Sanyam Jain

About Publications Projects Affi. Experience Education Contact

About Me

I am currently a Master's student (2022-24) at Østfold University College and a summer Intern (2023) at OsloMet University, Norway. My research focus belongs to ALife, Evolution, Complexity and Artificial General Intelligence. I enjoy working with Prof Stefano Nichele (also supervisor) where we together study complexity and emergent behaviour in discrete Cellular Automata, continuous CA (Lenia) and Neural CA. Some of my previous work and projects also determine my interest in Deep Learning for Computer Vision and Explainable AI. I finished my Junior Research Fellowship (and did not continue PhD) at Indian Institute of Technology (IIT) Jodhpur (2020-2022) where I studied Deep Learning, Classical ML, and Dependable AI taught by Dr. Mayank Vatsa and Dr. Richa Singh. Conversely, I was also part of VANETs lab supervised by Prof Debasis Das, where my focus was to provide Machine Learning edge for the team. Moreover, I was part of QIC group at the IIT as well. I finished my early Computer Science Engineering (Bachelor's 2015-2019) degree from UPES, Dehradun at the foothills of Himalayas. Most of my guidance during bachelor's for which I am thankful, always to Dr Ravi Tomar. I belong to the central part of India, from a town called Banswara which lies in south Rajasthan.

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Publications / Preprints


Jain, S., Shrestha, A., Nichele, S. (2023). Capturing Emerging Complexity in Lenia. arXiv preprint arXiv:2305.09378.
Authors: Sanyam Jain, Aarati Shreshtha, Stefano Nichele

Jain, S. (2023). Adversarial Attack On Yolov5 For Traffic And Road Sign Detection. arXiv preprint arXiv:2306.06071.
Authors: Sanyam Jain

Jain, S. (2023). DeepSeaNet: Improving Underwater Object Detection using EfficientDet. arXiv preprint arXiv:2306.06075
Authors: Sanyam Jain

Jain, S. (2023). CQural: A Novel CNN based Hybrid Architecture for Quantum Continual Machine Learning. arXiv preprint arXiv:2305.09738.
Authors: Sanyam Jain

Jain, S. (2023). ADDSL: Hand Gesture Detection and Sign Language Recognition on Annotated Danish Sign Language. arXiv preprint arXiv:2305.09736.
Authors: Sanyam Jain

Jain, S. (2023). RAMario: Experimental Approach to Reptile Algorithm--Reinforcement Learning for Mario. arXiv preprint arXiv:2305.09655.
Authors: Sanyam Jain

Integration of wit API with python coded terminal bot. In Emerging Technologies in Data Mining and Information Security: Proceedings of IEMIS 2018, Volume 3 (pp. 397-406). Springer Singapore.
Authors: Jain, S., Sharma, S., & Tomar, R. (2019).

Four-Factor Authentication with Emerging Cybersecurity for Mobile Transactions. In Innovations in Cyber Physical Systems: Select Proceedings of ICICPS 2020 (pp. 391-399). Springer Singapore.
Jain, S., Gautam, R., Sharma, S., Tomar, R., & Choudhury, T. (2021).

Projects

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Frequency Histogram Coarse Graining and MNCA - Sanyam Jain, Stefano Nichele
Studying Complexity and Emerging Behaviour in ECA, Discrete CA and 2D MNCA. Cellular automata and other discrete dynamical systems have long been studied as models of emergent complexity. We argue that being able to capture emergent complexity in AI systems may pave the way to open-ended evolution, a plausible path to reach artificial general intelligence.
MNCA Portal Paper Released!

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EvoLenia Portal - Sanyam Jain, Aarati Shrestha, and Stefano Nichele
Capturing emerging complexity in Lenia using EC fitness based on VoT, AE and AEVoT. This work investigates the emergent complexity in Lenia, an artificial life platform that simulates ecosystems of digital creatures. Le- nia’s ecosystem consists of a continuous cellular automaton where simple artificial organisms can move, grow, and reproduce. Overall, this project aims at investigating the potential of Lenia as ecosystem for emergent complexity in open-ended artificial intelligence systems.
Evo-Lenia Portal Paper

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DeepSeaNet Portal: Using EfficientDet object detection for Denmark's Brackish-Dataset
The results indicate that modified EfficientDet achieved higher accuracy with five-fold cross validation than the other models with 88.54% IoU of feature maps.
DeepSeaNet Portal Paper

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Adversarial Attack On Yolov5 For Traffic And Road Sign Detection
The paper investigates the impact of different types of attacks, including the Limited memory Broyden Fletcher Goldfarb Shanno (L-BFGS), the Fast Gradient Sign Method (FGSM) attack, the Carlini and Wagner (C&W) attack, the Basic Iterative Method (BIM) attack, the Projected Gradient Descent (PGD) attack, One Pixel Attack, and the Universal Adversarial Perturbations attack on the accuracy of YOLOv5 in detecting traffic and road signs.
GitHub Repository Paper

Affiliations and Media Reach

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Conference Reports!

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Keynotes and Talks Summary: NORA AI Annual Conference 2023, Tromsø, Norway

Published on June 12, 2023 (Funding by HiØ)


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NEURO AI Workshop, Tromsø, June 4, 2023

Published on June 10, 2023 (Funding by HiØ)


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NORA-AI Meet 2022, Short Summary of Day 1 Keynote

Published on November 16, 2022 (Funding by HiØ)

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WIVACE 2023, 17th Workshop on ALife and Evolutionary Computation, Ca'Foscari, Venice, Italy with ECLT.

