Fellowship | Program

Program

TLF Program Experience

Spread over eight terms, each averaging six weeks, the program has four intertwined threads:

Data-X Coursework

Series of courses in Artificial Intelligence and Machine Learning, Design and Systems thinking to learn to apply technology to build holistic solutions.

Real-world Projects

12 week Challenge Lab to identify a need, market test, build a prototype, pitch to investors. 12 week Industry/ Research Capstone project, AI/ML centric (includes 8 weeks onsite).

Guest Sessions

Grand Challenge Lecture Series by domain experts on real-world AI/ML applications. Radical thinkers and global leaders share their ideas and walk you through their journey.

Leadership and mentoring

Intense curriculum involving goal setting, self reflection, group dynamics and leadership. Each Fellow is also assigned a distinguished mentor who is an eminent business leader or entrepreneur.

ACADEMIC CALENDAR: 2019 - 20

Orientation & Bootcamp: Aug 2 - Aug 7

Meet and Greet with Plaksha Founders

Dr. Ikhlaq Sidhu

Faculty Director & Chief Scientist
Sutardja Center for Entrepreneurship & Technology, UC Berkeley
Ph.D. & M.S. (Northwestern University)

Dr. Sidhu has 75 patents under his name and is the inventor of seminal technology that is used in internet communications today. He is also the co-creator of Berkeley Method of Entrepreneurship.

Ken Singer

Chief Learning Officer and MD
Sutarja Center for Entrepreneurship and Technology, UC Berkeley
Chair, European Innovation Academy Council

Ken is a serial entrepreneur, technology executive, who has founded or co-founded 5 companies in the mobility space. His experience ranges from mobile video advertising, downloadable mobile apps to advising governments. He specializes in Product lifecycle management.

TERM 1: Aug 8 - Aug 30

This is an in-depth course on Python programming with an overview of basic language concepts, built-in data types, and procedural and functional programming techniques, providing a foundation for the use of Python as a programming language in Machine Learning and Artificial Intelligence. The course includes Python basics, branching, iteration, string manipulation, guess and check, bisection, decomposition and functions, built in data types (Tuples, Lists, Dictionaries), recursion functions, testing, debugging, exceptions handling and ends with more advanced topics like Object Oriented Programming with Python, program efficiency and complexity, searching and sorting algorithms. The course will also give the students an overview of some data analysis libraries – Matplotlib, Pandas, Numpy, Scipy etc. and how to interact with databases in python. The course will have intense hands-on Python programming.

Kingshuk Dasgupta

Senior Manager, Site Reliability Engineering
Google, Massachusetts
B. Tech (IIT Kanpur), MBA (IIM Calcutta)

Kingshuk has more than 19 years of experience delivering complex distributed systems and customer facing web applications. He specializes in driving strategic change and creating architectural vision.

The course aims to teach the fundamentals of mathematics needed to become a proper practitioner of Artificial Intelligence and Machine Learning. The course provides a mathematically rigorous introduction to calculus, matrices and linear transformation, probability and other statistical tools. The course begins with an introduction to vector algebra, matrices, determinants, rank and trace of a matrix, eigenvalues and eigenvectors of a matrix, matrix calculus, principal component analysis and singular value decomposition as Linear Algebra concepts are key for understanding and creating machine learning algorithms. Further a selection of topics from the areas of statistical methods, probability, stochastic process and other statistical optimization theories will be covered in this course.

Name not published on the faculty's request

The success of a service or a product depends on how well its design addresses a need, and how resilient and adaptable it is. The design thinking methodology has been implemented by many organizations to consider these success factors right from the initial stages of product development. This course gives a hands-on project-based learning experience on the design thinking methodology. The topics covered in the course include introduction to design thinking, problem formulation, divergent and convergent thinking, idea generation, idea selection, prototyping, and testing. The course will provide a number of tools to support different aspects of design thinking. The students will learn how to follow the design-thinking process, identify user needs and formulate the problem, use ideation tools to generate ideas, use prototyping to effectively visualize and efficiently evaluate ideas, and select promising ideas for implementation of the solution. The students will also learn how to augment the design thinking process using domain-specific methods and tools.

Dr. Jitesh Panchal

Associate Professor of Mechanical Engineering, Purdue University
Ph.D. & M.S. (Georgia Tech)
B.Tech. (IIT Guwahati)

Dr. Panchal's current research focuses on science of systems engineering with focus on democratization of design and manufacturing. He was awarded University Silver Medal (1996-2000) at IITG.

