Interested Students

Key Notes for All Students

Read these items first.

  • Before sending an email to Dr. Shakarian inquiring about a position, please read this page first, and let him know in the email that you read this page in its entirety.
  • Note that Lab V2 has a somewhat different focus from Dr. Shakarian’s previous work. Lab V2 is primarily focused on symbolic artificial intelligence and neuro symbolic systems. The primary focus is not cyber security or social media.
  • All levels: if you are sending me an email, please include a resume, all transcripts (undergraduate and graduate, can be unofficial), and work samples (published papers, GitHub site, etc.). This will make for an easier conversation.
  • –> In your first email, tell me about a tough problem you solved, a personal project you worked on. I’m looking for people who can be dedicated to working independently to drive significant research results. If have a research paper, mathematical construct, or piece of software that you put some serious effort into over the course of a year, then please tell me about it. Self-starters, self-learners, and builders are the kind of people I want in Lab V2.

Ph.D. Applicants

At the time of this writing, I have no open positions for funded Ph.D. students in the lab and have a pipeline of several highly qualified candidates whom I have already evaluated. It will be very difficult to obtain a Ph.D.-level position in Lab V2 at this time.

The pursuit of a doctorate is a difficult journey and advising a doctoral student is something that I do not take lightly. I advise students pursuing doctorates in computer science, computer engineering, and data science. There are several base requirements that I look for, and competitive candidates should meet all of the following criteria.

  • Only students interested in doctoral programs in computer science, computer engineering, or data science can apply – I cannot advise students in other doctoral programs
  • Completed a bachelors degree in computer science, mathematics, or electrical engineering (with the bulk of coursework being computer-science related)
    • If you email me, you must identify which program you want to apply for, and check the deficiency courses in the handbook – this can be found with the links above
  • During the bachelors program, must have obtained a grade of A- or better in classes dealing with discrete math, calculus, algorithms, artificial intelligence, machine learning, and data structures; overall GPA of at least 3.5 and graduated in the top 5% of their undergraduate class
  • Have taken coursework in artificial intelligence and/or machine learning
  • Will have completed a masters degree in computer science or a closely related discipline prior to admission into the Ph.D. program with a GPA of at least 3.5 (on the American 4 point scale)
  • Must have taken coursework at the graduate level that requires significant mathematical maturity (500-level algorithms, combinatorial optimization, approximation algorithms, 500-level AI/ML/DL course are the type of coursework that I will look for)
  • 1-2 years of industry experience is highly desired, preferably in operational AI or ML work, experience in GPU parallelization is a plus
  • Have no more than 3 deficiency courses (contact SCAI Advising for more information)
  • Have taken and met requirements set by ASU SCAI advising for GRE scores
  • Proficiency in both written and spoke English along with the ability to pass the ASU SPEAK test
  • Significant contributions to 1-2 scientific papers relating to AI, ML, data mining, or optimization preferably published in a well-known IEEE or ACM venue
    • You must send me copies of the papers along with a paragraph describing your contribution to the papers.  For example, did you write code, conduct experiments, prove theorems, develop core ideas, write certain sections, etc.
    • I will not consider applicants who do not provide me the actual work to inspect.
  • Ability to meet all normal admission requirements for the program for which you are applying

If you meet all of the above requirement, then you can consider reaching out to me. When doing so, you must include in your email the following documents:

  • State in the email that you have read this web page and have met the requirements listed above
  • Resume
  • Transcripts for both BS and MS programs, translated into English
  • Copies of papers that are either published or pending publication (late-stage preprints are fine, but know that I need to see the actual papers to understand the nature of your work)

If you have followed these instructions, you should expect a fairly quick response (24-48 hours) – please write again if you do not. If everything checks out we will do an introduction call. This will more be getting to know each other and not evaluative. I may also ask you for a few specific references and I will schedule a private call with the references. If we both feel it makes sense, the next step is for one or more evaluative calls that normally consists of me sending you a scientific paper (which may or may not have come from my group) and then having a follow-up discussion. Based on how that call goes, we would then work toward getting you a RA or TA position (depending on funding) and I would agree to be your advisor.  Also note that if you are being seriously considered for a Ph.D. position in the lab, to expect multiple calls that occur during business hours in Arizona (typically 8:30am-5pm, U.S. Mountain Standard Time, which is same as Pacific time during the summer).

