Divyansh Chhabria

GitHub Repository

Course Project: Software Development and Operations (Jan'23 - April'23)

• Collaborated in a 10-member team and developed a software for digitalizing mess, canteen operations, bookings, and housekeeping services in the halls of residence at IIT Kanpur, enhancing transparency and minimizing paperwork


• Developed the software project using the waterfall model, divided the project into distinct stages, such as requirements gathering, design, implementation, testing, and maintenance, with each stage building on the previous one ensuring that each stage was completed thoroughly before moving onto the next one, with focus on proper documentation.


• Utilized Figma to design the frontend and Django Framework of Python to develop the backend functionality, while also performing unit-testing using the Django-Test Framework and integration-testing using Selenium, to ensure quality and reliability of the software.


• Managed the project timeline, conducted regular team meetings to discuss over project progress, risks & opportunities, delegated tasks, ensured that all team members were on track to meet project goals, and successfully delivered the project on time.

GitHub Repository

Course Project: Introduction to Machine Learning (Jan'23 - Feb'23)

• Designed and implemented a machine learning model capable of cracking an Advanced XOR Ring Oscillator (XORRO) Physically Unclonable Function (PUF) with 16 XORROs, each comprising 64 XOR gates, by accurately predicting the XORRO with a higher frequency in any given pair.


• Devised a method for generating new, complete, and consistent 1040 feature vectors from the original set of feature vectors, which included both 64 config bits and 8 selection bits, resulting in a linear model over the new feature vectors that consistently delivers accurate results.


• Achieved outstanding results in accuracy using the LinearSVC model with L1 penalty, attaining a remarkable 99.82% accuracy on the training dataset and 99.2% accuracy on the testing dataset.

GitHub Repository

Course Project: Introduction to Machine Learning (March'23 - April'23)

• Developed a decision tree learning algorithm for a word guessing game, utilizing a dictionary of 5167 words and only 15 trials to accurately guess the correct word with the additional constraint that characters were only revealed if they were at the same location in both the secret and query word.


• Developed and implemented an efficient algorithm that utilized dynamic programming to determine the optimal query word at each node of a decision tree used for a word matching task that resulted in node splitting, with the query word selected to maximize the number of matching characters at corresponding positions among the words in the node.


• Learnt a decision tree that achieved 100% accuracy, with remarkable performance metrics including a fast training time of 0.23 seconds, a compact model size of 1551.7 Kb, and an impressive average of 3.706 queries per round.

Self Project (Oct'22 - Dec'22)

• Learnt techniques such as L2 and dropout regularization, hyperparameter tuning, batch normalization, and gradient checking and implemented and applied a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, while checking for their convergence.


• Learnt to use best practices to train and develop test sets and analyzed bias/variance for building DL applications, used standard NN techniques, applied optimization algorithms, and implemented a neural network in TensorFlow.


• Diagnosed errors in a machine learning system; understood complex ML settings, such as mismatched training/test sets and applied end-to-end learning, transfer learning, and multi-task learning.

   

GitHub Repository

Mentor: Dr. Raj Dandekar, Ph.D., CSE department, MIT (Oct'22 - Nov'22)

• Learnt to be proficient in using Manim library, a mathematical animation engine developed in Python, to create engaging and informative visual representations of mathematical concepts, including visualizations of mathematical formulas, graphs, and geometric shapes.


• Demonstrated a keen aptitude for learning and innovation, continuously expanding knowledge of the Manim library to create visually engaging and effective animated videos that clearly explained complex mathematical concepts, earning positive feedback from both students and educators.


• Produced a series of 13 animated videos covering all elementary concepts of Surface Area and Volumes, and an additional 21 animated videos that explained concepts related to Trigonometric Ratios, providing students with a comprehensive visual learning experience.

GitHub Repository

Mentor: Prof. Ashwani Thakur, Biological Sciences and Bioengineering, IIT Kanpur (Sept'22 - Oct'22)

• Conducted in-depth research on Nobel Laureates Dr. Hargobind Khorana, Dr. W. Stanley, and Dr. Marshall Nirenburg, reading and summarizing their research papers to gain a comprehensive understanding of their work and contributions to the field of genetics.


• Studied the transfer of genetic information, DNA replication, and the cracking of the genetic code through articles and transcribed interviews, deepening knowledge of these topics and their implications in genetics research.


• Demonstrated strong research skills and attention to detail, synthesizing complex information into clear and concise summaries and analyses for effective communication of scientific concepts to both technical and non-technical audiences.

Association of Computing Activities, IIT Kanpur (Aug'22 - Oct'22)

• Acquired fundamental knowledge on algorithms and data structures, including time complexity, binary search, graph algorithms like BFS and DFS, modular inverse, and binary exponentiation, through the project.


• Gained practical experience in solving problems efficiently in competitive programming, enhancing problem-solving skills.


• Developed a solid foundation in computer science concepts, equipping me with the necessary skills to tackle complex problems and find effective solutions.

Course Project: Manufacturing Processes - II(Jan'22 - April'22)

• Collaborated with a team of 10 members under the supervision of laboratory staff to manufacture a motor-driven model of an orrery using 4 pairs of gears, which involved milling, lathe work, assembling, and other machining procedures with a high degree of accuracy.


• Demonstrated expertise in precision machining techniques and strong teamwork skills to create a fully functional model of an orrery, showcasing the ability to work efficiently in a team-based environment while maintaining high quality standards.

Course Project: Manufacturing Processes - I(Aug'22 - Nov'22)

• Collaborated with a team of 9 members to design and construct a functional wheelchair model using various manufacturing techniques, including welding, brazing, moulding, casting, sheet-metal cutting, and folding.


• Supervised by laboratory staff, gained hands-on experience in wheelchair design and synthesis, demonstrating proficiency in practical skills such as assembly, measurement, and machining.


• Successfully completed the project, producing a fully functional wheelchair model that met the required specifications, highlighting strong problem-solving and teamwork abilities.