The course highlights the ethical aspects of engineering in its entirety and trains future technology leaders to effectively resolve and handle ethical dilemmas that are encountered in designing, developing and implementing new advances in technology. The topics covered are ethical reasoning as applied to engineering principles and engineering designs, ethical sensitivity / ethics spotting, ethical imagination, ethical decision-making and reflections and responses. The course delves further into reflexive analysis and principlism of engineering ethics cases to amplify and develop moral reasoning.

Dr. Andrew O Brightman

Associate Professor of Engineering Practice, Purdue University
Ph.D. (Purdue University)
B.S. (North Carolina State University)

Dr. Brightman is developing a new pedagogy for training engineering students in ethical reasoning. He has taught Biomedical Engineering Ethics at Purdue.

TERM 2: Sep 2 - Oct 11

This course is based on the Data-X framework designed at UC Berkeley for learning and applying AI, Data Science, and emerging technologies. The topics include Installation Review / Jupyter Lab / Introduction to tools (Git, version control, IDEs, Google Colab etc), linear, logistic and polynomial regression, data visualization (Matplotlib, Seaborn, Plotly) and best practices, Entropy, Decision Trees, Random Forest, Gradient Boosting, dynamic programming, supervised and unsupervised learning, SVM, RBM, Bayesian techniques and time series analysis. NLP and image-processing will be covered at a basic level.

Dr. Ravi Kothari

Former Chief Scientist, IBM Research India
Professor of CS, Ashoka University
Ph.D. (West Virginia University)

IBM's first Distinguished Engineer from India, Dr. Kothari has deep strategy and innovation experience. His research interests are in Neural Networks, Pattern Recognition, Machine Learning, Big Data, Analytics, Streaming Analytics, Telecom.

Dr. Ikhlaq Sidhu

Faculty Director & Chief Scientist
Sutardja Center for Entrepreneurship & Technology, UC Berkeley
Ph.D. & M.S. (Northwestern University)

Dr. Sidhu has 75 patents under his name and is the inventor of seminal technology that is used in internet communications today. He is also the co-creator of Berkeley Method of Entrepreneurship.

Alexander Fred-Ojala

Research Director, Data Lab
Sutardja Center for Entrepreneurship & Technology, UC Berkeley
M.Sc. Mathematical Statistics (Lund University)

The workplace requires sharp communication skills, which comprise effective delivery, content and interaction. In this module, you will learn how to craft your content carefully, make a compelling presentation, and engage your audience.

Amit Kumar

Dr. Pradeep Chhibber

Professor of Political Science, UC Berkeley
Indo-American Community Chair in India Studies
Director, Institute of International Studies

The lecture will introduce the way developed and developing nations are looking at emerging technologies like AI and how the way forward is complicated by a number of considerations regarding effectiveness, accessibility, justice, ethics and of course the underlying tech itself. No universal solutions seem possible, but universally accepted principles can be articulated to obtain a balanced sub-optimal solution. A brief discussion how one such effort has been initiated will be highlighted.

Dr. Anurag Agrawal

Director
CSIR Institute of Genomics and Integrative Biology

A three-day program designed for exploring what is really possible in achieving unprecedented business results. Grounded in the best-selling book, The Three Laws of Performance, the program is designed for attendees to apply this cutting-edge approach in their current work and life situations.Over a period of 1 month culminating in the 3 day workshop, the course focusses on the students getting to gain critical awareness of the way human beings relate with each other, relate to themselves and their life and environment and how the function in a group and organisational context. The course enables students to take their performance to the next level and also be able to express themselves as leaders.The course is designed to impact their listening, communication, ability to question conventional thinking patters and ultimately have the participants to begin creating a new vision for themselves.

Balvinder Singh Sodhi

Country Manager
Vanto Group

This course aims to develop critical reading, thinking, and writing skills that will help you engage with the world of ideas, and enable you to develop and communicate your enhance your abilities to navigate the academic, professional, and social spheres around you. The following course outline is designed keeping in mind a 13 lecture course, spread over eight weeks. The course will employ the workshop model where the classes will not be lecture style but rather use a hands-on approach to writing and communications pedagogy. You will be made to read, write, reflect and re-write intensively over the duration of the course to maximise learning outcomes over the short duration of the course.

