With the goal of harnessing the untapped potential of Iranian-Americans, and to build the capacity of the Iranian diaspora in effecting positive change in the U.S. and around the world, the Iranian Americans’ Contributions Project (IACP) has launched a series of interviews that explore the personal and professional backgrounds of prominent Iranian-Americans who have made seminal contributions to their fields of endeavor. We examine lives and journeys that have led to significant achievements in the worlds of science, technology, finance, medicine, law, the arts and numerous other endeavors. Our latest interviewee is Babak Hassibi.
Babak Hassibi is the inaugural Mose and Lillian S. Bohn Pofessor of Electrical Engineering at the California Institute of Technology, where he has been since 2001. From 2011 to 2016 he was the Gordon M Binder/Amgen Professor of Electrical Engineering and during 2008-2015 he was the Head of the Electrical Engineering Department, as well as Associate Director of Information Science and Technology. Prior to Caltech, he was a Member of the Technical Staff in the Mathematical Sciences Research Center at Bell Laboratories, Murray Hill, NJ. He obtained his PhD degree from Stanford University in 1996 and his BS degree from the University of Tehran in 1989. His research interests span various aspects of information theory, communications, signal processing, control and machine learning. The work of his research group has been influential in the development of wireless communications standards (WiFi, 2G, 3G and 4G cellular) and his PhD students have gone on to leading positions in academia, industry and finance.
Hassibi is a recipient of the US Presidential Early Career Award for Scientists and Engineers (PECASE) and the David and Lucille Packard Fellowship in Science and Engineering. He serves on the Scientific Advisory Boards of the companies InSilixa Inc, EmeraldLogic Inc, and PlueBrintBio Inc, and is on the Advisory Board of the School of Information Sciences and Technology at Shanghai Tech University.
Where did you grow up and go to school? What and who were your most formative influences when you were growing up?
I was born in Tehran in 1967. When I was one-year-old my parents moved abroad (first to the US and then to Canada) so my father could attend graduate school at UCLA and then at the University of Waterloo. I lived in Los Angeles between the ages of one and five and in Waterloo, Canada between five and eight. After my father finished his graduate education, we returned to Iran on New Year’s Eve of 1976. I first began school in Canada, where I attended Northdale Public School in Waterloo, Ontario from kindergarten midway through third grade. It was a wonderful school and I have the fondest of memories of that time, as I was provided with an excellent education – so much so that when we returned to Iran I was pushed up to fourth grade after spending only a couple of days in third grade. I visited Waterloo a few years ago and went to my old school site – the building was still there, but the school had been closed for a couple of years.
When we returned to Iran it was January and midway into the school year. In those days there were very few Iranians abroad (especially in Waterloo) and so my Persian was very rudimentary – I could understand but could not speak very well and did not know how to read or write. For this reason, my parents tried to enroll me in one of the several international schools that existed in Tehran at the time (such as Community School, Iran Zamin, Tehran American School, etc.). Most had no room for a student entering mid-year, but fortunately we found a place in Rustam Abadian International School. The school was named after a philanthropic Zoroastrian Iranian who had donated the land (as well as some funds) for the school, but who had passed away before the school’s actual founding. It was located in Niavaran, a bit to the North-East of the Niavaran Palace and Niavaran Park, and its two principals were Ms. Changizi and Ms. Taheri-White. (I believe an incarnation of the school currently exists in London and is being run by Ms. Taheri-White.) The school was based on the British educational system (GCE) and the school population was half Iranian and half from the British Commonwealth. For the Iranian students, there were extra classes in Persian. In fact, I should mention a very kind Persian tutor I had at Rustam Abadian (with whom I would spend an hour each morning before school started), Ms. Shafii, who over the span of a few months was able to improve my Persian reading and writing to the level that I was able to attend fifth grade in Persian in the Fall of 1976.
