Dr. Pratik Barot of Government Engineering College, Gandhinagar

Support Vector Machines (SVMs) are powerful for classification, using a hyperplane to separate classes by maximizing the margin between them. When data isn't linearly separable, the "kernel trick" helps by mapping data to a higher-dimensional space without explicitly calculating this transformation. Kernels, like the polynomial or RBF (Gaussian) kernel, allow SVMs to create complex decision boundaries in the original feature space. The optimization problem for SVMs involves finding support vectors—key data points closest to the boundary—that define the model, making it efficient and robust. However, the right kernel choice and computational demands on large datasets can be challenging.

Biography:

Dr. Pratik Barot is an Assistant Professor at the Government Engineering College, Gandhinagar. With over ten years of professional experience, Dr. Barot has worked in both academia and the software industry. His expertise encompasses data mining, computer algorithms, database systems, and Oracle. 

He holds an ME/MTech from L.D. College of Engineering and a BE/BTech from Sankalchand Patel College of Engineering. Dr. Barot has taught courses in data mining, database management systems, operating systems, and other core computer science subjects. Additionally, he serves as the institute's Placement Coordinator.

His skills include data mining, machine learning, business intelligence, and Oracle database management. Dr. Barot has also participated in various training programs and workshops on topics ranging from intellectual property rights to privacy and security engineering, hosted by renowned institutions such as IIT Kharagpur, NIT Goa, and NITTTR Bhopal.

Email:

Address:Government Engineering College, Sector-28, Gandhinagar, India, 382028

Dr. Hiten Kanani of Government Science College, Gariyadhar

In linear algebra, a vector space is a set of vectors where vector addition and scalar multiplication are defined, fundamental for various mathematical operations. Eigenvalues and eigenvectors are properties of a matrix that describe how it transforms vectors in space; an eigenvector of a matrix remains in the same direction after transformation, scaled by its eigenvalue. Singular Value Decomposition (SVD) is a matrix factorization technique that decomposes any matrix into three components (U, Σ, and V matrices), useful for dimensionality reduction, noise reduction, and data compression in machine learning and statistics.

Biography:

Dr. Hiten Kanani is a dedicated mathematics professor, born on September 8, 1988, in Gujarat, India. He holds a B.Sc. in Mathematics from Saurashtra University, an M.Sc. in Mathematics from Sardar Patel University, and earned his Ph.D. in Mathematics from the same institution in 2016.

Dr. Kanani has an impressive track record of academic excellence, including multiple state-level awards in mathematics and prestigious scholarships, such as the National Board of Higher Mathematics Scholarship and UGC Junior Research Fellowship. His research primarily focuses on Banach algebras, and he has published numerous papers in reputable journals like the Proceedings of the American Mathematical Society and the International Journal of Mathematics and its Applications.

In his professional career, Dr. Kanani has amassed extensive teaching experience at both secondary and college levels, specializing in calculus, linear algebra, real analysis, complex analysis, and more. Currently, he teaches mathematics to B.Sc. students, preparing them for competitive exams like IIT-JAM. His expertise has also been shared through lectures and research presentations at various seminars, workshops, and conferences.

Dr. Kanani is an active participant in academic development, regularly attending and conducting workshops, faculty development programs, and refresher courses. He also shares his knowledge through his YouTube channel, Mathematics with Hiten Kanani, where he connects with a broader audience, furthering his impact in mathematics education.

Dr. Parita Shah of Vidush Somany Institute of Technology and Research

This session will cover the applications of linear algebra in machine learning, focusing on principal component analysis (PCA), dimensionality reduction, and matrix factorization techniques. Participants will engage in hands-on implementation of PCA and explore Singular Value Decomposition (SVD) using Python libraries such as NumPy and SciPy.

