversal path of the same customer or similar customer during their visits.

Mentor/Supervisor: Prof. (Dr.) P. Patil, Prof. (Dr.) R. Mennon

Right task allocation and team selection

Apr 2018 to Jun 2018

It is the context of task, behaviors of individuals and above all constitution of the team in that scenario contribute to the outcome. The proposed technique is based on convergence of multiple context vectors representing computational behaviors. Learning based on these vectors helps us to select the optimal combination. The Context Vector Convergence (CVC) of Behavioral Vectors helps in deriving the actual effect of two vectors in overall team performance. The personality vector is used to derive behavioral context while mission vector is used to derive the scenario context. Thus, team is selected so that negative emotional impact on team members is minimized. The algorithm of context vector convergence is proposed in this work.

Mentor/Supervisor: Prof. M. Marathe

Personalized Newspaper Based on Emotional Traits Using Machine Learning

In progress since May 2019

News unknowingly creates desired or undesired psychological impact. Right from title, presentation and sequencing to filtering and personalization - machine learning, and cognitive sciences can play a key role in news computing and processing. This project looks into research carried out in the area of cultural and news computing in elaborate way and proposes a model for personalized sequencing and presentation of news. This personalized newspaper aims to present newspaper of your liking and suitable to your emotional makeup so that the overall desired impact will be achieved. Further it helps in countering depression that may result due to negative news. In this project personal data of reader captured through our technique of responses to pictures is used to determine his/her cultural and emotional traits. The news articles are ranked with reference to user and even collated to derive desired impact. So far we have worked on expression analysis and news mapping.

Mentor/Supervisor: Prof. M. Marathe


Contextual Recall for patient suffering from Alzheimer

Jul 2018 to Sep 2018

Back end to classify patients based on properties and mapping the patients to sequence of events. Special help module for emergency. - Android, Java, python Features: Alerts, Reminders based on situation, Context based event trigger

Mentor/Supervisor: Prof. A. Bhadgale

An Artificial Intelligence Based Optimal Transfer Solution Using Constraint Vector resolution and Suitability Index - Smart India Hackathon 2018

Problem: Transfer of Employees
Solution: Transfer based on skills, suitability and context. Automated transfer module.
Learning based on human inputs,
Algorithms: Statistical machine learning and parametric association

Mentor/Supervisor: Prof. M. Marathe


Patents filed/pending

Based on the concept of Vichardhara, a provisional patent is filed in Aug 2017.
Filed an Indian patent on July 2018 E-2/1489/2018/MUM and PCT in July 2018.
PCT/IN2018/050502 Link


Papers published in Peer Reviewed Journals

  1. Hrishikesh Kulkarni, Prachi Joshi, PK Chande, "Computational Psychology to Embed Emotions into Advertisements to Develop Emotional Bonding", 2019, Indian Journal of Psychological Science, NAPS, (Accepted) Link
  2. Hrishikesh Kulkarni, Manisha Marathe, "Context Vector Convergence (CVC) of Computational Behavior and Cultural Traits for Team Selection", Int. J. of Information and Decision Sciences (IJIDS) (Accepted) (Scoupus Indexed) Link

Papers published in Peer Reviewed Conferences

  1. Hrishikesh Kulkarni, "Contextual Data Representation Using Prime Number Route Mapping Method and Ontology" IEEE Conference, ICCUBEA, June 2017 - Received Best Paper Award Link
  2. Hrishikesh Kulkarni, "Intelligent Context Based Prediction using Probabilistic Intent-Action Ontology and Tone Matching Algorithm", IEEE Conference, ICACCI, Manipal, Oct 2017 Scopus Indexed Link
  3. Hrishikesh Kulkarni, "Intent Action Ontology and Tone Matching Algorithm for Organizing News Articles", IEEE Conference, ICECDS, Chennai, July 2017 Link
  4. Hrishikesh Kulkarni, "Thought Process based Team Member Selection Using Contextual Sentiment Closeness", IEEE Conference (Bombay Chapter), International Conference on Convergence of Technology, I2CT Pune, April 2018 Link
  5. Hrishikesh Kulkarni, "Multi-Graph based Intent Hierarchy Generation to Determine Action Sequence", Springer Conference, ICDECT, December 2017, Pune Link
  6. Hrishikesh Kulkarni, Prachi Joshi, Pradip Chande, "Computational Psychology to Embed Emotions into News or Advertisements to Increase Reader Affinity", 5th International Psychological Congress, Chandigarh, INDIA, 2018 (NAPS) Link
  7. Hrishikesh Kulkarni, Bradly Alicea, "Cultural Affinity through Associative Machine Learning and Behavioral Computation" 5th International Psychological Congress, Chandigarh, INDIA, 2018 (NAPS) Link
  8. Hrishikesh Kulkarni, Prachi Joshi, Pradip Chande, "Computational Psychology to Embed Emotions into Product to Increase Customer Affinity" Springer Conference ICICCT, Hyderabad, 2019 Scopus Indexed Link
  9. Hrishikesh Kulkarni, P Patil, R Menon, "Multi-Agent System for Customer Behavior Tracking Using Shoppers' Path Traversal", CS8009, Third IEEE International Conference on Electrical, Computer and Communication Technologies (IEEE ICECCT 2019) (Scopus Indexed) Link
  10. Hrishikesh Kulkarni, Manisha Marathe, "Machine Learning Based Cultural Suitability Index (CSI) for Right Task Allocation" CT1055, Third IEEE International Conference on Electrical, Computer and Communication Technologies (IEEE ICECCT 2019) (Scopus Indexed) Link
  11. Hrishikesh Kulkarni, Bradly Alicea, ”Cultural Association Based on Machine Learning for Team Formation.”, IEEE Conference, ICCUBEA, Sept 2019 (Accepted) Link
  12. Hrishikesh Kulkarni, Tejas Joshi, Nikhil Sanap, Rohan Kalyanpur, Manisha Marathe, "Personalized Newspaper Based on Emotional Traits Using Machine Learning.", IEEE Conference, ICCUBEA, Sept 2019 (Accepted) Link