The 1978-79 revolution happened when I was in seventh grade. School closed in October and did not reopen until March. When the school reopened, virtually all of the foreign students, a good number of the Iranian students and a large fraction of the teachers had left the country. I was at Rustam Abadian for eighth grade as well until the revolutionary government closed down all international schools. (The school Rustam Abadian no longer exists, but I believe the buildings are currently in use for an all-girls high school.) Thus,starting ninth grade, I attended Soroush-e-Azadi High School. In fact, my first day of high school coincided with the start of the eight-year long war with Iraq.
I graduated from high school in 1984 and took the konkour exam in which I ranked 6th in the “Math-Physics Group” (which is what students attempting to study STEM fields must take). Earlier that year I had also ranked 4th in the National Iranian Mathematical Contest (which is now used to select Iran’s Math Olympiad teams). I entered the University of Tehran to study in Electrical Engineering. This was the second general nationwide or “konkour” exam held after the Cultural Revolution (during which time universities were closed for 3 years), and was an exceptionally competitive one given the large backlog of students that had been created. Most of the top students elected to study electronics engineering, either at Tehran or Sharif (which is an example of group think that is still largely prevalent in higher education in Iran), and my classmates were essentially from the top 40 of the “konkour” exam. I have met many smart individuals and groups during the course of my career but can attest that, pound for pound, the smartest group of people I have ever interacted with were my classmates from my undergraduate days at the University of Tehran. Many have now gone on to distinguished careers with leadership positions in industry and academia. Sadly, almost all have emigrated from Iran and only 2-3 remain in the country (something that continues to be quite common for top students graduating in years since).
As I have grown older I have come to realize the great debt I owe to the many individuals who have been in my life and for the opportunities that I have been given. First and foremost are my parents. I owe most of what I am to them. Our family in Iran was middle class but well educated (all my uncles have doctorate degrees), so getting a PhD was almost a given. However, the greatest influence in terms of educational success was my grandfather, Kazem Hassibi. He belonged to the first generation of students that Reza Shah sent to study abroad and was the first Iranian accepted to the Ecole Polytechnique in Paris. He subsequently studied at the Ecole des Mines and returned to Iran to teach Geophysics and Mining Engineering at the University of Tehran. During the Oil Nationalization Movement, he was Mossadegh’s oil adviser, Member of the Majlis from Tehran, and one of leading figures of the National Front. My grandfather has always been a role model for me in terms of excellence, rigor and integrity.
Another influential individual I should mention was my 10th grade classmate, Mehran Mesbahi (now a Professor of Aerospace Engineering at the University of Washington, Seattle), who first introduced me to calculus and set me on the course of studying well beyond school textbooks (something that has served me very well over the years).
What has been your personal key to success? What were the biggest inspirations for your career?
Success of any kind requires dedication, hard work and perseverance. Hard work and perseverance, in turn, require an engine and fuel. The engine symbolizes knowing your strengths and what you are good at and the fuel is having passion for what you are doing. Early on, I recognized that my strengths were in mathematics, and so much of what I have done in my career in engineering has appealed to this strength. Midway through my undergraduate studies I toyed with the idea of switching fields to theoretical physics. Later on I recognized that many of the mathematical ideas that were attractive to me could be used to solve real-world engineering problems of great consequence. This has continued to fuel my passion for my work and research.
In the United States, I have had the privilege to be associated with three great institutions of research and higher education: Stanford, Bell Labs and Caltech. I came to Stanford for graduate school in 1991 after finishing compulsory military service in Iran. My adviser at Stanford was Thomas Kailath, who is something of a “Renaissance man” in terms of the diverse set of research problems he has worked on. He was one of the main proponents of Mathematical Engineering – the uncanny power of mathematics to model and solve engineering problems. In 2015 he received the National Medal of Science from President Obama (the highest scientific award bestowed in the US). Stanford is arguably the world’s leading university in terms of technology transfer and spinning off startups. I joined Bell Labs in 1998 (after a postdoc stint at Stanford) in the Mathematics of Communications Research Department. While the current Bell Labs is barely a shadow of its former self, the contribution of Bell Labs to technology in the 20th century (the invention of the transistor and laser, the creation of information theory and control theory, the development of the C programming language and the Unix operating system, etc.) far surpasses any other institution. At Bell Labs my department head was the late James Mazo, a true gentlemen and scholar, who gave the members of his group the utmost freedom to pursue their research interests. I am truly indebted to him for the belief he had in me. My most productive years, research-wise, were undoubtedly the two years I spent at Bell Labs. The theoretical work that I undertook there (in collaboration with others) made its way to practical wireless communication systems (both WiFi and cellular) within a decade –something that has been truly rewarding. Since 2001, I have been at Caltech which, among institutions of higher education in the US, is arguably the one most devoted to the pursuit of scientific inquiry in its purest form. I chaired the Electrical Engineering Department at Caltech from 2008 to 2015.