Biography:

Dr. Parita Shah is working as an assistant professor in computer engineering at Vidush Somany Institute of Technology and Research with more than 10 years of experience. She completed her Ph.D. from Parul University and has a robust academic background with degrees from esteemed institutions in Gujarat. Dr. Shah has a keen interest in sentiment analysis, particularly in the Gujarati language and has published several papers in renowned journals. She has also received financial grants for projects and holds a patent for a virtual reality headset.  Her dedication to academic counseling, research, and innovative teaching methods has made significant contributions to her field. Dr. Shah is committed to fostering student engagement and achieving program outcomes through effective learning strategies.

Email:

Address:Vidush Somany Institute of Technology and Research, SVIM Campus, Ayodhya Nagar, Kadi, India, 382715

Dr. Krunal Kachhia of Charotar University of Science & Technology

Differentiation, Gradient, Hessian, Optimization Techniques (Gradient Descent, Lagrange Multipliers), Gradient Descent and its Variants in Machine Learning (Stochastic Gradient Descent, Adam Optimizer) Implement gradient descent algorithms and explore their impact on training models

Biography:

Dr. Krunal B. Kachhia is the Head of the Department of Mathematical Sciences at the P. D. Patel Institute of Applied Sciences, Charotar University of Science and Technology (CHARUSAT), located in Changa, Anand, Gujarat, India. He completed his B.Sc. (Mathematics) in 2008, M.Sc. (Mathematics) in 2010, and M.Phil. (Mathematics) in 2012 from Sardar Patel University, V. V. Nagar, Gujarat. Dr. Kachhia earned his Ph.D. from CHARUSAT in 2017. With over 13 years of academic experience, his research focuses on Fractional Calculus and Chaos Theory.

Dr. Kachhia has published 27 research papers in reputed national and international journals. He has successfully supervised one Ph.D. student and currently guides three more, alongside mentoring five M.Sc. students. His achievements have been recognized with several prestigious awards, including the CHARUSAT-GSA Best Thesis Award in Mathematical Sciences (2016) from the Gujarat Science Academy, the GSA – Dr. A. 

K. Shah Best Research Paper Award in Sciences (2020), Excellence in Research and Development (2024) from The MathTech Thinking Foundation (MTTF) in Punjab, and the Young Scholar Award of the Year (2024) from MTTF.

In addition to his research contributions, Dr. Kachhia serves as a reviewer for numerous esteemed international journals and has organized multiple academic events.

Email:

Address:Department of Mathematical Sciences, P. D. Patel Institute of Applied Sciences, Charotar University of Science & Technology, Changa, India, 388421

Dr. Mrugendrasinh Rahevar of Charotar University of Science & Technology

Gradient Descent and its Variants in Machine Learning (Stochastic Gradient Descent, Adam Optimizer). Implement gradient descent algorithms and explore their impact on training models.

Biography:

Dr. Mrugendrasinh Rahevar holds a PhD and serves as an Assistant Professor at the U & P U Patel Department of Computer Engineering, Charotar University of Science and Technology (CHARUSAT), Gujarat, India. He earned his Bachelor of Engineering in Computer Engineering (B.E.C.E.) from Gujarat University in 2006 and completed his Master of Engineering in Computer Science and Engineering (M.E.C.S.E.) at Gujarat Technological University in 2014. His primary research areas focus on computer vision and deep learning, where he actively contributes to advancements in these cutting-edge technologies.

Email:

Address:CHARUSAT Campus, ATPO Changa, Anand, India, 388421

Dr. Brajeshkumar Jha of Pandit Deendayal Energy University

The lecture is distributed into two parts. First part contains the basic probability and statistics. Second part contains the concept of hypothesis testing

Biography:

Dr. Brajesh Kumar Jha is working as an Associate Professor in the Department of Mathematics, School of Technology, Pandit Deendayal Petroleum University, Gandhinagar, Gujarat, India. He has more than 12 years of teaching and research experience. He holds a M.Sc. degree in Mathematics from Jiwaji University, Gwalior, MP. and a Ph.D. degree in Mathematics from S.V. National Institute of Technology, Surat, Gujarat, India. He is working in the area of mathematical neuroscience, application of fractional and fuzzy differential equations in biological and physiological process, Bioinformatics, AI/ML application in biological process. He has published more than 60 research papers in journals and conference proceedings like Springer, Elsevier, World Scientific, etc. He has organised number of national/international conferences, workshops, STTPs, Seminars etc. He has edited a book entitled “Computational and Analytic Methods in Biological Sciences: Bioinformatics with Machine Learning and Mathematical Modelling” that was published by River Publishing, Denmark. He was also served as editor of an international conference proceeding on “Mathematical Modeling, Computational Intelligence Techniques and Renewable Energy,” MMCITRE-2020 published in Springer. He also serves as a reviewer for many international journals of repute. He has guided 3 PhD and one M.Sc. students. Currently he is guiding 5 PhD students and 1 M.Sc. student.  He has presented many papers in various international conferences like Singapore, Srilanka, UAE, Portugal (Online) etc.

Email:

Address:Department of Mathematics, School of Technology, Raysan Village, PDPU Road, Pandit Deendayal Energy University, Gandhinagar, India, 382426

Dr. Safvan Vahora of Government Engineering College, Modasa

Application of Probability and Statistics in Machine Learning (Naive Bayes, Bayesian Networks, and Hypothesis Testing in ML Models). Implement a Naive Bayes classifier and hypothesis testing techniques using Python (Scikit-learn).

Biography:

Prof. Vahora’s research is at the intersection of Computer Vision, Machine Learning, Deep Learning, Medical Imaging and Image Processing. Prof. Vahora has delivered over 13 invited talks at various workshops and training programs. He has published over 20 research articles in reputed journals/conferences and has published three Indian patents. Prof. Vahora has performed role of a reviewer, editorial board member and program committee member at number of international journals and conferences.

Email:

Address:Government Engineering College, Modasa, ATPO Changa, Anand, India, 388421

Dr. Tathagatha Bandyopadhyay of Dhirubhai Ambani Institute of Information and Communication Technology

Foundations of Statistics in Machine Learning

Biography:

Dr. Tathagata Bandyopadhyay earned his PhD, MSc, and BSc degrees in Statistics from the University of Calcutta. Before joining DA-IICT, he held the position of Dean (Faculty) and Professor at the Indian Institute of Management Ahmedabad. Dr. Bandyopadhyay has extensive teaching experience and has visited several universities, including the University of Nebraska, University of Connecticut, Michigan State University, Iowa State University, University of Georgia, University of Windsor (Canada), Umea University (Sweden), and National University of Singapore. He assumed the role of Distinguished Professor at DA-IICT in December 2021.

Since 2009, Dr. Bandyopadhyay has been the editor of the Calcutta Statistical Association Bulletin. Additionally, he has contributed to the editorial boards of journals such as Sankhya, Journal of the Indian Society of Agricultural Statistics, and the Journal of Agricultural, Biological, and Environmental Statistics (a journal of the American Statistical Association).

Having authored over 70 research articles in premier national and international journals, Dr. Bandyopadhyay has significantly contributed to the field. In addition to his editorial responsibilities, he has supervised numerous PhD students and played a crucial role as a member of the PhD Dissertation Committee at the University of Calcutta and IIMA.

