Schedule
Program schedule.xlsx - Sheet2 (5).pdfDay 1: 15th September 2021, Wednesday
8:00 AM - 9:15 AM: Talk 1: AI, Machine Vision and Robotics in Agriculture
Associate Professor, Biological Systems Engineering
Washington State University
Abstract:
Decreasing availability and increasing cost of farm labor is a critical challenge faced by agricultural
industry around the world. Robotics has played a key role in reducing labor use and increasing
productivity in farming. Modular automation and robotics technologies developed in recent years,
decreasing cost and increasing capabilities of sensing, control and automation technologies such as
UAVs, and increasing emphasis by governments around the world in mechanizing and automating
agriculture have created a conductive environment to develop and adopt smart farming technologies for
the benefit of agricultural industries around the world including smaller, subsistence farming operations
common in developing and underdeveloped countries. In this presentation, the author will first discuss
the importance of precision and automated/robotic systems for the future of farming (Smart Farming,
Ag 4.0). He will then summarize past efforts and current status of agricultural automation and robotics
including examples from fruit harvesting and fruit tree pruning, followed by an introduction of the
novel systems being developed in his program. The technologies to be introduced include robotic fruit
harvesting, targeted shake-and-catch harvesting, and fruit tree and berry bush pruning. At the end,
major challenges and opportunities in agricultural robotics and related areas, especially in small-scale
farming common in countries like Nepal, as well as potential future directions in research and
development will be discussed.
11:00 AM- 12:15 AM Keynote 1: Traditional ML Vs Deep Learning
Prof. Dr. Shashidhar Ram Joshi
Dean, Institute of Engineering,
Pulchowk, Nepal
1:15 PM - 2:30 PM : Talk 2: Supervised Learning: Tutorial for Beginners
Tej Shahi
Asst. Professor, TU-CDCSIT
Research Fellow, CQUniversity, Australia
Co-founder, MLDSN
2:45 PM- 4:00 PM: Talk 3: Data Science Overview and Applications
Dr. Jhanak Parajuli
Co- founder, MLDSN, Nepal
4:15 PM - 5:15 PM: Talk 4: Generative Adversarial Network (GAN) for Data Augmentation
Dr. Binod Bhattarai
Senior Research Fellow
University College London
Day 2: 16th September 2021, Thursday
8:00 AM- 9:15 AM: Keynote 2: Secure and Trustworthy Machine Learning Algorithms and Artificial Intelligence Systems: Status, Challenges and Perspectives
Professor, Department of Electrical Eng. & CS
Howard University, Washington DC
Abstract:
In this talk, we will share the overview, vision as well as technical and contributed results about the secure and trustworthy machine learning algorithms and artificial intelligence systems.
9:30 AM - 10:45 AM: Talk 5: Machine Learning in Medical Imaging and Healthcare
Dr. Ukash Nakarmi
Assistant Professor
University of Arkansas
11:00 AM - 12:15 PM: Talk 6: Leveraging NLP and ML Solutions: Current Trends and Practices.
Dr. Bal K. Bal
Associate Professor and Head of Department,
Computer Science and Engineering,
Kathmandu University
Abstract:
NLP and ML, when leveraged, can result in robust language technology solutions, which would not have been possible in their standalone versions. This talk gives an overview of the current trends and practices on the hybridization of two technologies to achieve state-of-the-art solutions.
1:15 PM - 2:30 PM: Talk 7: A session on AWS Cloud Computing
Anjani Phuyal
Global CTO and Founder,
Genese Solution
2:45 PM - 4:00 PM: Talk 8: Deep Active Learning
Razvan Caramalau
Research Post-graduate
Imperial College London
Abstract:
Large-scale dataset annotation has been a laborious, expensive, and time-consuming process. In this talk, we will go through one of the key solutions for optimizing real data selection with Active Learning. A short presentation of this standard practice is presented within the deep learning domain. We will address the recent trends and how these impacted several vision applications.
4:15 PM- 5:15 PM - Talk 9: Building a Nepali Quantum Computing Ecosystem
Dr. Manish Thapa
President, OneQuantum Nepal
Quantum Engineer, Germany
Abstract:
In this presentation, I will discuss how Nepalis can help catalyse a nascent quantum ecosystem within Nepal. Quantum computers operate by harnessing the fundamental laws of nature. These devices are seen to have capacity to solve computational tasks much faster than our present-day supercomputers. Tasks suited for quantum computers include traffic route optimization, drug discovery, financial modelling, better batteries and artificial intelligence, among others. Many sources estimate $50 billions worth of market for quantum computers by 2030. If this number is accurate, Nepal should partake in the quantum revolution now so as to built capabilities, workforce as well as a sizeable quantum market within Nepal and beyond. After a short crash course on quantum computing, I will discuss about different potential ways to achieve this challenging yet seeming rewarding goal.
Day 3: 17th September 2021, Friday
8:00 AM- 9:15 AM: Talk 10 : Video Based Scoring prediction in basketball game using deep learning architecture
Dr. Sarbagya Ratna Shakya
Asst. Prof. Eastern New Mexico University
9:30 AM - 10:45 AM: Talk 11: Machine Learning in Healthcare
Dr. Bibek Paudel
Post-doctoral Research Fellow
Stanford University
11:00 AM- 12:15 PM: Talk 12: Building machine learning products
Dr. Rakesh Katuwal
Machine Learning Engineer
Fusemachines Inc.