What kind of research do you conduct in your lab? Could you please identify a couple of research articles that you value as of high importance produced by your lab?
At a high level, the work done in my lab has to do with the analysis and design of complex engineering systems. We look at such systems not at the level of device or circuits, but at the level of the subsystems that comprise them and at how these various subsystems should interact with each other, exchange information, perform computations, etc., in order to optimize some desired performance. In fact, today we are moving towards a massively connected world populated by a seamless network of intelligent, dynamic distributed systems engaged in a shared interaction with the physical world and each other through unreliable sensors, actuators and noisy communication channels. This network is often referred to as the Internet-of-Things (IoT). Such a complex system cannot be simply put together in an ad hoc and haphazard fashion and requires careful mathematical modeling, analysis and optimization. In my research, mathematics is not just used for modeling and analysis, but also as a creative tool to identify and use mathematical structures to solve problems of interest.
More specifically, what we do spans fields referred to as control theory, communication theory, signal processing and machine learning. Control has to do with the question of how to influence a system so that it has some desired behavior. Classical applications are in the control of aircraft, missiles, chemical plants, etc. Modern applications include the control of autonomous drones and robots, self-driving cars, congestion control of packets in the Internet, control of the SmartGrid and so on. Communication theory has to do with the reliable transmission and storage of information and is what has, among other things, allowed the mobile telephone revolution that has improved and continues to improve peoples’ lives across the globe. Signal processing and machine learning have to do with the problem of extracting actionable information from data, or learning new facts and patterns from data in an automated way. We are currently in what is referred to as the era of Big Data where we are confronted with a deluge of data (images, social network data, bio-informatic data, etc.) and where it is necessary to design efficient algorithms that can extract the desired information and avoid the “curse of dimensionality.”
One of the important results that came out of my lab is work done in 2005 with my former student Masoud Sharif on scheduling wireless transmissions in cellular networks whose base stations employ multiple antennas. Our method has been adopted by 2G, 3G and 4G wireless standards so that any phone conversation initiated anywhere in the world employs our scheduling algorithm. Another important result appears in a series of papers from 2014-16 by my former and current students Samet Oymak, Christos Thrampoulidis and Ehsan Abbasi, where we develop a framework for the performance analysis of a wide range of convex-optimization-based algorithms that have become very popular in machine learning. Prior to our work it was not possible to evaluate the performance of such algorithms. I believe our analysis will become textbook material and will be the way in which these algorithms are taught to future computer scientists and engineers.
Your research and teaching interests include communications theory, information theory, adaptive and statistical signal processing, robust and distributed control, DNA microarrays, random matrices, group representation theory. Could you please shed further light on your research that has made significant contributions to your fields of interest?
In the area of communications most of my significant results have been related to multiple antenna wireless communications. We have done pioneering work on what are called “space-time codes” or objects that describe how to optimally transmit signals across both antennas (space) and time. These codes and their variants are used in various standardized systems. We have also done breakthrough work on training based schemes in multi-antenna communications where the communication medium must be “learned” before any information transmission can be performed. This problem has gained additional relevance in the massive MIMO (multiple input multiple output) communication systems that will be employed in 5G communications and which will entail many hundreds of antennas at the base station. We have also solved open problems on how to secretly communicate in such systems. Random matrices and group representation theory are two fields of mathematics that have proven indispensable in our solutions to the above engineering problems.
