4^th Webinar on Robotics December 29-29, 2021 London, UK

Biography:

Asif is a senior high school student at Notre Dame College, Dhaka who will graduate in November 2021. He is a machine learning enthusiast from an early age and attending MIT Beaver Summer Works in 2021 on Quantum Computing and machine learning. He is the youngest research work publisher in the field of computer science in Bangladesh in 2020. He is also the software engineer and editor of Young Scientists Journal which is the world’s first peer-reviewed research journal for youths.

Abstract:

The advancements of computer science and its related fields are making our tasks easier in almost every scientific and non-scientific field. The use of machine learning in the field of drug discovery and development is accelerating so fast and helping us to discover anti-viral drugs for devastating viruses like coronavirus. The author will discuss using a deep reinforcement learning model 'ORGAN' which is a modified version of Generative Adversarial Network for predicting the potential anti-viral of coronavirus. The author used the deep reinforcement learning model (ORGAN) to generate potential candidates’ drugs, with a λ of 0.2 and epochs of 240 and a sample set of 6400, 10 good sample SMILES were generated and the Solubility or LogP of these samples is 0.7098. Then using the coronavirus as a target, all the good samples of SMILES were bounded and the drug with the highest binding affinity (Most negative value) is C18H15ClN4O2 also known as Olutasidenib which can be the potential anti-viral drug of coronavirus.

Biography:

Asif is a senior high school student at Notre Dame College, Dhaka who will graduate in November 2021. He is a machine learning enthusiast from an early age and attending MIT Beaver Summer Works in 2021 on Quantum Computing and machine learning. He is the youngest research work publisher in the field of computer science in Bangladesh in 2020. He is also the software engineer and editor of Young Scientists Journal which is the world’s first peer-reviewed research journal for youths.

Abstract:

The advancements of computer science and its related fields are making our tasks easier in almost every scientific and non-scientific field. The use of machine learning in the field of drug discovery and development is accelerating so fast and helping us to discover anti-viral drugs for devastating viruses like coronavirus. The author will discuss using a deep reinforcement learning model 'ORGAN' which is a modified version of Generative Adversarial Network for predicting the potential anti-viral of coronavirus. The author used the deep reinforcement learning model (ORGAN) to generate potential candidates’ drugs, with a λ of 0.2 and epochs of 240 and a sample set of 6400, 10 good sample SMILES were generated and the Solubility or LogP of these samples is 0.7098. Then using the coronavirus as a target, all the good samples of SMILES were bounded and the drug with the highest binding affinity (Most negative value) is C18H15ClN4O2 also known as Olutasidenib which can be the potential anti-viral drug of coronavirus.

Biography:

Erica Li is in charge of overseas BD marketing and sales in HSOAR Precision Robotics from Sep 2019. Before joining HSOAR, she has demonstrated 18 years experience with both marketing and international BD role in reputable multinational and group manufacturing companies. In recent two years, she has published 1000+ posts, articles,videos on personal social networks. 

Abstract:

Where there is a motor, there will be a reducer. The Most key component of the robot, the reducer, belongs to the first of three core parts. As far as the robot system is concerned, the precision reducer business is the most central profit source in the whole robot industry chain. 

Ball precision cycloidal reducer is recommended to provide the outstandingly perfect accuracy and repeatability through its full-contact, all-involve simple steel ball rolling cycloidal mechanism ! ！ The zero-backlash reducer will also be keeping excellent accuracy through long operating life of robot repeated motion, It has been applied and acknowledged by world top famous robot brand since January 2021 to replace gear mechanism.

Biography:

Joe is currently 20 years old, studying an Entrepreurial Business Management Undergraduate Degree at Northumbria University. He is the Co-Director of the European Chatbot Summit 2021. He is the host of Founders of the Future, an emerging technology entrepreneurship podcast, and has interviewed 16 tech startup founders in the fields of AI, Blockchain, IoT, Virtual Reality and many more.

Abstract:

Artificial is an inexorable force, whether we like it or not. In the right hands, artificial itelligence can be a force for good. I believe AI has the potential to solve some of the worlds grand challenges. AI has the potential to change the lives of billions, and the course of history.

My talk will help you to understand where the opportunities lie, and how to take advantage of them.

AI isn’t just about labling cats and dogs, automating business processes or reducing cots. Right now, AI and machine learning is being applied to many humanitarian and environmental projects. In this talk I will disect specific case-studies, to demonstrate the philanthropic potential of these exciting new technologies.

Biography:

Athira M is a lead Data Scientist at Dubai Technologies, who is passionate about the transformation of traditional traffic monitoring systems, to a next pace using Artificial Intelligence, deep learning, machine learning, natural language processing and computer vision technologies. She has completed M.Tech in Computation Linguistics from University of Calicut and has 5+ years of experience as Data Scientist. She is an active member of WomenTech Network and was nominated for AI Inclusion award by the network. She is often invited to speak at conferences and recently she has spoken at GEC, Palakkad and MBZ University for Artificial Intelligence, Abu Dhabi.

Abstract:

Autonomous Vehicle is a technological revolution in the transportation industry and is one among the most anticipated trends of near future. It uses a combination of cameras and sensors like lidar and radar for understanding the scene around it and thereby taking the necessary actions accordingly.   This work focuses on  segmenting the scene i.e. separation of whole image into individual segments, detecting objects of interest from the road using the 2D view of the road, which is obtained from cameras installed in the vehicle.  The objects of interest include traffic signals, traffic signs, road lanes, pedestrian, road markings, vehicles in blindspot area etc. The work also focuses on the headpose detection of the driver to identify whether he is performing mirror and shoulder checks properly. This can be viewed as a driver monitoring application also.