Date:
31st August 2023, 6.30 PM – 9.00 PM IST
Session 1:
Algorithm development in biotechnology by Dr. Nivedita Majumdar, Thermo Fisher Scientific
Biography:
In 2002, Dr. Majumdar accomplished her MS degree at The University of Memphis, followed by her PhD from George Mason University in 2007. Over the past 15 years, she has been an integral part of Thermo Fisher Scientific in California, a global frontrunner in scientific services. Presently, she holds the esteemed position of Senior Manager, leading the algorithm development efforts for the digital PCR product line. Her role entails close collaboration across various functions including software, hardware, systems, product management, molecular biology, field support, and legal departments.
Notably, Dr. Majumdar has spearheaded the creation of annotated datasets aimed at empowering AI and ML algorithms. These efforts focus on the research-use-only (RUO) and clinical segments of the digital and qPCR markets. Her contributions have extended to the publication of her research in esteemed high-impact journals. Furthermore, her innovative work has been recognized through the acquisition of multiple US patents.
Dr. Majumdar’s professional interests encompass a wide array of domains including Algorithm Development, Testing, Modeling, Signal Processing, Machine Learning, and Data Visualization.
Snapshot of the Session:
Session 2:
Towards Unsupervised Learning in Computer Vision by Prof. Amit Roy-Chowdhury, University of California, Riverside (UCR)
Biography:
Prof. Amit Roy-Chowdhury received his PhD from the University of Maryland, College Park (UMCP) in Electrical and Computer Engineering in 2002 and joined the University of California, Riverside (UCR) in 2004 where he is a Professor and Bourns Family Faculty Fellow of Electrical and Computer Engineering, Director of the Center for Robotics and Intelligent Systems, and Cooperating Faculty in the department of Computer Science and Engineering. He is the Director of the DoD Center of Excellence, NC4 (Networked Configurable Computing, Communications and Control for Rapid Situational Awareness). He leads the Video Computing Group at UCR, working on foundational principles of computer vision, image processing, and statistical learning, with applications in cyber-physical, autonomous and intelligent systems. He has published about 200 papers in peer-reviewed journals and conferences. Prof. Roy-Chowdhury’s research has been supported by various US Federal and State agencies and private industries, including the NSF, DoD, Google, Amazon, and CISCO. He is the co-author of two monographs on camera networks and target tracking. Some of his work has been featured widely in the news media, including a PBS/National Geographic documentary and in The Economist. He is a Senior Associate Editor of the IEEE Trans. on Image Processing, an Associate Editor of the IEEE Trans. on Pattern Analysis and Machine Intelligence, been an Area Chair of multiple computer vision and machine learning conferences, and on the program committees of many conferences. His students have been first authors on multiple papers that received Best Paper Awards at major international conferences, including ICASSP and ICMR. He is a Fellow of the IEEE and IAPR, received the Doctoral Dissertation Advising/Mentoring Award 2019 from UCR, and the ECE Distinguished Alumni Award from UMCP.
Snapshot of the Session:
Link of the lecture:
https://www.youtube.com/watch?v=MxC496PZupM