Special AI course offers tools to leverage the benefits of AI in real-life settings

FCAI and the Finnish Indian Consortia for Research and Education (FICORE) organize a special course to help industry to identify and solve the most pressing challenges and teach best practices regarding artificial intelligence, machine learning and deep learning. You can find the course details and register to the course below.

AI/ML/DL for Industry: Special FCAI/FICORE Project Course

Tentative dates: April 11–June 18 (inaugural)
Instructor: Vikas Garg (Assistant Professor, Aalto University; Co-Founder, YaiYai Oy; PhD, MIT)

Background

Artificial Intelligence and Machine Learning (AI/ML), including deep learning (DL), is all set to transform the society around us in unprecedented ways. However, the industry typically fails to leverage the benefits that cutting-edge AI/ML techniques can bring to their real-life settings, owing to some critical handicaps, including, but not restricted to:

(1) technical challenges in

  • abstracting the industry setting (constraints, requirements, etc.),

  • identifying opportunities for leveraging AI/ML/DL that could enable significant

  • competitive advantage and streamlined processes,

  • framing the right questions, and formulating concrete AI/ML problems,

  • optimizing tradeoffs to minimize the inefficiencies and maximize the benefits,

  • defining appropriate scalable and robust DL models and architectures,

(2) significant discrepancy between published models founded on idealized assumptions (e.g., about the amount and quality of data), and real-life challenges faced by a company, and

(3) lack of skilled AI/ML/DL experts who can guide the process,  evaluate pros and cons of different methods,  innovate and conjure new principled learning techniques and models tailored for the setting of interest, take follow-up corrective actions, and implement, e.g., efficient DL models.

Aim

The objectives for this project are two-fold:

(1) work closely with industry to help identify and solve their most pressing challenges via a scientifically principled and procedurally transparent AI/ML/DL process,

(2) teach best practices in AI/ML/DL, and inculcate out-of-box thinking and  rigorous real-life problem solving skills to students as well as industrial practitioners.

Course Structure & Organization

The tentative plan for the course (evolving, subject to minor changes) is as follows.

(1) Industry partners shall be given the opportunity to express their interest in registering for the course for free, by filling in a Google form prompting for basic information such as contact person(s), a short high-level description of the problem setting/domain, etc. The deadline for expression of interest by the industry partners is March 22.

(2) Separate registrations will be made open to students (PhD, Master’s, and advanced Bachelor’s) - who work in AI/ML/DL or related areas, and satisfy some additional prerequisites - from participating academic institutes (Aalto University, University of Helsinki).

Course credits: TBD

(3) Based on the information provided by industry partners and students’ preparation (coding skills, mathematical proficiency, previous projects and courses, internships etc.), we will conduct a rigorous matching process to assign a tentative 3-4-person team for each project.

Note: Due to time constraints, we’ll be limiting the inaugural course to at most 15 companies (i.e., 15 projects) and 60 students. However, we plan to offer the course again in the near future, when we will prioritize the companies that express interest but miss out in the initial matching process.

(4) Representatives from selected industry partners shall be invited to a kick-off session, tentatively, in the week beginning April 11, where they can give a quick overview of one or two key problems they would like to investigate. If required, this information will be used to refine the student teams assigned for the projects in order to ensure required competencies are met.

(5) To track progress and discuss next steps,  regular (bi-weekly or tri-weekly) meetings will be held for each project between the course instructor, and the students and company representative(s).

(6) Towards the end of the course, students on each project would be expected to write a report and/or make a presentation about their work, and share their findings with the relevant company. 

For enrollment or any questions, or more information, please reach out to the organizers latest by March 22, 2022.

Organizers

(1) Dr. Vikas Garg (Instructor for the course):

Vikas Garg is currently Assistant Professor with Aalto University and FCAI. He holds a PhD in Computer Science (specialization: AI/ML/DL) from the Massachusetts Institute of Technology (MIT), USA. He has over 15 years of experience in research, teaching, engineering, product development, and supply chain management including stints at leading academic institutes, business schools, and companies such as Amazon A9, Microsoft Research, and IBM Research.

He is also Co-Founder and Chief Scientist at YaiYai Oy, a company established to provide cutting-edge AI/ML/DL based solutions to startups, governments, and leading companies across the globe in multiple sectors including Biopharma, IoT, Energy, FinTech, and Gaming.

Some of his recent innovations have led to advances in diverse domains such as protein design,  multi-attribute visual search, fast inference on IoT devices such as smartphones, query recommendation and auto-completion for e-commerce platforms, drug discovery, strategic decision making in multi-agent systems, global supply chain dynamics, and design of smart grids and next generation wireless systems. He holds multiple patents and his research gets published regularly at premier venues in AI, ML, NLP, Computer Vision, Automation, Energy, etc. (e.g., NeurIPS, ICML, CVPR, AISTATS, UAI, AAAI, IJCAI, TKDE, CIKM, e-Energy, and SmartGridComm).

Select honors include BP Technologies Fellowship awarded by MIT to the strongest incoming students, top ranks in competitions such as Microsoft Imagine Cup, and highest student evaluation scores for an Applied ML course that he co-designed and co-instructed at MIT.  He's also been an Energy Fellow at MIT as well as active member of Machine Learning for Pharmaceutical Discovery Symposium (MLPDS), a consortium of leading pharma companies with MIT.

(2) Ms. Terhi Kajaste (FCAI Contact)

Terhi Kajaste from the Aalto University is the Manager of Industry and Society collaboration at Finnish Center for Artificial Intelligence FCAI. FCAI is a community of experts that brings together top talents in academia, industry and the public sector to solve real-life problems using both existing and novel AI. Terhi will be supporting the instructor and facilitating the participation of the companies to the course. 

(3) Ms. Kit Srinivasan (FICORE Contact)

Kit Srinivasan is a Senior Manager at the Global Engagement team of Aalto University. Kit is currently coordinating the FICORE (Finnish Indian Consortia for Research and Education) network which involve 38 higher education institutions from India and Finland. Kit will be supporting the instructor by inviting some of the Indian companies and start-ups to benefit from the course.

Contact Information

Vikas Garg (vikas.garg@aalto.fi)
Terhi Kajaste (terhi.kajaste@aalto.fi)
Kit Srinivasan (kit.srinivasan@aalto.fi)

Kaisa PekkalaEducation, Industry and Society