  13. ICCUBEA 2017


    Hrishikesh Kulkarni, "Contextual Data Representation Using Prime Number Route Mapping Method and Ontology" IEEE Conference, ICCUBEA, June 2017


National Insurance Academy (NIA)

Jun 2019 to Aug 2019

Three Month Research and Development internship

Worked on Context based personalized analysis of individuals to decide premiums and claims. Further worked on developing an intelligent algorithm and culture based analysis so that the agriculture and health care insurance benefits could reach to Bottom of Pyramid. The core part of this project is to mine farmers' intent. In intent mining farmer association, farmer context and expression are used. We have used periodic responses from farmers along with contextual data to mine their intents. Thus, farmers are mapped to the most suitable schemes.

Mentor/Supervisor: Prof. (Dr.) S. D. Page

GSOC 2018 @ GCC

May 2018 to Aug 2018

Only candidate selected by GCC for GSOC in 2018

The LTO object file is a regular elf file with sections containing LTO byte-code. A LTO object file contains various sections for storing command line options, symbol table, global declarations and types, function bodies in GIMPLE, ipa pass summaries, ipa references, static variable initializers and the call graph. There are couple of limitations of the byte code format: 1] It is not self descriptive, which makes it harder to debug. 2] The byte code is essentially a "serialized" version of in-memory representations, which makes it prone to break across versions.
The purpose of this project is to create a dump tool for easily analyzing LTO object files similar to readelf or objdump -d for regular ELF object files. Link Code

Mentor/Supervisor: Martin Liska, Jan Hubicka

iKnowlation Research Labs Pvt. Ltd.

Jul 2017 to Dec 2017

Six Month Research internship

During this internship I got opportunity to play with data. During this internship I used different existing clustering techniques to cluster behaviors. We used different statistical methods. I could take part in proposing a new algorithm for intent mining. In this internship data of different teams and performance of individuals and teams is used. The data is analyzed considering different attributes. I have used different keyword and key-phrased based associations. At later stage we build a node association map. This map could yield better results than traditional approaches. Apart from this core work I also got opportunity to work on different aspects thought process mapping.

Mentor/Supervisor: Dr. P. Chande, Dr. P. Joshi

Hosting Duty (subsidiary of Kaizen Infosys Pvt. Ltd.)

May 2017 to Jul 2017

Summer Internship for two months

Hosting duty is working on developing and hosting websites along with mining website data. During this internship I got opportunity to make my hand dirty with actual website development work and basic web mining activities. For web mining I used all off the shelf algorithms like TFIDF. I used cosine similarity to associate data. The aim of this work was to detect exceptions and anomalies in information. We used signature-based approach for the same.

Mentor/Supervisor: Nenadd Chandorkar


Activities and Accolades

  1. Best Paper Award at IEEE conference ICCUBEA ( for paper Titled "Contextual Data Representation Using Prime Number Route Mapping Method and Ontology" 2017
  2. Only candidate selected by GCC for GSOC 2018
  3. Idea "VicharDhara" Selected in top five for Accenture Innovation Challenge - 2017 among 7000 entries across the country. Specially appreciated as one of the most innovative projects by juries.
  4. Finalist at Smart India Hackathon 2018 Chennai
  5. PVG Merit Award - First admission award - 2016 (2 in 500 students got it)
  6. Only student representative for IQAC (Internal Quality Assurance Cell) PVGCOET 2018-2020
  7. Founded Open Source Club at PVGCOET Pune
  8. Won second award (Runner-up) Cyber Genius Quiz
  9. Stood Sixth in High School Scholarship (Among 30000 students) 2011
  10. Cleared two Tabla examinations (2008, 2009) – Bharat Gayan Samaj
  11. IEEE student member since 2017
  12. Life member of National Association of Psychological Sciences since 2018
  13. Member of ToastMaster's club of Pune since 2017
  14. Member of Technical Team ACES 2017-2018
  15. School Basketball team captain
  16. Completed many Swimathons


Hrishikesh Kulkarni

Striving to solve social problems using Research and Technology. If you would like to discuss on Cognitive Computing over a cup of coffee, feel free to drop me a mail at