Email:

Address:Dhirubhai Ambani Institute of Information and Communication Technology, Near Reliance Cross Rd, Gandhinagar, India, 382007

Dr. Ojas Shriniwas of Pandit Deendayal Energy University

Introduction to data driven methods 
Introduction  to fluid mechanics and transport related problems.
Relavent problems for hybrid solutions (CFD ML)
Relavent problems for hybrid solutions (Experiment ML)
Datadriven approaches for steady state and  transient state problems.
Integration of AI in  Manufacturing processes

Biography:

A motivated scientist & academician in mechanical engineering, specialized in modelling of multiscale, multi-physics modelling. He is having more than 4.5 years of rich post-PhD experience. He has completed his post-graduation and Ph.D from IIT Kharagpur in Mechanical engineering.  Later, he completed his post-doctoral work at IIT Bombay. Dr Ojas Satbhai was awarded with Teachers Associateship for Research Excellence (TARE) by the Science and Engineering Research Board, Government of India. His core expertise lies in computational heat-transfer and fluid flow, and multi-scale modelling of solidification processes using high performance computing systems. He has numerous publications in the area of multi-scale, multi-physics modelling in manufacturing processes; microstructure modelling; material process optimization, energy storage system and phase-change Rayleigh B\'{e}nard convection.  Dr Ojas Satbhai was the convener for the 1st International Symposium on Battery Technology: Advances and Future Trends held on 19 - 21 January 2024 and jointly organized by Pandit Deendayal Energy University, India, Toronto Metropolitan University, Canada, and McMaster University, Canada.

Email:

Address:Mechanical Engineering Department, SoT, Pandit Deendayal Energy University, Gandhinagar, India, 382426

Prof. Manoj Sahni of Pandit Deendayal Energy University

Solving linear systems involves finding values for variables that satisfy a set of linear equations. Methods like Gaussian elimination, LU decomposition, and iterative techniques (e.g., Jacobi or Gauss-Seidel) are used to solve these efficiently, especially for large systems.

Non-linear Equations involve equations where variables appear with non-linear relationships, such as powers of trigonometric functions. Analytical solutions are often difficult, so iterative numerical methods like Newton-Raphson, bisection method, and secant method are commonly employed.

Numerical Methods provide approximate solutions to mathematical problems that may not have exact solutions. These methods cover areas such as root finding, integration, and differential equations. They are widely used in engineering, physics, and computer science to tackle complex systems.

Biography:

Dr. Manoj Sahni is a dedicated and experienced mathematics teacher and researcher with more than 19 years of experience and currently serving as a Professor in the Department of Mathematics, School of Technology, Pandit Deendayal Energy University, Gandhinagar, Gujarat, India. He has an excellent academic background with an M.Sc. (Mathematics with specialization in Computer Applications) from Dayalbagh Educational Institute (Deemed University), Agra, an M. Phil. from I.I.T. Roorkee, and a Ph.D. degree in Mathematics from Jaypee Institute of Information Technology (Deemed University), Noida, India. He has published more than 100 research papers in peer-reviewed journals (SCI/SCIE/ESCI/Scopus), conference proceedings (Scopus Indexed), and book chapters (Scopus Indexed) with reputed publishers like Springer, Elsevier, Taylor & Francis, and many more. He also serves as an advisory board member, technical committee member, and reviewer for many international journals of repute and conferences. He has organized four International Conferences on Mathematical Modeling, Computational Intelligence Techniques, and Renewable Energy (MMCITRE) in 2020, 21, 22 and 24. He participated in the scientific committees of several international conferences and associations and also delivered many expert talks at the national and international levels. He has organized many seminars, workshops, etc. In addition, he is a member of many international professional societies, including the American Mathematical Society (AMS), Society for Industrial and Applied Mathematics (SIAM), IEEE, Mathematical Association of America (MAA), Forum for Interdisciplinary Mathematics (FIM), Indian Mathematical Society (IMS), IAENG, and many more. He has written eight edited books, which were published by publishers like Springer, Taylor & Francis, NOVA, and River. He has guided 3 Ph.D. students, and three more are working under him. He has completed one project, and one is undergoing him sponsored by the Gujarat Council on Science and Technology (GUJCOST) (under DST).

Email:

Address:Department of Mathematics, School of Technology, Raysan Village, PDPU Road, Pandit Deendayal Energy University, Gandhinagar, India, 382426