My group has also pioneered the development of information transmission schemes for control systems (where delays cannot be tolerated) such as tree codes, and has also studied rate-cost tradeoffs in control. We have studied epidemic spread in complex networks and have developed various algorithms for compressed sensing and structured signal recovery in machine learning. I am particularly excited about very recent work done with my former student Kishore Jaganathan on the problem of phase retrieval, or how to obtain the phase of a signal from phaseless measurements. We have provided an optimal solution (requiring only three phaseless measurements) with a myriad of applications in 3D imaging, phaseless radar (which can significantly reduce the cost of radars in self-driving cars for example), machine-to-machine communications, etc.
Another important project to come out of my group is the invention of the real-time DNA microarray – a platform that enables the fast and inexpensive molecular diagnostics of diseases. This technology is currently being commercialized by a startup, InSilixa Inc., which recently raised series B funding.
What are the research avenues you are exploring for the next few years?
In the next decade we will witness the convergence of communication, computation and control. The reason for this is that we will be confronted with a countless number of devices that can wirelessly communicate with each other, can perform calculations and make decisions and that can interact with the physical world and control their environment. Think of self-driving cars communicating with one another to avoid collisions, communicating with stop lights to request passing access and downloading Google Maps to study traffic patterns and make decisions on what routes to take. Deciding how to design the communication protocols, messaging systems and distributed control algorithms is a major challenge, as one needs to contend with time-varying channel conditions, stringent delay constraints and severe safety requirements. The potential impact of the correct design of such systems will be comparable to the impact that the wireless transmission schemes designed in the late 90’s and early 2000’s had on the development of mobile wireless telephony. It will change the world as we know it. Thus, I am extremely excited to work in this area.
As I mentioned earlier, we are in the era of Big Data. Therefore, I envision continuing to work in the area of machine learning algorithms – especially those that deal with multi-modal data. The goal will be to develop algorithms that are efficient (and can scale) and that come with provable performance guarantees. The problem of storing immense amounts of data (think of the data centers operated by Facebook, Instagram, etc.) is also critical and I will be studying distributed storage and computation.
Finally, I have always been interested in the problem of information transmission over distributed networks (what is known as network information theory). Current networks, such as the Internet, through protocols such as TCP-IP, view information as a flow and route packets through a network as one would route the flow of a fluid. Flows satisfy certain conservation laws (such as the conservation of mass) which information does not: information can be reproduced and copied; it can be processed, compressed and combined with other pieces of information (things that one cannot do with a fluid). As a result, it is known that the information capacity of networks can be significantly increased over what TCP-IP routing provides. However, how to best do this is unknown. It is related to some deep mathematical questions about the joint entropy of a collection of random variables, something I intend to explore.
The past 25 years of my career have been a very exciting one in terms of the development of technologies that have impacted the lives of billions of people on the planet in a positive way. I envision the next 25 to be as exciting.
Can you tell us about your research which earned you the most awards and recognition?
Because of the impact that it has had on mobile wireless communication (both WiFi and cellular systems), my work in the communications area is my most cited as well as the area for which I have been most recognized and awarded. In fact, the citation to the Presidential Early Career Award I received from President George W. Bush reads, “For making fundamental contributions to the theory and design of data transmission and reception schemes that will have a major impact on new generations of high-performance wireless communications systems.”
How do you see your field changing? What excites you most about the future of your field?
The one thing that never changes is the constancy of change itself. With regards to my field, what I see is a confluence of different areas. The boundaries between certain areas of electrical engineering, such as signal processing, control and information theory, certain areas of computer science, such as machine learning and networks and certain areas of applied mathematics, such as computational statistics and optimization are blurring. People from these different fields are coming together to work on a diverse set of problems in networks, Big Data, robotics, etc. Many of the interesting problems are cross disciplinary or multi-disciplinary and straddle the boundaries of established fields; many ideas from engineering are now influencing faraway fields such as biology and the social sciences. In addition to guiding how research is done, this will have an effect on engineering education itself. Current engineering departments are essentially constructed based on 19thcentury technology. Back then it was thought that what mattered was the platform on which the engineering was performed: if you knew chemistry you were a chemical engineer, if you knew electricity you were an electrical engineer, if you knew mechanics you were a mechanical engineer, and so on. Increasingly, people are beginning to realize that the main divide is between Physical Engineering (be it chemical, electrical or mechanical) and Information Engineering (which deals with data, computations, communications, etc.).