Anunaya Rajhans

TERM 3: Oct 14 - Nov 22

In this course, the participants need to apply the knowledge acquired in the first Data Science and Machine Learning course and work on a pre-defined project. Students work in teams or individually to encapsulate, design, develop, implement and test their project work. Optional curated lectures / support are provided on topics and programming practices relevant to the project. Students learn and improve their programming skills experientially. The project lab culminates in a live demonstration of the solution.

Alexander Fred-Ojala

Research Director, Data Lab
Sutardja Center for Entrepreneurship & Technology, UC Berkeley
M.Sc. Mathematical Statistics (Lund University)

Dr. Ikhlaq Sidhu

Faculty Director & Chief Scientist
Sutardja Center for Entrepreneurship & Technology, UC Berkeley
Ph.D. & M.S. (Northwestern University)

Dr. Sidhu has 75 patents under his name and is the inventor of seminal technology that is used in internet communications today. He is also the co-creator of Berkeley Method of Entrepreneurship.

This course is based on the Data-X framework designed at UC Berkeley for learning and applying AI, Data Science, and emerging technologies. This is continuation of the course DATAX-1. The participants will learn Neural Networks from the initial days. Perceptron, ANN, DNN, CNN, GAN will be covered in the greatest detail. Tensorflow, Keras, Spark, handling of Big Data will be explained in detail. Transfer Learning, Fine tuning, Data Augmentation and Reinforcement Learning will also be covered.

Dr. Ravi Kothari

Former Chief Scientist, IBM Research India
Professor of CS, Ashoka University
Ph.D. (West Virginia University)

IBM's first Distinguished Engineer from India, Dr. Kothari has deep strategy and innovation experience. His research interests are in Neural Networks, Pattern Recognition, Machine Learning, Big Data, Analytics, Streaming Analytics, Telecom.

Dr. James Shanahan

Lecturer, UC Berkeley School of Information
Former Research Scientist, Xerox Research
Ph.D. ML (University of Bristol)

Dr. Shanahan has spent the past 25 years developing cutting-edge information management systems. He co-founded several companies including: Church and Duncan Group Inc., RTBFast and Document Souls.

Alexander Fred-Ojala

Research Director, Data Lab
Sutardja Center for Entrepreneurship & Technology, UC Berkeley
M.Sc. Mathematical Statistics (Lund University)

The course will initiate the economist's dilemna: "Individual versus the aggregate welfare " and then proceed to cover the fundamental theorems in development economics detailing the interventions needed for desirable outcomes. Further, the following topics will be taught: preferences and production technologies, demand, supply and equilibrium, entities as strategic agents, market failure, law and economics, regulation, technology, growth and development.

Dr. Shubhashis Gangopadhyay

Managing Trustee, India Development Foundation
Ex-Director, ISI
Former Advisor - Finance Minister, Government of India

Shubhashis is associated with various international institutions such as University of Groningen, Netherlands and University of Gothenburg, Sweden. He was an Advisor to the Finance Minister, Government of India in 2008 during the global financial crisis. In Sweden, he held the prestigious Malmsten Guest Professorship in 2007 and the Bertil Danielsson Guest Professorship in 2008. He has been a member of the South Asia Chief Economist’s Advisory Council of the World Bank, Advisor to the Competition Commission of India, Member of the Board of the Centre for Analytical Finance, ISB and a member of the Bankruptcy Task Force of IPD, Columbia University. He completed his PhD in Economics from Cornell University, USA and his Bachelor’s degree from Presidency College, Kolkata.

India confronts us with many puzzles which seem to defy explanations. In this course an attempt will be made to answer some of the big questions that routinely appear before us in our everyday lives. Are we really rural? Why is caste so important, even in politics? Even though there are so many cultures and languages, how has India remained a unified nation state and democratic? On the face of it, Indians seem to be oblivious to public hygiene. Can this be true? Also, what makes us so susceptible to Godmen? The short, quick and convenient responses to all of these is to point to an unopened black box labelled “culture”. However, once we lift the lid we find culture speaking to us in different voices and the mysteries gradually find some kind of resolution.

Dr. Dipankar Gupta

Former Professor, Centre for the Study of Social Systems, Jawaharlal Nehru University
Board Member - Reserve Bank of India, the National Bank for Agricultural and Rural Development (NABARD)

Dr. Dharmendra Saraswat

Associate Professor, Agricultural and Biological Engineering
Purdue University

Gaurav Sharma

VP Analytics
Indifi Technologies

TERM 4: Dec 2 - Jan 10

In this course, the participants need to apply the knowledge acquired in the second Data Science and Machine Learning II course and work on a pre-defined project. Students work in teams or individually to encapsulate, design, develop, implement and test their project work. Optional curated lectures / support are provided on topics and programming practices relevant to the project. Students learn and improve their programming skills experientially. The project lab culminates in a live demonstration of the solution.