Published on September 11, 2023 (Funding by HiØ)

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ICAPAI 2024, Halden AI Week, Conference

Published on May 7, 2024 (Funding by HiØ)

Academic and Professional Experience

Here, you can find information about my professional experience.

Research Asst. Summer Internship - OsloMet
July 2023 - current
Continuing research with Stefano Nichele
Research Asst. - Part Time - Østfold University College
September 2022 - June 2023
- Studying and Analyzing Complexity in Discrete Cellular Automata (1D and 2D) using Evolutionary Algorithm
- Capturing Emerging Complexity in Lenia
Teaching Assistant, Machine Learning - Winter 2022 - IIT Jodhpur
January 2022 - May 2022
Course Instructor: Dr. Richa Singh, IIT Jodhpur Skills: Machine Learning
Teaching Assistant, Foundations of Quantum Information and Computation - Trimester 3 - IIT Jodhpur
August 2021 - December 2021
Course Instructors: Dr. Subhashish Banerjee, IIT Jodhpur Dr. Atul Kumar, IIT Jodhpur Dr. V. Narayan, IIT Jodhpur
Research Asst. - Full Time - IIT Jodhpur
September 2020 - June 2022
- Course work Machine Learning (by Dr. Gaurav Harit), Deep Learning (by Dr. Mayank Vatsa), Dependable AI (by Dr. Richa Singh), Cryptography (by Dr. Somitra Sanadhya)
- Part of VANETs Lab supervised by Dr. Debasis Das.
Amazon Alexa Specialist - Conversational AI - KeyringCorp
2019 - 2020
Proudly, an AWS Activate startup founders portfolio for 10 years. Building Great Experiences for Kids using Voice-Driven AI, VUI, and Alexa skills. Conversational AI, Voice User Experience, Interactive Alexa skills, 100k+ customers worldwide, Helping businesses and institutions to design and develop their custom Alexa Skills and Google Actions.
RPA UiPath Consultant
2019 - 2020
RPA UiPath Advanced Certified, Level 1,2 and 3, UiRPA, UiARD 1. RPA UiPath Learning Plan and Package 2. RPA UiPath Advanced Certification guidance 3. Helping Startups to setup RPA Automation in their daily working flow. 4. Helping Professional with hands on experience to UiPath RPA Studio.
Software Eng Intern - YellowAnt Inc
May 2018 - July 2018
Built CRM platforms using Django and REST APIs. OAuth for Sugar CRM, Zoho CRM and FreshSales.
Remote Intern - IBM Watson
May 2018 - July 2018
Studying Watson API.

Education

Østfold University College, Norway

Degree: Masters in Science

Major: Applied Computer Science

Year: 2022-2024

Currently maintaining 4.4/5 - Stduying Machine Learning specialisation with CPS. Projects for the courses adv. ML and Applied CS project includes "DeepSeaNet" and "Complexity in Lenia" which can be found in publications section as part of preprint.

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Indian Institute of Technology, Jodhpur

Degree: PhD (Dropped)

Major: Quantum Information and Computation with focused coursework on Deep Learning

Year: 2020 - 2022

Grade: 7.8/10, Activities and societies: Part of VANETS LABActivities and societies: Part of VANETS LAB, Courses: Machine Learning, Dr G. Harit AI 1, Dr D. Mishra Graph Theory and Applications, Dr A. Mishra Deep Learning, Dr M. Vatsa Dependable AI, Dr R. Singh (A- grade) Financial Engg., Dr V. Vijay (A- grade) Cryptography, Dr S. Sanadhya ML for Economics, Dr D. Brahma Adv Machine Learning, Dr M. Vatsa (A grade) Cryptography, Course Project Theoretical analysis of QKD protocol BB84 and experimenting related algorithms on qiskit, (Endsem) QKD protocols and Quantum attacks on blockchain. (Attacks on Bitcoin PoW and Attacks on Digital Signatures) ML2, Endsem Project - Analyzing and Improving the Image Quality of StyleGAN (StyleGAN2) CVPR 2020, HELEN EYE DATASET and Clothing Dataset (Fashion Dataset) ML2, Group Project - Random Multimodel Deep Learning for Classification (arXiv:1805.01890) 20NewsGroup and IMDB dataset & CIFAR-10, MNIST Dataset. Dependable AI - Study of Nature of Different Adversarial Attacks and Impact of Different Data Augmentation Techniques on Robustness.

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UPES, Dehradun, India

Degree: BTech (Bachelor's in Technology)

Major: Computer Science Engineering

Year: 2015 - 2019

Grade: 77.50, Best Project award for Compariso - whatsapp bot to compare e-commerce prices. Top 10 in R.I.S.E. UPES under supervision of Dr. Ravi Tomar sir with project title: KidExa (Team KeyringCorp) Won Best project Award in Project Parliament (2018) college Minor Project 2 for Facial Recognition significance in cybersecurity. (Team KeyringCorp) Won Third Prize for Real-time Traffic Analysis – IBM ICE on campus Hackathon. (Team KeyringCorp) Won Second prize for 4FactorAuthentication in North India Cyber Security Hackathon at WIC Dehradun. (Team KeyringCorp) Developed Python Chatbot using wit NLP engine. (Wit.ai) Developed Automated Key logger using C. (Unix/Py) Studied Digital Logic, Data Structures and Algorithms, Java, Operating Systems, DBMS, Computer Networks, Theory of Computation, Discrete Maths, Information Retrieval and Search engines, Artificial Intelligence, Mobile Applications.

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Contact Me

You can reach me via email at sanyamjaincs@gmail.com. Connect with me on social media through the following profiles:

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