13:15 - 14:30: Talk 13: AI in Education
Dr. Dovan Rai
Researcher,
Global Institute for Interdisciplinary Education
14:45 - 16:00: Talk 14: Application of Machine Vision and Deep Learning in Agriculture
Dr. Anand Koirala
Post-doctoral Research Fellow,
Institute of Future Farming,
CQ University Australia
Abstract:
In this talk, he will explore some example applications of machine vision and deep learning in
Agriculture. Highlights will be Object Detection and Classification using Deep Learning
Convolutional Neural Networks (CNN). A general overview of Machine Learning, Computer
Vision and Image processing will also be covered.
17:15 - 18:15: Keynote 3: AI in Nepal
Dr. Sameer Maskey
CEO and Founder,
Fusemachines Inc.
Day 4: 18th September 2021,Saturday
8:00 - 9:15: Talk 15: An Application of NLP in Health Domain
Dr. Sabita Acharya
R &D Scientist, NLP
Proctor and Gamble, USA
Abstract:
This talk will cover my work on generating personalized and patient-friendly health information. I will discuss some of the challenges of working in this domain and talk about how we collected data, built our pipeline, and conducted evaluations.
9:30 AM - 10:45 AM: Talk 16: Robust and Flexible Machine Learning for Real-world applications
Dr. Sunil Aryal
Lecturer in IT,
Deakin University, Australia
11:00 AM- 12:15 PM: Keynote 4: Artificial Intelligence in Least Developed Countries: Are we ready ?
Prof. Dr. Manish Pokharel
Dean, Kathmandu University
1:15 PM - 2:30 PM: Talk 17: Machine Learning and Artificial Intelligence for Geospatial data: Status, Challenges and Perspectives
Dr. Bhogendra Mishra
Research Fellow,
Policy Research Institute, Nepal
4:15 PM - 5:15 PM: Talk 18: Wireless Communications and Its Optimizations
Dr. Samip Malla
Wireless System Engineer
Germany
Day 5: 19th September 2021, Sunday
8:00 AM- 9:15 AM: Talk 19: Semantic Search: Retrieval with Meaning
Dr. Archana Bhattarai
Senior Search Relevance Engineer
Apple, USA
Abstract:
The traditional information retrieval methodology is guided by the document retrieval paradigm, where relevant documents are returned in response to user queries. This paradigm faces serious drawback if the desired result is not explicitly present in a single document. The problem becomes more obvious when a user tries to obtain complete information about a real world entity and its properties such as “best food in Kathmandu”, “best place to visit in Nepal”. In such cases, understanding the meaning of the query is important as well as collecting various facts about the target entity or concept from multiple document sources. We present in this talk, various methods to get to the meaning of the query and methods to extract information about a target entity based on the concept retrieval paradigm that focuses on extracting and blending information related to a concept from multiple sources if necessary. The paradigm is built around a generic notion of a semantic understanding which is defined as “the process of capturing the real meaning of a document beyond word and phrase frequencies, to represent the interpretation of text, in order for computers to be able to process it”.
9:30 AM- 10:45 AM: Talk 20: AI for Health: Academic and Industrial Perspective
Bishal Lamichhane
Researcher, Scalable Health Labs
Rice University, USA
Abstract:
We are witnessing the rapid ascent of AI-enabled healthcare technologies in the past years. Applications across the healthcare spectrum of diagnosis, therapeutics, and care are being developed with some, or the majority, of the components driven by advanced AI solutions. There are unique challenges in healthcare such as the unavailability of large datasets, the need for personalization, frequent concept drifts, privacy needs, etc. which stipulates innovative AI solutions. In this talk, I will share some recent advances on AI for healthcare applications being pursued at the Scalable Health Labs, Rice University, in collaboration with its academic and clinical collaborators. This discussion will mainly focus on mental health where opportunities for improvements are plenty. I will also share some industrial perspectives on the productization of AI solutions in healthcare markets based on my experiences at Philips Research and IMEC.
11:00 AM - 12:15 PM: Talk 21: AI in Health care for LMICs like Nepal
Director/Research Scientist NAAMII
Co-founder/Scientist Diyo.ai
Abstract:
Taking an example of Nepal, we will see a brief overview of important health problems in Low and Middle Income Countries, then see what potential opportunities and challenges AI has in solving some of the difficult health care delivery challenges with a focus on rural and community health services. We will then go into some of the open problems in machine learning that are relevant to the development of health care in AI.
2:45 PM - 4:00 PM: Talk 22: A Session on Big Data
Er. Jnaneshwar Bohara
Computer Engineer
Government of Nepal
4:15 PM - 5:15 PM: Talk 23: Business Strategy in the age of AI
Dr. Yash Raj Shrestha
Senior Researcher, ETH Zurich,
Assistant Director, Strategy and AI Lab
5:15 PM - 6:15 PM: Talk 24: Strong AI
Ashok Pant
VP of Engineering and Co-founder
Treeleaf Technologies Pvt. Ltd