Dr. Ravi Kothari

Former Chief Scientist, IBM Research India
Professor of CS, Ashoka University
Ph.D. (West Virginia University)

IBM's first Distinguished Engineer from India, Dr. Kothari has deep strategy and innovation experience. His research interests are in Neural Networks, Pattern Recognition, Machine Learning, Big Data, Analytics, Streaming Analytics, Telecom.

Dr. James Shanahan

Lecturer, UC Berkeley School of Information
Former Research Scientist, Xerox Research
Ph.D. ML (University of Bristol)

Dr. Shanahan has spent the past 25 years developing cutting-edge information management systems. He co-founded several companies including: Church and Duncan Group Inc., RTBFast and Document Souls.

Alexander Fred-Ojala

Research Director, Data Lab
Sutardja Center for Entrepreneurship & Technology, UC Berkeley
M.Sc. Mathematical Statistics (Lund University)

Dr. Ikhlaq Sidhu

Faculty Director & Chief Scientist
Sutardja Center for Entrepreneurship & Technology, UC Berkeley
Ph.D. & M.S. (Northwestern University)

Dr. Sidhu has 75 patents under his name and is the inventor of seminal technology that is used in internet communications today. He is also the co-creator of Berkeley Method of Entrepreneurship.

Social Network Analysis (SNA) relates to mapping, understanding, analyzing and measuring interactions across a network of people. Multiple inference options exist for understanding the behavior of entities in a social network. One area of analysis is that of focusing on the content, to try to discover concepts, facts or opinions from the content posted by users. A second type of analysis is to focus on the users to discover networks in the community and to learn how those sub-groups get formed or change. Using SNA, analysts can explore questions related to social networks such as Who are the members to watch?, What are they saying?, Where do they interact?, Strength of interactions, Emergence of sub-groups? etc. This course will focus on developing Social Network Analysis (SNA) based models and understand their implications for decision making. The course will be taught with equal emphasis on theory and application. Theoretical concepts will be explained through examples from the field and the applications will be covered through Gephi software designed for the analysis of network data will be used.

Dr. Jai Ganesh

Senior Vice President, Head Mphasis NEXT Labs

Modern applications need to be built in a distributed manner, i.e., from components that are not located on a single machine. This is the case for a phone or a browser application that needs to communicate with a cloud system, the cloud system itself that servers users, a data processing system, a machine learning system, etc. As a technology leader, one needs to understand how such systems work so that one can architect or influence architectures for a problem being considered. This course will present various aspects of distributed systems that are critical for building current and future applications. It will cover topics such as remote communication, distributed storage, caching, consistency, availability, and scalability. The student will learn concepts along with the knowledge of the popular systems used in industry.

Dr. Atul Adya

Principal Engineer
Google
Mountain View, California

The Challenge Lab will be an entrepreneurship oriented course to pick up a problem area from the Grand Challenges seminar series and try to design a solution as well as a company to sell it. The topics will include: roles and importance of team, opportunity identification, rocket pitches, customer validation, preto-prototyping, business validation and present mockups. Mentoring will be provided through the course, and at the end of the first segment, a decision will have to be made by the team whether to pivot or persevere.

David Law

Director, Global Academic Programs
Sutardja Center for Entrepreneurship & Technology, UC Berkeley
CEO, Venture Dojo
MBA (Arizona State University)

Alok Mittal

Co-Founder & CEO
Indifi Technologies
Founding Member
Indian Angel Network

Sebastian Foucaud

Chief Data Officer
HRS Group, Germany
Ph.D. (Aix-Marseille University)
M.S. (Université Claude Bernard Lyon 1)

Dr. Foucaud's current research looks at how Data Science can be used to make business decision and gain insights. He is an advocate of using Big Data to change the way business is conducted. Prior to this, Dr. Foucaud tracked the evolution of galaxies.

All AI/ML problems need a proper configuration of the technology stack to solve the problem. This course aims to provide a hands-on training in understanding and detailing the technology stack. Data tools, distributed systems, cloud computing, performance management, software installation, CPU, GPU, TPU will be taught. An introduction to databases will also be provided.