All these developments are exciting for me.
Since you have a PhD in electrical engineering, can you address the relationship between academia and industry in your field? How can their relationship be optimized?
Engineering is an applied field where the goal is to create technological innovations that benefit society and solve real-world problems. This is true both of engineering practice in industry and of engineering research in academia. Engineering research in academia, however, is distinguished by the fact that it is more forward thinking and it explores the boundaries of what is possible. It is also often concerned with the discovery and development of general principles, ideas, design methodologies and theories that, rather than apply solely to a specific immediate application, have implications and applications to a broad array of problems. There is also an element of intellectual curiosity that is independent of any applications. This is not to say that engineering research in universities does not pay attention to industry – it absolutely does, and good engineering research always takes into account the economic and technological constraints of industry and is often inspired by the practical problems encountered there. Successful engineering research is many times spun off into startup companies or licensed by industry. But academia is not the place to solve the industry’s immediate problems. Most companies, whether large corporations or small startups, have teams of engineers who are capable of solving the problems they encounter. And, of course, many of the most successful companies are those that are aware of research that is performed at universities.
During my industry visits I am often pleasantly surprised by how up-to-date the various engineers are of the latest developments in the field and how dedicated they are to keeping themselves abreast of the latest scholarly publications in technical journals and conferences. While there are multiple mechanisms to foster the academia/industry relationship, such as offices of technology transfer and industry liaisons in universities, jointly-funded incubators and university relations offices in industry, much of the relationship happens organically through alumni networks, interactions between former students and their advisers and so on.
While the most successful example of academia/industry cooperation is what exists in the US today (which many other countries are trying to emulate), there is often a misperception that industry funds much of the engineering research in universities. While industry does provide some funding to universities (through various scholarships and occasional joint projects), by far the lion’s share of engineering research funding in universities comes from the federal government. One should think of engineering research and development in the United States as a triangle with three vertices: the federal government, academia and industry. Support from the federal government is critical to the ability of universities to perform innovative research and to pursue novel lines of inquiry. Not all university projects lead to direct applications in industry (though they do further push the envelope of knowledge), but those that do can have an enormous impact. The benefits the industry receives from academic research in turn create jobs, solve societal problems, improve the economy, and more – all of which directly benefit society, thereby justifying the federal government’s investment in academic research. This investment also helps maintain the independence of universities and their scholars in the pursuit of research problems, which promotes long term thinking and avoids the myopic obsession with the present. This federal government/academia/industry triangle, especially since the end of the Second World War, is what has created the modern research university in the United States, which has become the envy of the world. It is for this reason that it is critical, especially in the current political climate in the United States, that federal funding for university research be maintained at its current levels, better yet, increased.
Can you share your thoughts on your Iranian-American identity? What does it mean to be an Iranian-American to you?
This is an interesting question. I came to the United States in 1991 and have lived, studied and worked here since. During this time, my Iranian identity has not waned in the slightest – I take great pride in my heritage and am fully aware of where I came from and of the cultural/societal/familial background that molded me. However, over the years the American side of my identity has certainly waxed. I feel great pride in being an American and fully appreciate the great opportunities this country provides for its citizens and for the open-mindedness with which it embraces all of its inhabitants (while there are, of course, some flaws, these pale in comparison to most other countries in the world). I have become especially aware of my Iranian-American identity since the birth of my children. While my wife and I were born and raised in Iran, my children are second generation Iranian-American and this is the identity that they will carry with themselves throughout their lives. I have also come to realize that there is no escaping this identity: it is the prism through which others often see you at first and project their impressions upon.
Thus, I think what you are doing with this interview series is a noble endeavor. There are a great many very successful Iranian-Americans in a diverse set of fields ranging from the arts and culture to news and media, to science and industry and to business. The Iranian-American identity is what we as Iranian-Americans make it to be and introducing the achievements of Iranian-Americans to the society at large will help in the creation of this identity.