I often teach class and the classes involve teaching assistants and graders. Typically, teaching assistants are Ph.D.-level students, while graders are often MS-level. If you are interested in TA’s for me, it is best to write after the current semester is over or between semesters, as these positions are not open during the term. Please note that I get very many requests for such positions and may not have time to respond to all requests.

Masters Student Looking to Conduct Research

There are many ways masters students can get involved in research at ASU, including the following:

  1. Research volunteer. This is often the best way to start, and successful volunteering can result in a paid position or the professor agreeing to be your thesis advisor. I also routinely select teaching assistant and graders from volunteer graduate-level researchers as well. That said, I am very selective on picking volunteers (as it is an investment in my time) and I look for many of the same things as I look for in PhD students. Some things to set yourself apart: straight A’s in all undergrad CS classes, publications in respectable venues as first author, experience working in a research lab, excellent programming and mathematical ability, and industry experience in Google, Meta, Microsoft, IBM, or similar.
  2. FSE’s MORE Program. The MORE program provides a small stipend for semester-long MS-level research projects, and I am interested in supporting these efforts for people who have previously volunteered for the lab and wish to pursue a topic that closely aligns with the goals of the lab.
  3. Thesis Advisor. Some MS students may choose to pursue a thesis option. I am very selective in the MS students that I advise for thesis and typically only advise to those who are already volunteering in the lab.
  4. Paid Research Assistant Position. From time to time, we have open positions for MS research positions. However, when we do, they are filled very quickly as we have a cohort of MS-level volunteers who get priority.

Note that I typically only engage with MS students once they have arrived at ASU.

Undergraduate Researchers

In general, I only consider undergraduates (for paid positions or programs like FURI, GCSP, honors, capstones, or independent studies) who have volunteered for the lab for a few months. Further, I do not accept all students desiring to volunteer. In general, I look for the following items:

  • A real interest in the current topic of Lab V2 (as seen on this site)
  • Willingness to commit to longer-term (1-2 year) projects
  • Excellence in mathematics for computer science (in particular, A’s in courses like discrete math, data structures, theoretical computer science)
  • Excellent coding ability in Python and at least one other language (Java, C++, Scala, Ada, etc.) demonstrated in some project or industry experience (e.g., GitHub site)
  • Some experience in AI or machine learning (e.g., ASU’s CSE 475, CSE 472, industry experience, or significant personal projects)
  • All-around high grade-point average

On very rare occasions, for certain highly qualified students looking to gain experience, I will mentor a non-ASU volunteer (typically a 4th-year undergraduate). The idea is that such an undergraduate already possesses many of the skills listed above for a Ph.D student. Volunteers will be vetted thoroughly to include interviews with both the volunteers and reference calls. Please note that it is extremely rare for me to accept non-ASU volunteers.

High School Students

If you are an exceptional high school student in Arizona and have demonstrated exceptional skills in areas such as computer programming, mathematics (especially discrete mathematics), machine learning, and/or software development I would be happy to talk. Note that I do not work with very many high school students (I have worked with 2 in over a decade of teaching at the university) but it is something that I am happy to do. If you are just interested to talk about ASU, computer science, or research, I’m happy to do so as well. Just a few notes:

  • Students must be attending high school within the state of Arizona
  • Students must have demonstrated high proficiency in Python
  • Students must have demonstrated that they have written code that uses machine learning
  • Students must have received a grade of “A” or higher in all high school math and computer science classes

Recommendations

Recommendation letters are generally only provided for students who work in the lab for a period of 6 months or more, have shown excellent performance during that time, and have not been involved in disciplinary issues.

Additional Lab Guidance

In addition to lab guidance issued upon joining, the guidance on this page is also lab policy. Specifically:

  • Students who are not performing well academically may be dismissed from the lab
  • Students who do not communicate with the lab director for more than two weeks will be dismissed from the lab
  • Volunteer memberships in the lab will be re-evaluated on a monthly basis