Anurag Sahay

Vice President, AI and Data Sciences
Nagarro

Drishan Arora

Software Engineer
Google
Mountain View, California

This workshop addresses issues that are central to leadership: followership, wealth creation, wealth distribution, innovation, critical thinking, cross-sector collaboration, intra-group and inter-group dynamics, creating possibilities, organizational politics, shaping the future, abundance and scarcity. It builds on the thinking found in psychology, anthropology, sociology, management, politics, economics and philosophy. It starts with the premise that leadership requires a form of thinking that transcends the conventional. However, it stands on the shoulders of the reasoning processes used by organizational members and managers who are addressing every-day complexities, as well as the mundane. Leadership thinking is done in concert with, but is not captive to the conventional.

The focus is on developing new thinking capabilities about many themes. This workshop is both theoretical and practical. Participants can expect to be stretched to think in both the most abstract and the most concrete ways. No theory divorced from reality will be treated as relevant. And no questions of application (“what we could or should do in any situation”) that are not attached to meaningful and robust theory will be entertained. The learning is dynamic, and everyone is asked to push the envelope of our reasoning powers. Our deliberations will be relevant to people working in all types of organizations, will have a global flavor and will be focused on both the present and the future.

Dr. Kenwyn Smith

Professor, Organizational Behaviour
University of Pennsylvania

TERM 5: Jan 13 - Feb 21

This is an introductory graduate-level course in human-computer interaction. The course introduces students to HCI techniques and given them experience in conducting experiments with human subjects. It also provides some connections between Computer Science and other disciplines.

Dr. Sudheendra Hangal

Professor of the Practice in Computer Science, Ashoka University
Ph.D. & M.S. (Stanford University)
B.Tech. (IIT Delhi)

Currently researching social computing and human-computer interaction, Dr. Hangal was the Associate Director for the Stanford Mobisocial Lab. He is the Founder & CEO of Amuse Labs.

This is a Systems Thinking course, which will discuss some foundational underpinnings, look at historical failures, discuss how to take a systems oriented approach, and apply Systems Thinking to a prescribed problem. The foundational underpinnings might include Universal Design and Risk Analysis. Historical case studies may include, for example, Therac 25 (radiation treatment machine), Ariane 5 (rocket launch system), Volkswagen Emissions Scandal, Denver International Airport Baggage Handling, Boeing 737 MAX and others. Rather than simply reviewing each historical case study, students will outline potential success and failure modes for each of the case studies. Failure mode analysis will have particular focus on risk analysis, including potential risk, probability of occurrence, significance of occurrence, and mitigation. Finally, students will apply the foundational underpinnings (that is, how to succeed) and the historical failures (that is, how not to fail), to a prescribed problem such as the design of a small 'system'.

Dr. Dave Chesney

Toby Teorey Collegiate Lecturer CSE, University of Michigan
Former Engineer, General Motors
Ph.D. & M.S. (Michigan State University)

Dr. Chesney's rich experience is split almost evenly evenly between industry and academia. His research focuses on Socially Relevant Computing, Assistive Technology, Universal, Inclusive and Individual Design, Pedagogy, Ethics and Technology.

Dr. Rajeev Barua

Professor, Dept. of Electrical and Computer Engineering
University of Maryland, College Park
Ph.D. & M.S. (MIT)
B.Tech. (IIT Delhi)

Dr. Rajeev Barua is a Professor of Electrical and Computer Engineering at the University of Maryland. He received his Ph.D in Computer Science and Electrical Engineering from the Massachusetts Institute of Technology, and a Bachelor’s degree in Computer Engineering from the Indian Institute of Technology, Delhi. Dr. Barua's research interests are in the areas of compilers, binary rewriters, embedded systems, and computer architecture. He has published over 60 peer-reviewed publications, and holds four granted patents. He is also the Founder of CEO of SecondWrite Inc, which markets a malware detection tool based on his research, where he has raised over $2M in public and private investment, and launched a product with several paying customers. Dr. Barua is a recipient of the NSF CAREER award in 2002, the UMD George Corcoran Award for teaching excellence in 2003, and the UMD Jimmy Lin Award for innovation in 2014.

In this course students get exposed to contemporary quantitative techniques for optimal decision making under uncertainty. They learn an important tool of Monte Carlo simulation, and get introduced to cutting edge ideas in probabilistic modelling and stochastic optimization including queueing, Markov chains, Multi-armed bandit methods, Logit model, maximum likelihood estimation technique, portfolio risk and deep learning predictive methods.

