Deep Dive Into Dimensionality Reduction - A Machine Learning Approach
"Deep Dive Into Dimensionality Reduction - A Machine Learning Approach" is a one day workshop is aimed to provide students from 6th Semester of CE & IT Department with an in-depth understanding of machine learning techniques, focusing particularly on dimensionality reduction methods.
It is led by Prof. (Dr.) Mehul Raval, Experiential Learning, Ahemedabad University who will be covering key topics such as Machine Learning fundamentals, exploration of problem areas in Regression & Classification, and comprehensive insights into Principal Component Analysis (PCA). These topics are crucial for comprehending complex data structures and are fundamental in various applications across industries.
In an era dominated by data-driven decision-making, proficiency in machine learning and dimensionality reduction techniques is indispensable for aspiring data scientists and machine learning engineers. Through interactive sessions, practical exercises, and collaborative discussions, students will enhance their analytical capabilities and expand their technical expertise under the guidance of experienced professionals in the field.
In conclusion, this workshop offers students a chance to deepen their understanding of machine learning, particularly in dimensionality reduction. Through the interactive session and practical exercises, students will enhance their analytical skills. Mastering key topics like Machine Learning fundamentals and PCA promises to unlock new opportunities in data science careers.
Date and Time
Location
Hosts
Registration
- Date: 15 Mar 2024
- Time: 03:30 AM UTC to 09:30 AM UTC
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- LDRP ITR Campus
- Gandhinagar, Gujarat, Gujarat
- India 382016
- Building: Shift 1
- Room Number: MCA Labs
- Click here for Map
- Contact Event Host
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Prof. Anita Anand : anita_ce@ldrp.ac.in
Prof. Trupesh Patel : trupesh_ce@ldrp.ac.in
- Co-sponsored by IEEE LDRP Institute of Technology & Research Student Branch
Speakers
Dr. Mehul Raval of Ahmedabad University
Machine Learning
Key Topics
- Quick View: Machine Learning
- Problem areas in Regression & Classification
- Principal Component Analysis (PCA)
Biography:
Dr. Raval earned his Bachelor's in Electronics and Telecommunication Engineering from the College of Engineering Pune, India. He pursued further studies, obtaining a Master's in Digital Systems in 2002 and a Ph.D. in Electronics and Telecommunication Engineering in 2008 from the University of Pune, India. His research interests include – Computer Vision, Image Processing, Machine Learning, Data Analytics, and Engineering Education.
He is now a faculty member at Ahmedabad University, serving as the Associate Dean of Experiential Learning and Professor from 2020. From 1997 to 2008, he served as a lecturer and assistant Professor at SCET, Surat, India; from 2008 to 2013, he served as an assistant professor at DA-IICT Gandhinagar, India. From 2013 to 2018, he was an associate professor at Ahmedabad University. He was the founding head of the department and Professor at the ICT department of the School of Technology, PDEU, Gandhinagar, from 2018 to 2020. With over 25 years of experience, Dr. Raval has had the opportunity to engage in academic activities abroad, conducting research at Okayama University in Japan as a recipient of the Sakura Science fellowship. He also served as an Argosy visiting associate Professor at Olin College of Engineering in the United States in 2016. He held a visiting professorship at Sacred Heart University, USA in 2019.
He has received many accolades and awards, including a Young Scientist Fellowship by the Department of Science and Technology, Govt. of Gujarat (2005), the Indian Society for Technical Education (ISTE) Best Engineering College Teacher award for the State of Gujarat (2005), IEEE Region-10 Outstanding Branch Counselor award(2012), appreciation certificate for Dedicated leadership and support of the activities for SPS Chapter, IEEE Signal Processing society (2014), Distinguished Speaker Computer Society of India (2015), Gandhian Young Technological Award(2016), 50 Fabulous Edutech Leaders Award (2019), Intel – AI Prize at BraTS 2019, IEEE Access Outstanding Associate Editor (2018 to 2022), and several Best Paper awards from conferences.
Dr. Raval's research has been published in reputable journals, magazines, conferences, and workshops. He has been a reviewer for well-known publishers, including IEEE, ACM, Springer, Elsevier, IET, and SPIE. His research has received support from institutions such as the Board of Research in Nuclear Science (BRNS) and the Department of Science and Technology, Government of India. Dr. Raval mentors doctoral, Master, and Bachelor students and actively contributes to conferences, workshops, and symposiums as a program committee member. He also participates in curriculum development for esteemed Indian universities as a Board of Studies (BoS) member.
He serves as Senior Editor and Associate Editor of IEEE Access (2017 onwards ), Guest Associate Editor and Review Editor - Frontiers Machine Learning and Artificial Intelligence (2021 - ), Review Editor - Frontiers in Imaging (2022 - ). He served as Chair of the IEEE Computational Intelligent Society Gujarat Chapter (2021 – 2022), Joint Secretary of IEEE Gujarat Section (2019 – 2020), Vice Chair of the IEEE Signal Processing Society, Gujarat Chapter (2014 – 2015), Vice Chair of IEEE Gujarat Section (2013 – 2014), Secretary IEEE Gujarat Section (2011 – 2012).
Email:
Address:Ahmedabad, India, 380009
Media
| ML Workshop | 356.70 KiB | |
| Prof. (Dr.) Mehul Raval | 152.30 KiB | |
| IEEE ML Workshop Event Report | 4.64 MiB |