Dr. Sandeep Juneja

Professor and Dean
School of Technology and Computer Science
Tata Institute of Fundamental Research

This is the second segment of the Challenge Lab. Student teams will continue to develop their startup idea which will include continued customer validation and solution iteration. This second segment of the course will focus on the following topics: customer acquisition process, finance (understanding key metrics), legal & intellectual property, funding a new venture, storytelling and pitching a new venture, review and practice (prototype inspection, demonstration) and final presentations. Ample time will be provided for in-class project work and mentoring as projects mature and develop.

David Law

Director, Global Academic Programs
Sutardja Center for Entrepreneurship & Technology, UC Berkeley
CEO, Venture Dojo
MBA (Arizona State University)

The Four Foundational Elements of Leadership is a powerful 4-day course that is split into two sessions of 2 days each. Created inside a new paradigm of performance, this new framework of Leadership, when learnt and applied as per the design, will have each student walk out of the course being a leader and exercising leadership in all areas of their lives. The course uses the methodologies of Ontology and Phenomenology that enable the students to experience what they learn and personally be impacted. Ontology: The science of the nature and function of being. (In this course the being of being a leader and the source of the actions of effective leadership.) Phenomenology: A methodology that provides access to being and action as these are actually experienced and lived real time “on-the-court”.

Nirav Vyas

Senior Consultant
Vanto Group

TERM 6: Feb 24 - Apr 17

This term is dedicated to the Capstone Project. Each project will take place in teams and may fall in one of the following categories:

Industry Capstone: Typically teams will work from the company site

Research Capstone: under the supervision of a faculty/ researcher

Work on own Start-up: subject to a strong proposal and approval of Capstone Committee

CAREER WEEK I: Apr 20 - Apr 24

TERM 7: Apr 27 - May 22

Dr. AnnaLee Saxenian

Dean, UC Berkeley School of Information
Professor, UC Berkeley School of Information

The Internet of Medical Things incorporates all devices utilized to monitor, manage, and inform human health and well-being. Consequently, the IoMT incorporates traditional medical devices (e.g., pulse oximeters, pacemakers, and ventilators) as well as non-traditional medical devices such as smart watches, smart home devices (e.g., Amazon Alexa, Google Home), and connected automobiles. In this course, students will interactively learn the fundamentals of developing, interacting and controlling devices within the IoMT. Specifically, the course is divided into three modules focusing on: (i) platforms for monitoring health and collecting the right data securely and privately; (ii) clinical decision support utilizing machine learning to interpret data; (iii) safe personalized closed-loop physiological control. The course will utilize real IoMT case-studies to provide practical experience in developing safe, secure, and clinically-useful IoMT applications and systems.

Dr. James Weimer

Research Assistant Professor of CS, University of Pennsylvania
Research Assistant Professor, Children’s Hospital of Philadelphia
Ph.D. & M.S. (Carnegie Mellon University)

Dr. Weimer's research focuses on design, analysis, and security of Medical Cyber-Physical Systems and Internet of Medical Things. He addresses challenges arising from the intersection of data science, embedded systems, cyber-security and healthcare.

This will be an intense 2 day workshop around the four foundational elements of leadership. This is the second part of the lecture series, a continuation of Foundational Elements of Leadership course.

Nirav Vyas

Senior Consultant
Vanto Group

CAREER WEEK II: May 25 - May 29

TERM 8: Jun 1 - Jun 26

This course is more algorithmic rather than just data processing course. Participants will be taught how algorithms are designed in the area of epigenomics using genomic pattern recognition. The topics include introduction and background to epigenomics and genomic pattern recognition, reading and writing the genome, data-analytics to annotate the genome/epigenome, high-performance computing for data analytics at scale. Lastly, three emerging areas of research would be discussed to brief the participants about the future challenges.

Dr. Somali Chaterji

Assistant Professor, Biological Engineering, Purdue University
Ph.D. (Purdue University)
B.S. (North Carolina State University)

Dr. Pramath Sinha

Founder & MD, 9.9 Group Private Limited
B. Tech. (IIT Kanpur)
Ph.D. & M.S. (University of Pennsylvania)

Pramath Raj Sinha is a Senior Advisor of the Albright Stonebridge Group, India and the Founder and Managing Director of 9.9 Group Private Limited. Prior to founding 9.9 Group, he was a Partner at Mckinsey and led the ABP Group, one of India's leading and most diversified media conglomerates. Pramath helped set up and served as the Founding Dean of the Indian School of Business (ISB). He holds a Bachelor’s degree from IIT Kanpur and an MSE and PhD from University of Pennsylvania.

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